v>EPA
           United States
           Environmental Protection
           Agency
                 Office of Air and Radiation
                 Washington D.C. 20460
EPA 400/1-87/001F
December 1987
Assessing the Risks of
Trace Gases That Can
Modify the Stratosphere
           Volume VI:
           Technical Support Documentation
           Production Projections
<**^fWlll'

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    Assessing The Risks of Trace Gases
     That Can Modify The Stratosphere
Volume VI: Technical Support Documentation
            Production Projections
      Senior Editor and Author: John S. Hoffman
             Office of Air and Radiation
        U.S. Environmental Protection Agency
             Washington, D.C. 20460
                 December 1987
                          U*5. EnTironmental Protection Agency
                          Region 5, Library (5PL-16)
                          ,;,-.; S. Dearborn Street, Boom 1670
                          Chicago» ~IL  60604

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                                 APPENDIX C

                              TABLE OF CONTENTS
                                                                           TAB
Probabilistic Projections of Chlorofluorocarbon Consumption. 	  1
by William D. Nordhaus (Yale University) and Gary W. Yohe
(Wesleyan University) (1986)

Scenarios of CFG Use:  1985-2075. by Michael J.  Gibbs (ICF  	  2
Incorporated) (1986)

Product Uses and Market Trends for Potential Ozone Depleting 	  3
Substances 1985-2000. by James K. Hammitt,  et al. (RAND
Corporation) (1986)

Joint Emission Scenarios for Potential Ozone Depleting 	  4
Substances, by Frank Camm,  et al. (RAND Corporation) (1986)

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             PROBABILISTIC PROJECTIONS OF CHLOROFLOUROCARBON

                                CONSUMPTION
Dr. William D. Nordhaus
Department of Economics
Yale University
New Haven, CT  06520
Dr. Gary W. Yohe
Department of Economics
Wesleyan University
Middletown, CT.  06457
                                 June 1986

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     Recent scientific evidence  indicates  that  significant  ozone  depletion




is likely to occur if atmospheric concentrations  of chloroflourocarbons




(CFCs) continue to grow at current rates.   The  precise health and welfare




ramifications of this depletion are not yet completely understood,  but the




potential for widespread increases in the  incidence of skin cancer, along




with damage to animals and crops, and dramatic  climatic change is now




apparent.  Increased concentrations are a manmade phenomenon, the result of




increased production and emission of a bevy of fluorocarbons over the past




40 years.  Reductions in the emissions of these compounds are possible,  but




can be realistically expected only if the cost of the required regulatory




activity can be justified in terms of avoiding expensive environmental




damage.




     Assessing the value of a policy response to the potential environmental




consequences of CFC emissions is thus a vital undertaking,  but it  is




inextricably linked with forecasting CFC emissions into the next century.




It is  in the next century that most of the potential problems linked with




CFC  emissions are likely to occur, but it  is in  the next few decades that




policy designed to avoid those problems would be most  effective and least




costly.  The need for long term  forecasting is thus clear, but so  too is the




observation that such forecasting  is dominated by  uncertainty.  In the  case




of CFC's,  rates of emissions beyond the year 2000  will certainly  depend upon




circumstances  that cannot be accurately predicted.




      If  the appropriate decisions  are  to  be made in dealing with  the




potentially harmful  effects of emissions,  then,  a balance  of future  risks




 and costs must be struck.   Given the impossibility of conducting policy




 debate with any degree of confidence on the basis of one,  two,  or ten

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alternative scenarios, this balance must be weighed in the context of not




only the estimates of most likely future emissions, but also




probabilistically weighted ranges of other possible trajectories that




deviate from any specified "best guess".  Only then can policymakers survey




the full menu of policy options --a menu that may include direct and




immediate intervention, to be sure, but might also include contingency




intervention schemes to be triggered if future scientific findings indicate




that the emissions or health risks are more serious than is now thought.




Despite some significant effort in the past, the literature has not yet




provided policymakers with the evidence required either to evaluate the




relative value of options or to legitimize any but the simplest of options




listed there.




     The earliest studies undertaken under the auspices of the National




Academy of Sciences produced estimates of future emissions of CFC's by




simply projecting constant emissions forward from a specified date [see,




e.g., NAS 1976 and 1979].  While these studies helped bring CFC emissions to




the attention of the world scientific community, they were unable to provide




an accurate understanding of the sources of the various forecasts, the




uncertainties surrounding those forecasts, or the relative social values and




costs of the potential policy alternatives.   A second generation of




analyses overcame some of the shortcomings of the initial exercises by




constructing precisely articulated scenarios of how the future might unfold




[e.g., Gibbs, ICF, 1986 and Quinn et. al., RAND, 1986].  Each traced future




emissions trajectories from well defined models based upon sets of




explicitly recorded assumptions and statistical analyses.  While these




studies have been successful in identifying interesting "what if" scenarios,

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they have still been nonprobabilistic in nature.   They continue,  therefore,




to fail to provide policymakers with any quantified notion of the likelihood




of the specified scenarios.




     The present study will try to provide the next step by explicitly




incorporating uncertainty into the modeling exercise so that more definite




estimates of likelihoods can be associated with possible future trajectories




of CFC emissions.  The technique to be employed,  called probabilistic




scenario analysis, was designed by Nordhaus and Yohe [1983] to investigate




the problem of forecasting carbon dioxide emissions and concentrations from




an economically consistent model of future energy markets.  It identifies




the most important sources of uncertainty in our present understanding of




future CFC emissions, examines the current knowledge and disagreement about




these variables and parameters, specifies a range of values that they might




assume with specified relative frequency, and incorporates both the ranges




and their relative frequencies into a simulation or Monte Carlo exercise.




The focus is not, therefore, on resolving uncertainty.  It is, instead, on




representing existing uncertainty as accurately as possible and integrating




that uncertainty explicitly and consistently into the analysis.  The results




not only provide a "best guess" trajectory for CFC emissions through the




middle of the next century, but also suggest a set of alternative




trajectories and associated probabilities that quantify the range of




outcomes  that  is consistent with  the current state of knowledge and




ignorance.




      Section I  describes the analytical  framework within  which the




probabilistic  scenario  analysis is  conducted; coverage  of the details  of the




modeling has been  relegated to supporting appendices.   Section II reviews

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the judgmental values assigned to the major random variables identified in




Section I.   Section III presents the results of the scenario analysis




assuming only the regulatory impetus on reducing aerosol consumption that




produced the ban in the United States nearly a decade ago.   Section IV




follows with an extension of the regulatory environment to include the




indefinite continuation of the voluntary restrictions now imposed on aerosol




consumption by various countries across the rest of the world.  Comparisons




of the aerosol consumption distributions produced in Sections III and IV can




therefore provide some insight into the possible effect of continuing




voluntary regulatory initiatives outside the United States.
I.  The Analytical Framework.









     This study analyses the future worldwide emissions of four separate




"CFC commodities": CFC-11 aerosols, CFC-12 aerosols, CFC-11 nonaerosols, and




CFC-12 nonaerosols.  Each is derived from the sum of CFC consumption in the




United States and the rest of the world, but the models used to develop the




individual forecasts have different empirical foundations.  Because the




models for both components of the four CFC commodities are nonetheless




identical in structure, it is convenient to describe that structure.  It is




also convenient to focus initial attention on the modeling that produced the




consumption trajectories, because their derivation is the most elaborate




part of the analysis.  CFC emissions flow in part from consumption through a




straightforward linear allocation between emissions from current consumption




and deposits into a CFC bank.  The rest of current emissions are the result

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of leakage from the existing CFG bank and therefore also depend upon (past)




consumption.  To describe the modeling that produced the consumption




scenarios is thus to describe the heart of the analytical framework.




     The central uncertainty in projecting future CFC emissions can be




traced to the imprecision with which we understand the demand for CFC




consumption.  The general process employed here to model that demand is




illustrated in Figure 1-1.  Four separate factors, taken in this study to be




exogenous and uncertain, directly effect the demand for consumption:




technological developments including the development of new products and




processes; the level of population and its distribution across different




regions of the globe; the level of per capita income and its distribution




across different regions of the globe; and the regulatory environment.




Depending upon the demand schedule for CFC consumption, each of these four




plays a role in tracing out the path of future consumption.




     The approach taken here to model CFC demand is based upon four major




premises.  First of all, most of the observed history of CFC use in the




United States mirrors the experience of a rapidly developing technology in




the early phase of its growth cycle.  It should not, however, be expected




that the rapid growth rates of the last two or three decades will continue




into the future as the CFC-using technologies run their courses to  maturity




and market  saturation in  the United States.   In our demand modeling,




therefore, we recognize that the growth phase for CFCs has come to  an end




(or will do  so in  the near  future), and that  the  demand patterns for  CFCs




are likely  to resemble more conventional products  in  subsequent years.




     Secondly, it  is assumed that  CFC use  is  likely  to be  determined  by  the




presence or absence  of major new CFC-using products  along  with the  income

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 LEVEL AND DISTRIBUTION
     OF POPULATION
          LEVEL AND DISTRIBUTION
               OF INCOME
  TECHNOLOGICAL
  DEVELOPMENTS
a                            DEMAND FOR   \
                           ="C CONSUMPTION
TON   1
	-A
               REGULATION
Figure 1-1   Steps in the Generation of CFC Consumption and Emission

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elasticity of current CFC-using products.  If the inherent possibilities for




major new CFC-using products were to be low because the potential for




regulation inhibited research and development into new CFC uses,  then we




should expect that the volume of CFC use per unit of output in the United




States would remain stable or perhaps even decline.  If, on the other hand,




major new CFC-using technologies were developed, then, at least for




nonaerosols, the growth in CFC use could continue into the future.




     In addition, future trends in CFC use will be significantly affected by




the extent to which current CFC-using products are ones that tend to be more




or less extensively used as peoples' incomes rise (or, technically,




depending upon whether the income elasticities of CFC-using products are




greater or less than unity).  If CFC-using products are extensively




contained in CFC-using products that appeal to high-income consumers (like




automobiles or air conditioning), then CFC use will tend to rise more




rapidly than income.  Conversely, if CFCs are associated with products  like




food that tend to take a lower share of  income as income rises, then CFC use




will tend to rise relatively  slowly.




     In estimating CFC use outside  the United States,  finally, we view




development as a process through which,  abstracting from regulatory




constraints, technologies  that have emerged  in  the most advanced  countries




 (particularly  the United States) are likely  to be  increasingly adopted  by




 less  advanced  countries.   Put differently,  if  and  when a particular  country




 is able  to  attain  the  living standards  prevailing  in  the United  States, then




we expect  that country will  exhibit consumption patterns  similar  to  those




 supported  by  today's American consumer --to buy refrigerators and air




 conditioners,  to purchase  deodorants and insecticides, to  employ plastic

-------
foams and sprays, and so on.  When we project the consumption patterns of




the rest of the world, then, we begin with the assumption that CFC use will




be driven, as have many other commodities, by incomes, prices, and available




technologies.




     Figure 1-2 illustrates more specifically the determinants of U.S.




consumption over time.  A logistics equation defines a trajectory for




consumption per constant dollar of GNP (locus AB) that asymptotically




converges to an asymptotic CFC frontier (locus CF).   The notion behind this




frontier is that the growing technological maturity in CFC markets dictates




gradual movement toward a path of slow growth or decline in the income




intensity of CFC demand (the ratio of CFC use per dollar of real GNP) rather




than a trajectory of immediate convergence.  CFCs first came into use in the




1930's, and the widespread introduction of products over the next 30 years




produced an extremely rapid rate of growth.  As the potential market became




saturated, however, the growth rate slowed.  This abbreviated history is




depicted by the left half of locus AB in Figure 1-2 with the early 1980's




appearing near an inflexion point in the logistics curve.  Eventually, if




all markets are saturated and if no new uses are discovered, the actual CFC




frontier will approach some potential CFC frontier like locus CF.




     The frontier locus CF depicts the usage pattern when CFC products




ultimately and completely penetrate every available submarket; that  is, once




the introduction of the new technologies has been played out.  The potential




frontier is thus determined by the level of per capita income in the United




States, the prices of CFC-using products, and climatic, cultural, and other




miscellaneous factors.  As drawn in Figure 1-2, the frontier has a positive




slope, but that need not be the case.  The slope would be positive if (1)

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 CFC use/GNP
                  potential
              1950
1980
time
Figure 1-2    Illustration of the Dynamic Logistics Curve for the
              U.S. Consumption of CFCs Approaching a Positively
              Sloped CFC Frontier

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new products and processes developed over the coming decades were CFC-




intensive, (2) CFC-using products displayed income elasticities greater than




unity, or (3) the prices of CFC-using products and services were declining




relative to other commodities.  The CFC-intensity of the economy would tend




to decline, giving the frontier a negative slope, if the reverse of these




conditions were true.




     It must be emphasized that we have no a priori conviction whether the




CFC frontier has a positive or negative slope.  We simply do not know, at




this point, how CFC-intensities, income elasticities, and relative prices




will fit together to determine the trend in the potential for future demand.




It should be clear, nonetheless, that the inclusion of such a frontier in




the modeling focuses attention on a convenient method of capturing all of




that uncertainty with a device that is commonly employed in the economics




literature (e.g., potential GNP).  The frontier is, moreover, a convenient




vehicle with which to incorporate even complicated regulatory options in a




straightforward and uncomplicated way.  Finally, the dynamic nature of the




frontier, with its potential  for a nonzero slope, represents an important




extension of the usual logistics approach that envisions trajectories




climbing asymptotically to a  fixed limit.




     A system of equations depicting these loci must be estimated on  the




basis of U.S. time series data that shows dramatic reductions in the  rate of




growth of CFC consumption since the middle of the 1970's --a slowdown that




poses significant difficulty  in interpretation.  Recall that it was in the




middle of that decade that increased awareness of the potential for CFC's




contribution to ozone depletion produced an aerosol ban in the United




States.  General concern that regulatory efforts would extend to other

-------
fluorocarbons was also voiced at that time and probably led to a reduction




in the vitality of CFC market activity at all levels.




     The uncertainty about the effect of regulation leads to another




important issue in forecasting trajectories.  Figure 1-2 illustrates a




single potential CFC frontier.  In fact, we do not know either the level or




the growth rate (positive or negative) of the CFC frontier.  This




uncertainty reflects the general problem of "specification uncertainty" in




estimating statistical models.




     Figure 1-3 illustrates this difficulty more clearly; there, a second




set of actual and potential trajectories (labeled A'B' and C'D',




respectively) is drawn.  Based on the data at hand, it is impossible to sure




whether the frontier is CF or C'F'; i.e., the specification of the




underlying relationship is, itself, uncertain.  This type of specification




uncertainty creates fundamental estimation problems in models like the




present one.  The procedure for incorporating specification uncertainty into




this study employs historical CFC end-use data for the United States to




estimate the likelihood of different rates of growth supporting different




potential CFC frontiers.  Logistics paths converging to these frontiers are




then estimated, again on the basis of the observed U.S. experience.  The




procedure is explained in some detail in Appendix A.




     One critical source of uncertainty has thus been identified (the




frontier growth parameter), along with a statistical procedure for




estimating its probability distribution.  This procedure provides not only a




distribution of growth rates for the frontier, but also an associated




distribution of initial starting points (like C and C' in Figure 1-3).




Locus C'F' begins, in other words, in 1950 (e.g.) at some level of intensity






                                      10

-------
    CFC use/GNP
                 1950
1980
time
Figure 1-3    Illustration of the Possibility of Alternative Paths for
              Actual and Potential CFC use

-------
that is consistent with the estimated rate of growth along C'F',  and that




initial boundary point need not be the same as the point C that anchors  the




first alternative locus CF.




     Consumption per constant dollar of GNP for the U.S. can now easily  be




translated into total consumption for the U.S. for any given year simply by




multiplying the number read from the AB loci by real per capita GNP and




population for the year in question.  Both the rate of growth of per capita




GNP through the middle of the next century, denoted in most economic work as




labor productivity, and the rate of growth of population over the same




period of time are, however, uncertain.  Both multiplicative factors are




thus uncertain or random variables.  Population and productivity projections




through 2050 are based only partially upon statistical exercises for which




standard errors can be computed.  They are, in addition, based upon




judgmental views of the structure of long term economic and demographic




trends that vary from expert to expert.  A procedure has been developed to




extract a representation of the underlying (or "true") distribution of that




uncertainty for such a random variable from disagreement across published




projections.  The details  of the procedure, developed initially for the




Nordhaus and Yohe contribution to the National Academy of Science's Changing




Climate was refined on the basis of some subsequent work by Nordhaus on




macroeconomic forecasts, and its application  to productivity and population




growth rates in the United States is outlined in Appendix B.




     With consumption for  the U.S. sufficiently specified, turn next to the




rest of the world.  The United States has, historically, led the rest of  the




world  to new uses of CFC's.  The experience of the rest of the world can




therefore be described reasonably well by a function that reflects  the speed






                                      11

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with which the rest of the world adopts U.S.  patterns of production and




consumption.  A time series for the rest of the world can,  in fact,  be




constructed from an estimated equation that relates differences in the




relative size of CFC consumption per constant dollar of GNP between the rest




of the world and the U.S. to corresponding differences In the relative size




of per capita GNP.  Figure 1-4 shows how such a time series might evolve.




Curves AB and CF are defined as in Figure 1-2; that is, they represent




actual and potential CFC usage in the United States.  We know that lower-




income countries in Europe, Africa and Asia currently have significantly




lower CFC use per unit of GNP.  This is reflected in the rest of the world




curve shown in Figure 1-4 as DE; it lies everywhere below the U.S. curve AB.




The rest of the world curve gradually moves toward the frontier, but it lags




behind the U.S. curve because incomes outside the U.S. are lower and because




there is a diffusion lag of technology developed and introduced in the




United States.




     The rate of convergence is determined jointly by an estimated intensity




factor and by projected rates of growth of per capita GNP in the rest of the




world.  It is therefore uncertain along two dimensions.  Two more sources of




uncertainty must, in other words, now be noted.  First, the intensity




parameter must be estimated from cross sectional data, and the confidence of




its estimation captured by a likelihood distribution; this estimation is




also discussed in Appendix A.  Secondly, the rate of growth of productivity




in  the rest of the world, another exogenous variable whose distribution  is




gleaned from disagreement across published projections in Appendix B, enters




at  this point.  CFC consumption per dollar of GNP has thus been specified,




but a fourth and  fifth source of uncertainty have also been revealed.






                                      12

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  CFC use/GNP
             potential, U.S
                                 actual, rest of world
               1950
1980
time
Figure 1-4    Illustration of the Rest of the World Given a U.S.
              Frontier

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     A sixth factor appears quickly when CFG consumption per constant  dollar




of GNP is translated into total CFC consumption for the rest of the  world.




As before, the consumption per dollar series needs to be multiplied  by both




per capita GNP and population.  Per capita GNP is already available  .from




productivity growth projections employed in the transition from U.S.




consumption to the rest of the world, but the level of population has  yet to




be specified for the rest of the world.  This sixth uncertainty is




quantified by the procedure of comparing forecast disagreement cited above.




Appendix  B records the specifics of this process.




     A more detailed summary of the entire process can now be presented




schematically; a representation of the computations required each year for




each sampled combination of uncertain parameter and variable values is




depicted  in Figure 1-5.  The  interaction of population, per capita GNP, and




CFC consumption per constant  dollar of GNP produces an estimate for total




U.S. consumption of CFC's  in  period t, as shown at point A  in the upper left




hand corner.  Two uncertain exogenous variables and one uncertain parameter




imply that  three sources of uncertainty need  to be quantified just  to cover




the U.S.  The middle part  of  the upper half of the figure shows the




interaction of U.S. consumption per constant  dollar of U.S. GNP, real per




capita GNP  in the U.S.,  and real per capita GNP  in the  rest of  the  world to




produce  an  estimate of CFC consumption per  constant dollar  of GNP for  the




rest  of  the world  at point B,  A third uncertain exogenous  variable and a




second uncertain parameter come into play  there.   The  upper right hand part




of the figure reflects at  point C  the  determination  of total CFC consumption




for the  rest  of the world  on  the basis  of  CFC consumption per  constant




dollar of GNP in  the rest  of  the world,  real  per capital  in the rest  of the







                                      13

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                                       Frontier
M
H)
CD
             S. Population (t)j

                      __	—	-^

                       U.  S.  Productivity (t)j
                      ^^.       	    	 ^ 	   { |{ ^^


                       U.  S.  CFC use  per $ (t)
                           S.  Consumption  (t)
                                                                      ROW CFC use per  $
                                               XTotal  World
                                               (Consumption (t)

                                                               "
                                                  ^^ ^^            ^X^

                                                /OFC  Emissions  (t))
ROW Consumption  (t)
           Figure 1-5    Detailed Schematic of the Workings  of  One  Iteration of the Analytical Framework

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world, and the population level in the rest of the world.  The uncertain




exogenous variable required there is the sixth explicit source of




uncertainty that must be quantified to construct a probabilistic scenario




exercise.




     The final stage of the model construction, the part that takes CFC




consumption to CFC emissions, is displayed at point E found toward the




bottom of Figure 1-5.  Part of the world's total consumption -- the sum of




the U.S. consumption and the rest of the world accomplished at point D --




leaks into the atmosphere during the period of consumption.  This fraction




depends upon the mix of products using the CFC's that are produced in any




one year and the difference between the quantity produced and the quantity




consumed.  It is claimed that CFC inventories are currently very low




worldwide because they are difficult and expensive to store.  It is also




claimed that the decade-long glut of capacity has dampened trade.  The




leakage parameter may not, therefore,  be significantly affected by the




production/consumption distortion.   It may, however,  vary significantly with




product mix in a manner that would make the leakage factor from current




consumption the third uncertain parameter of an emissions model and the




seventh source of uncertainty requiring some quantification.




     A second source of emission is leakage from the CFC bank that exists




like a vast reservoir of unreleased fluorocarbons.   Each year, the




proportion of CFC's consumed which does not leak into the environment is




deposited through point F in Figure 1-5 into a bank from which it will




eventually leak.  The schema for period t must, therefore, display some of




current consumption being deposited through point F into the reservoir bank




at the same time it displays some proportion of the bank inherited from






                                      14

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period (t-1) leaking through point E into the environment: as emissions.   The




first flow proceeds at a rate equal to one minus the current leakage




parameter just defined; its uncertainty has already been noted.   The second




flow combines with direct emissions to produce, for any given year, total




emissions and, given well accepted CFC molecular atmospheric lifetimes,




corresponding atmospheric concentrations.




     The grand total for identified sources of quantifiable uncertainty is




8.  In the Monte Carlo estimates, we discretized the probability




distributions into high, middle, and low cells with 25 percent,  50 percent,




and 25 percent likelihoods to facilitate the sampling process.  As a result,




there are 6561 possible combinations of values for the 4 exogenous variables




and 4 estimated parameters or 6561 potential trajectories for CFC emissions




for each of the four types of CFC's to be studied.  Even before emissions




are computed, there are 729 possible combinations of 4 random exogenous




variables and 2 estimated parameters upon which total consumption




distributions will depend.  Appendix C records the detailed equations of the




complete model just described.




     Finally, we need  to discuss the regulatory environment presumed




throughout  the analysis.  Because we begin every run at  the actual  1980




consumption levels in  the United States  and  the rest of  the world,  the




impact of the U.S. aerosol ban  is automatically captured  in all of the




results.  The ban was,  of course, applied only to  "nonessential" uses, so




1980 consumption levels were  not zero, even  in the United States.   Aerosol




consumption was, instead, some  small  fraction  of  the peak levels of the  mid




1970's,  and the  frontier  growth methodology  is applied to that quantity  in




all  cases.






                                      15

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     Section III reports results for the rest of the world based on




scenarios that envision regulation going no further than the U.S.  aerosol




ban.  These runs assume, in other words, that the voluntary restraint




presently imposed by the EEC and other countries on themselves will lapse




when economic growth makes those restrictions binding.  Section IV goes to




the other extreme and reports results based on scenarios that envision




existing worldwide restraint on aerosol consumption and/or capacity




continuing as presently written for the next seventy years.  The reader is




thus provided some well defined regulatory benchmarks against which to




measure expectations of the future demand for aerosol regulation.  It should




be noted, too, that nonaerosols are never assumed to be subjected to any




direct regulatory restraint.  Association with aerosols may have depressed




their consumption levels over the past ten years, but that possibility would




be captured, if it were true, in the lower statistical estimates of the




frontier growth rates.




II. The Subjective Distributions.






     Probabilistic scenario analysis applied to  the eight  sources of




uncertainty just noted  requires that we sample randomly over  the judgmental




distributions of each source.   It  is most convenient, for  the purposes of




this sampling,  to discretize each  distribution into high,  middle, and  low




cells with  25 percent,  50  percent  and  25 percent likelihood weights




attached, respectively.  Table  II-l records  the  values  assigned to  these




cells for the four exogenous random variables  identified  in the previous




section: population  growth in  the  United States  and the Rest  of the  World




and productivity growth in the  United  States and the  Rest of  the World.  The




 technique with  which the  subjective distributions for these variables  were




                                      16

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        TABLE II-l

Judgmental Cell Values for
Exogenous Random Variables
LIKELIHOOD
VARIABLES WEIGHT 1980-2000
A.

B.

C.

D.

2000-2020
THEREAFTER
U.S. Population Growth (% per year)
High
Middle
Low
Rest of the World
High
Middle
Low
U.S. Productivity
High
Middle
Low
Rest of the World
High
Middle
Low
25
50
25
0.8
0.7
0.6
Population Growth (X
25
50
25
Growth (% per
25
50
25
Productivity
25
50
25
2.0
1.7
1.3
year)
3.2
2.1
1.0
Growth
2.9
2.0
1.1
0.8
0.4
0.3
per year)
1.5
1.1
0.7

3.2
1.6
0.0
(% per year)
2.8
1.8
0.9
0.15
0.1
0.0

0.9
0.5
0.2

1.7
1.1
0.0

1.7
1.1
0.0

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produced is described in some detail in Appendix B.  The underlying data are




recorded there, as well.




     Table II-2 records the cell values assigned to the two uncertain




parameters that specify CFC demand: the rate of growth of the CFG frontiers




for the United States and the relative intensity elasticities for the rest




of the world.  They are based upon the estimates that emerge from the




statistical procedures outlined in Appendix A.  Table II-3 finally records




the values assumed by the parameters that take consumption of the four CFC




compounds in any one year into current and future emissions: the




distribution of current consumption between release into the atmosphere as




current emission and deposit into the bank for future emission; the annual




rate of release from the bank, and the annual rate of molecular decay in the




atmosphere.
                                      17

-------
                                  TABLE I1-2

                          Judgmental Cell Values for
                          Exogenous  Random  Parameters

                  LIKELIHOOD
    VARIABLES       WEIGHT       1980-2000     2000-2020     THEREAFTER

A.  Frontier Growth Rate for CFC-11 Nonaerosols

       High          .25            2.283         1.706          1.749
       Middle        .50           -0.304        -0.246         -0.250
       Low           .25           -2.885        -2.214         -2.250

B.  Frontier Growth Rate for CFC-12 Nonaerosole

       High          .25            2.518         2.0            2.0
       Middle        .50           -0.729         0.0            0.0
       Low           .25           -2.647        -2.0           -2.0

C.  Frontier Growth rate for CFC-11 Aerosols

       High          .25            2.451         2.0            2.0
       Middle        .50           -0.043         0.0            0.0
       Low           .25           -2.590        -2.0           -2.0

D.  Frontier Growth Rate for CFC-12 Aerosols

       High          .25            2.451         2.0            2.0
       Middle        .50           -0.095         0.0            0.0
       Low           .25           -2.596        -2.0           -2.0

E.  Relative Intensity Elasticity:  Rest of the World for CFC-11 Nonaerosols

       High          .25            1.62          1.62           1.62
       Middle        .50            1.27          1.27           1.27
       Low           .25            0.92          0.92           0.92

F.  Relative Intensity Elasticity:  Rest of the World for CFC-12 Nonaerosols

       High          .25            1.43          1.43           1.43
       Middle        .50            1.15          1.15           1.15
       Low           .25            0.87          0.87           0.87

G.  Relative Intensity Elasticity:  Rest of the World for CFC-11 Aerosols

       High          .25            1.82          1.82           1.82
       Middle        .50            1.30          1.30           1.30
       Low           .25            0.78          0.78           0.78

H.  Relative Intensity Elasticity:  Rest of the World for CFC-12 Aerosols

       High          .25            1.31          1.31           1.31
       Middle        .50            0.93          0.93           0.93
       Low           .25            0.55          0.55           0.55

-------
                                  TABLE II-3

                            Judgmental Cell Values
                           for Emissions Parameters
                                               LIKELIHOOD
    VARIABLE                                     WEIGHT         VALUE

A.  Fraction of Consumption emitted Directly:

       CFC-11 Nonaerosols                         1.0            0.1
       CFC-12 Nonaerosols                         1.0            0.1
       CFC-11 Aerosols                            1.0            1.0
       CFC-12 Aerosols                            1.0            1.0
G.  Fraction of Bank Emitted:

       CFG High                                    .25            .85
       CFC Middle                                  .50            .80
       CFC Low                                     .25            .75
C.  Annual Rate of Atmospheric Decay

       CFC-11 Nonaerosols                         1.0            0.01
       CFC-11 Nonaerosols                         1.0            0.0143
       CFC-12 Aerosols                            1.0            0.01
       CFC-12 Aerosols                            1.0            0.043

-------
III.  Results







     In reporting the results of this analysis,  we show not only the global




consumption (production), emissions,  mass in the banks, and concentrations




for the identified CFC compound, but also a number of important ingredients:




the division of total world production of CFCs between the U.  S. and the




rest of the world, GNP levels for the U. S. and the Rest of the World,




population for the U.S. and the rest of the world, and other key driving




variables.  Recall, particularly in reading the aerosol results recorded in




this section, that they include only the effects of the U.S. aerosol ban.




Voluntary restrictions presently in place in various countries around the




world are reflected explicitly in the results reported in Section IV.




Nonaerosols are assumed to face no formal restraint.  Finally, the




concentration and bank volume trajectories are nominally based on estimates




of the 1980 levels, but the long term results are almost completely




insensitive to their initial specification; virtually all of the CFC's  in




the banks and in  the atmosphere in the  year 2020  and beyond will have been




produced  since 1980.




     Table  III-l  shows the base or "most  likely"  cases obtained by  setting




each of the uncertain  random variables  equal  to  its middle  or  most  likely




value.  The  remaining  tables present  the  probabilistic results based on 200




randomly  selected runs.  The runs were  chosen by drawing  one  of the three




values for  each of the uncertain variables and  parameters from a random




number generator;  the  probability of selecting  each was proportional to the




corresponding judgmental probability under the  assumption that all  of  the




variables were  independently distributed.  For  example, because there  were 7




uncertain variables (the distribution of CFC  consumption  between immediate

-------
                                                             Table II1-1

                                                        Base Case Seceoarioa
Major Driving Variables:

  U.S. POPULATION U0*«9)
  ROW POl>ULATION (10"9)
  US LABOR PRODUCTIVITY (1985$ 10««3/CAP«YR)
  RW LABOR PRODUCTIVITY (1985$ 10««3/CAP«YR)
  U.S CROSS OUTPUT (1985* 10"12/YR)
  ROW CROSS OUTPUT (1984$ 10"12/YR)
  WORLD CROSS OUTPUT (1985$ 10"12/YR)

CFC-11 Konaerosols:

  RATIO OF CFC/CKP (US) (10"3 MT/YR)
  US CFC CONSUMPTION (10"3 MT/YR)
  ROW CFC CONSUMPTION (10**3 MT/YR.)
  WORLD CFC CONSUMPTION (10*»3 MT/YR)
  WORLD CFC BANK (10««3 MT)
  WORLD CFC BUSSIONS (10"3 MT/TR)
  WORLD CFC CONCENTRATIONS U0"3 MT)
                                                   1980
                                                             1990
                                                                        2000
                                                                                   2010
                                                                                              2020
                                                                                                         2030
                                                                                                                    2040
  193.316   264.650
                       357.122    464.330    589.657
                                                                                                                               2050
0.225
4.226
15.150
2.520
3.409
10.550
14.058
19.836
67.616
125.700
0.241
5.009
18.690
3.078
4.510
15.418
19.928
19.504
87.969
176.680
0.258
5.884
22.885
3.748
5.896
22.054
27.951
19.032
112.222
244.901
0.269
6.608
26.991
4.496
7.260
29.711
36.970
18.593
134.983
329.347
0.279
7.310
31.437
5.327
8.761
38.939
47.701
18.153
159.041
430.616
0.282
7.731
35.268
5.988
9.958
46.294
55.251
17.710
175.346
500.719
0.285
8.127
39.369
6.684
11.227
54.326
65.553
17.274
193.937
573.142
0.288
8.544
43.947
7.461
12.658
63.752
76.410
16.848
213.270
656.005
                                                         677.065   767.078    869.275
  689.193 1.051.439  1.438.844  1,893.235 2,435.381    2.888.110  3,287.048  3,726.254
  148.134   229.779    315.072    415.269    535.140
                                                        637.397    725.880
                                                                              822.907
1,935.351 3,618.248   5911.371  8.882.086 12,631.320  17,115.297  22,042.629 27,384.535
CFC-12 Nooaerosols:

  RATIO OF CFC/GKP (US) (10««3 MT/YR)
  US CFC CONSUMPTION (10««3 MT/YR)
  ROW CFC CONSUMPTION (10**3 MT/YR)
  WORLD CFC CONSUMPTION (10**3 MT/YR)
  WORLD CFC BANK U0**3 MT)
  WORLD CFC EMISSION (10"3 MI/YR)
  WORLD CFC CONCENTRAIONS (10««3 MT)
37.647
128.324
120.800
249.124
883.011
189.612
35.427
159.781
162.697
322.478
1,303.290
285.514
33.448
197.224
218.350
415.574
1.697.653
372.468
33.261
241.461
298.276
539.738
2,201.117
482.814
33.281
291.582
398.888
690.470
2,843.410
624.546
33.288
331.471
475.424
806.894
3,419.687
754.063
33.291
373.471
557.960
931.722
3,964.472
874.646
33.292
421.425
654.794
1.076.220
4.580.465
1,010.593
2.749.781 4,699.805  7,195.145 10,281.656 14,160.613 18,827.820  24,003.590  29,690.176
CFC-11 Aerosols:

  RATIO OF CFC/GNP (US) (10*«3 MT/YR)
  ui CfC CONSUMPTION (10**3 MT/YR)
  ROW CFC CONSUMPTION (10««3 MT/YR)
  WORLD CFC CONSUMPTION (10**3 MI/YR)
  WORLD CFC BANK U0**3 MT)
  WORLD CFC EMISSIONS (10*«3 MT/YR)
  WORLD CFC CONCENTRATIONS (10«*3 MT)
CFC-12 Aerosols:

  RATIO OF CFC/GNP (US) U0«*3 MT/YK)
  US CFC CONSUMPTION (10*«3 MT/YR)
  ROW CFC CONSUMPTION (10**3 MT/YR)
  WORLD CFC CONSUMPTION (10*«3 MI/YR)
  WORLD CFC BANK U0**3 MT)
  WORLD CFC EMISSIONS <10*«3 MT/YR)
  WORLD CFC CONCENTRATIONS (10*«3 MT)
24.062
4.101
111.900
116.001
0.000
116.001
2,506.029
31.695
5.402
178.800
184.202
0.000
184.202
24.282
5.476
161.371
166.847
0.000
166.847
3,633.926
31.797
7.171
257.287
264.457
0.000
264.457
24.314
7.168
229.493
236.661
0.000
236.661
5,239.586
31.690
9.343
364.936
374.278
0.000
374.278
24.348
8.838
316.515
J25.353
0.000
325.353
7,456.504
31.716
11.512
499.856
511.368
0.000
511.368
24.365
10.673
424.388
435.061
0.000
435.061
10,442.164
31.736
13.902
665.987
679.889
0.000
679.889
24.371
12.134
505.979
581.113
0.000
518.113
14,059.691
31.743
15.804
793.429
809.234
0.000
809.234
24.373
13.682
593.827
607.409
0.000
607.509
18,135.649
31.746
17.821
931.178
948.999
0.000
9A8.999
24.374
15.427
696.887
712.313
0.000
712.313
22,756.617
31.747
20.093
1,092.786
1,112.879
0.000
1,112.879
                                               3,300.393 5,057.617  7,416.750  10,628.937  14,891.117  19,970.742 25,602.395 31.913.781

-------
release into the atmosphere and deposit into the bank was not included as a




random variable in the probabilistic runs), the most likely run had .0078 -




.5  chance of being chosen.




     Table III-2 presents the mean values of the different variables for the




period 1980 through 2050.  As can be seen, these differ from the most likely




values shown in Table III-l.  More precisely, the mean Levels of CFC




consumption, emission, bank volume, and atmospheric concentration are all




higher when uncertainty is allowed than when uncertainty is ignored.  The




reason for this difference can be traced to the nonlinear nature of the




demand model.   Location of the mean above the most likely scenario can occur




only if the extreme trajectories on the high side deviate further from the




best guess than do the extreme runs on the low side.  Further evidence of




this skewness will be drawn from tabulations of 25th and 75th percentile




boundaries provided below.




     Table III-3 records the rates of growth of the different variables over




the next seven decades.  These show that CFC production grows faster than




GNP for both aerosols and non aerosols over the near term.  By the middle of




the next century, though, consumption increases slow, but to rates that




still exceed the rate of growth of GNP.  Remember that these growth rates




emerge from simulations that ignore the possibility of increased regulatory




activity.




      Table III-4 shows the quartile projections of the estimates of CFC




production along with the other critical variables.  The 25th and 75th




percentile paths show, respectively, the trajectory below which the outcome




is  thought to lie with probability one-quarter -nd above which the outcome




is  thought to lie with probability one-quarter.  Put differently, the

-------
                                                             Table III-2

                                           Mean Eatlaaces  Based OD  Probabilistic Scenario
                                                    1980
                                                             1990
                                                                        2000
                                                                                    2010
                                                                                              2U20
                                                                                                         2030
                                                                                                                    2040
                                                                                                                               2050
Major Driving Variables:

  US POPUI-ATION U0««9)
  ROW POPULATION (10«*9)
  US LABOR PRODUCTIVITY (198Si 10*«3/CAP«YK)
  RW LABOR PRODUCTIVITY (1985* 10«*3/CAP«YR)
  US CROSS OUTPUT (1985* 10*«12/Wl)
  ROW CROSS OUTPUT U984J 10*«12/YR)
  WORLD GROSS OUTPUT (1985i 10««12/YR)

CFC-11 Nouaerosola:

  RATIO OF CFC/CNP (US) (10"3 KT/YR)
  US CFC CONSUMPTION (10«*3 KT/YR)
  ROW CFC CONSUMPTION (10**3 KT/YR)
  WORLD CFC CONSUMPTION (10"3 KI/YR)
  WORLD CFC BANK (10"3 KT)
  WORLD CFC EMISSIONS U0««3 KT/YR)
  WORLD CFC CONCENTRATIONS (10"3 KT)
CFC-12 Nooaero»ol«:

  RATIO OF CFC/CNP (US) U0**3 XT/ML)
  US CFC CONSUMPTION (10"3 KT/YR)
  ROW CFC CONSUMPTION (10*«3 KT/YR)
  WORLD CFC CONSUMPTION (10"3 KT/YR)
  WORLD CFC BANK (10"3 KI)
  WORLD CFC EMISSION (10««3 KT/YR)
  WORLD CFC CONCENTRAIONS U0"*3 HT)
0.225
4.226
15.150
2.520
3.409
10.649
14.058
19.836
67.614
125.699
193.313
687.732
149.581
1,936.767
37.645
128.321
120.797
249.121
881.141
191.463
0.241
5.015
18.915
3.087
4.568
15.481
20.049
20.090
91.881
182.803
274.686
1,084.663
233.000
3,624.866
37.772
172.787
174.039
346.826
1,377.701
296.206
0.
5.
23.
3.
6.
22.
28.
20.
127.
277.
405.
1,603.
343.
6,059.
39.
239.
263.
503.
2.000.
428.
25«
904
596
786
092
358
449
793
288
910
195
191
462
812
127
732
400
124
347
816
0.270
6.665
28.779
4.603
7.783
30.694
38.477
21.748
171.174
431.751
602.921
2,378.147
509.032
9.594.180
42.056
331.542
414.791
746.321
2,947.394
630.988
0.
7.
34.
5.
9.
41.
50.
23.
270
421
879
539
807
137
944
069
230.565
682.
912.
3,601.
771.
14,855
46.
461.
664.
1,125.
4,445.
951.
259
824
833
112
.895
033
098
279
379
590
686
0
7
39
5
11
49
61
24
290
962
1,252
5,090
1,093
22,507
51
598
952
1,551
6,295
1,351
.281
.913
.874
.267
.360
.648
.007
.872
.039
.655
.689
.520
.563
.977
.176
.228
.858
.099
.930
.506









1,
1,
7.
1,
32


1,
2,
8,
1,
0.287
8.395
45.298
7.050
13.031
59.264
72.295
27.201
366.555
369.580
736.134
023.227
508.082
,905.691
57.700
779.570
377.317
156.903
722.164
870.871
0.290
8.901
51.570
7.954
14.981
70.986
85.968
30.123
470.212
2,000.110
2,470.333
9,902.477
2,125.121
47,272.129
65.869
1,030.872
2,040.773
3,071.668
12,323.117
2,640.922
                                               2,751.606 4,734.773  7,535.559 11,544.707  17,502.113 26,154.359  37,915.098  54,195.031
CFC-11 Aeroioli:

  RATIO OF CFC/CNP (US) (10"3 KT/YR)
  US CFC CONSUMPTION (10*«3 KI/YR)
  ROW CFC CONSUMPTION (10"3 MT/YX)
  WORLD CFC CONSUMPTION (10"3 MT/TR)
  WORLD CFC BANK (10«*3 KT)
  WORLD CFC EMISSIONS (10**3 KT/YR)
  WORLD CFC CONCENTRATIONS (10*«3 KT)
CFC-12 Aerocola:

  RATIO OF CFC/GNP (US) (10*«3 KT/YR)
  US CFC CONSUMPTION (10««3 KT/YR)
  ROW CFC CONSUMPTION (10"3 KT/YR)
  WORLD CFC CONSUMPTION (10««3 KT/YR)
  WORLD CFC BANK (10««3 KT)
  WORLD CFC EMISSIONS U0*«3 KT/YR)
  WORLD CFC CONCENTRATIONS (10««3 HT)
24.061
4.101
111.899
116.000
0.000
116.000
2,506.003
31.693
5.402
178.797
184.200
0.000
184.200
24.982
5.713
166.782
172.495
0.000
172.495
3,654.350
32.632
7.290
270.379
277.669
O.OOO
277.669
26.489
8.108
260.069
268.177
0.000
268.177
5,426.937
34.352
10.019
426.177
436.193
O.OOO
436.193
28
11
416
427
0
427
8,254
36
13
682
696
0
696
.426
.186
.439
.624
.000
.624
.383
.724
.368
.794
.163
.000
.163
30.
15.
680.
695.
0.
695.
12.912
39.
17.
1 , 104 .
1,122.
0.
1,122.
957
470
136
605
000
605
.727
871
982
890
887
OOO
870
34
19
989
1.009
0
1,009
19,949
44
22
1,595
1,618
o
1.618
.230
.958
.654
.613
.000
.613
.750
.002
.829
.984
.817
.OOO
.817
38.
25.
1,452.
1,478.
0.
1,478.
30,030
49.
29.
2,319.
2,348.
0.
2.348.
385
864
441
304
000
304
.828
268
224
579
805
000
805
43.589
34.021
2,189.739
2.223.763
0.000
2,223.763
44,998.930
55.878
38.076
3,452.257
3,490.336
0.000
3,490.336

-------
                                                                  TABLE  III-3

                                                  Kates of Growth-Bate Case and Mean Estimates
                                                  1980-
                                                   1990
1990-
 2000
2000-
 2010
2010-
 2020
2020-
 2030
2030-
 2040
2040-
 2050
Base Case

    US POPULATION
    ROW POPULATION
    US LABOR PRODUCTIVITY
    RW LABOR PRODUCTIVITY
    US GROSS OUTPUT
    ROW GROSS OUTPUT
    WORLD GROSS OUTPUT

CFC-11 Nooaerosola:

    RATIO OF CFC/CNP (US)
    US CFC CONSUMPTION
    ROV CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-12 Nooaerosols:

    RATIO OF CFC/CNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-11 Aerosols:

    RATIO Cf CFC/CNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-12 Aerosols:

    RATIO OF CFC/CNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS
0.700
1.700
2.100
2.000
2.800
3.700
3.469
0.655
1.610
2.025
1.970
2.680
3.560
3.363
0.430
1.160
1.650
1.820
2.080
2.960
2.797
0.355
1.010
1.525
1.695
1.880
2.705
2.548
0.130
0.560
1.150
1.170
1.280
1.730
1.649
0.100
0.500
1.100
1.100
1.200
1.600
1.530
0.100
0.500
1.100
1.100
1.200
1.600
1.533
-0.169
2.631
3.404
3.141
4.224
4.390
6.257
-0.245
2.435
3.265
2.997
3.137
3.137
4.909
-0.233
1.647
2.963
2.625
2.744
2.761
4.072
-0.240
1.640
2.681
2.389
2.518
2.536
3.521
-0.247
1.033
1.508
1.382
1.705
1.749
3.038
-O.249
0.951
1.351
1.248
1.294
1.300
2.530
-0.250
0.950
1.350
1.251
1.254
1.255
2.170
-0.608
2.192
2.978
2.581
3.893
4.093
5.360
-0.575
2.105
2.942
2.536
2.644
2.659
4.259
-0.056
2.024
3.199
2.614
2.597
2.595
3.570
0.006
1.886
2.907
2.463
2.560
2.574
3.201
0.002
1.282
1.755
1.558
1.845
1.885
2.849
0.001
1.201
1.601
1.438
1.478
1.484
2.429
0.091
2.891
3.661
3.635
0.000
3.635
3.716
0.013
2.693
3.522
3.496
0.000
3.496
3.659
0.014
2.094
3.215
3.183
0.000
3.163
3.528
0.007
1.887
2.933
2.906
0.000
2.906
3.368
0.002
1.282
1.758
1.747
0.000
1.747
2.975
0.001
1.201
1.601
1.592
0.000
1.592
2.546
                                                                      0.000
                                                                      1.200
                                                                      1.600
                                                                      1.442
                                                                      1.444
                                                                      1.445
                                                                      2.126
                                                                      0.000
                                                                      1.200
                                                                      1.600
                                                                      1.592
                                                                      0.000
                                                                      1.592
                                                                      2.270
0.032
2.832
3.639
3.616
0.000
3.616
4.029
-0.034
2.646
3.495
3.473
0.000
3.473
3.828
0.008
2.088
3.147
3.121
0.000
3.121
3.598
0.006
1.886
2.869
2.848
0.000
2.848
3.372
0.002
1.282
1.751
1.742
0.000
1.742
2.935
0.001
1.201
1.601
1.593
0.000
1.593
2.484
0.000
1.200
1.600
1.593
0.000
1.593
2.204

-------
                                                                  TABLE III-3
                                                                  (Continued)

                                                  Rites of Growth-Base Case and Mean EatlMtea
                                                  1980-
                                                   1990
1990-
 2000
20OO-
 2010
2010-
 2020
2020-
 2030
2030-
 2040
2040-
 2050
Means

    US POPULATION
    ROW POPULATION
    US LABOR PRODUCTIVITY
    RU LABOR PRODUCTIVITY
    US CROSS OUTPUT
    ROW GROSS OUTPUT
    WORLD CROSS OUTPUT

CFC-11 Nonaeroaola:

    RATIO OF CFC/CNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-17 Nonaerosols:

    RATIO OF CFC/GNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-11 Aerosols:

    RATIO OF CFC/GNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD CFC CONCENTRATIONS

CFC-12 Aerosols:

    RATIO OF CFC/GNP (US)
    US CFC CONSUMPTION
    ROW CFC CONSUMPTION
    WORLD CFC CONSUMPTION
    WORLD CFC BANK
    WORLD CFC EMISSIONS
    WORLD OT
0.707
1.712
2.220
2.029
2.927
3.7*1
3.550
0.667
1.632
2.211
2.041
2.879
3.676
3.499
0.463
1.211
1.986
1.954
2.451
3.169
3.019
0.386
1.074
1.922
1.850
2.311
2.929
2.807
0.130
0.643
1.339
1.235
1.470
1.880
1.803
0.096
0.590
1.275
1.178
1.373
1.770
1.698
0.096
0.596
1.297
1.206
1.395
1.805
1.732
0.127
3.067
3.745
3.513
4.556
4.432
6.268
0.344
3.260
4.189
3.887
3.907
3.880
5.139
0.449
2.962
4.405
3.974
3.943
3.934
4.595
0.590
2.979
4.576
4.148
4.151
4.153
4.372
0.753
2.295
3.443
3.165
3.459
3.494
4.155
0.895
2.341
3.526
3.264
3.218
3.214
3.798
0.034
2.975
3.652
3.309
4.470
4.364
5.427
0.352
3.275
4.144
3.720
3.7M
3.700
4.647
0.722
3.242
4.541
3.943
3.876
3.863
4.266
0.904
3.299
4.709
4.107
4.110
4.109
4.161
1.059
2.604
3.608
3.208
3.480
3.507
4.017
0.376
3.315
3.991
3.968
0.000
3.968
3.772
0.586
3.501
4.443
4.413
0.000
4.413
3.955
0.706
3.219
4.708
4.666
0.000
4.666
4.194
0.853
3.242
4.906
4.865
0.000
4.865
4.475
1.005
2.547
3.751
3.725
0.000
3.725
4.350
                                                        1.200
                                                        2.648
                                                        3.684
                                                        3.297
                                                        3.260
                                                        3.252
                                                        3.713
                                                        1.146
                                                        2.592
                                                        3.836
                                                        3.813
                                                        0.000
                                                        3.813
                                                        4.090
0.292
2.997
4.136
4.104
0.000
4.104
4.132
0.514
3.179
4.550
4.517
0.000
4.517
4.233
0.668
2.884
4.713
4.675
0.000
4.675
4.397
0.822
2.965
4.813
4.781
0.000
4.781
4.586
0.9086
2.387
3.677
3.658
0.000
3.658
4.367
1.130
2.470
3.739
3.722
0.000
3.722
4.051
                                                                      1.021
                                                                      2.490
                                                                      3.787
                                                                      3.527
                                                                      3.436
                                                                      3.430
                                                                      3.623
                                                         1.324
                                                         2.794
                                                         3.932
                                                         3.535
                                                         3.456
                                                         3.447
                                                         3.572
                                                         1.271
                                                         2.741
                                                         4.105
                                                         4.083
                                                         0.000
                                                         4.083
                                                         4.044
                                                                      1.259
                                                                      2.646
                                                                      3.976
                                                                      3.961
                                                                      0.000
                                                                      3.961
                                                                      3.973

-------
                                                             TABLE III-*


                                                 25th .nd 75th per«"tll« Scea.rlo.
                                                 Based on Prob.bllltl.tlc Seeiurlos
                                                   1990
                                                             2000
                                                                        2010
                                                                                   2020
                                                                                               2030
                                                                                                          2040
                                                                                                                    2050
Major Driving Variable.:

 251 Point. fro« Hlghe.t

  U.S. POPULATION (10*«9)
  ROW POPULATION (10**9)
  US LABOR PRODUCTIVITY (1985$ 10"3/CAP*YR)
  RW LABOR PRODUCTIVITY (1985$ io«*3/CAP*tt)
  U.S CROSS OUTPUT (198Si 10««12/YR)
  ROW CROSS OUTPUT (1984$ 10**12/YR)
  WORLD CROSS OUTPUT (1985$ 10**12/tR)

 25Z Point, fro* Love.t

  US POPULATION (10««9)
  ROW POPULATION (10**9)
  US LABOR PRODUCTIVITY (1985$ 10*«3/CAP«YR.)
  RW LABOR PRODUCTIVITY (1985$ 10*«3/CAP«Y8.)
  US GROSS OUPUT (1985$ 10««12/YR)
  ROW CROSS OUPUT (1985$ 10*«12/YR).650
  WORLD GROSS OUTPUT (1985$ 10"12/YR)
0.263
5.162
20.863
3.078
4.985
15.887
20.922
0.241
5.009
18.690
3.078
4.465
14.BL3
19.323
0.280
6.257
28.731
3.748
7.256
23.454
30.856
0.258
5.884
22.885
3.748
5.780
20.359
26.255
0.295
7.306
39.567
4.496
10.328
32.852
43.494
0.269
6.608
26.991
4.496
7.045
26.351
33.611
0.301
8.413
53.276
5.327
14.265
44.814
59.661
0.279
7.310
31.437
5.327
8.418
33.232
41.993
0.306
9.260
64.103
5.988
17.216
55.452
73.550
0.282
7.731
35.268
5.988
9.472
38.302
48.259
0.310
10.133
75.981
6.684
20.406
67.729
89.397
0.265
8.127
39.369
6.684
10.573
43.619
54.846

11.067
90.060
7.461
24.187
82.724
108.665
0.288
8.544
43.947
7.461
11.802
49.675
62.333
CFC-11 Noa.ero.ol.:

  25! Point, fro* Hlghe.t

  RATIO OF C/C/GW (US) (10"3 KI/YR)
  US CFC CONSUMPTION (10»*3 MT/YR)
  RC*. CFC CONSUMPTION (10««3 MT/YR)
  WORLD CFC CONSUMPTION (10"3 MT/YR)
  VOiC-L CFC BANK ac««i HI)
  WORLD CFC EMISSION (10«*3 MT/YR)
  WORLD CFC CONCENTRAIONS (10*«3 MT)
   25.263
  103.098
  216.726
  311.733
1,236.624
  254.521
3,768.578
   31.627
  151.766
  369.757
  506.536
1,915.576
  413.702
6,581.363
   37.797
  206.053
  612.346
  784.184
3,081.874
  650.924
   44.887
  285.687
1,007.599
1,176.177
4,694.414
  994.623
                                                                   11,180.367 18,018.219
   53.457
  341.956
1,354.829
1,617.706
6,737.695
1,395.858
27,858.199
    63.680
   401.323
 1,777.063
 2,215.491
 9,239.391
 1,902.741
41,106.008
   75.854
  470.970
2,330.753
3,045.602
12,442.797
2.598.740
58,880.111
 251 Point, from Lowe.t

  RATIO OF CFC/GNP (US) U0**3 MT/YR)
  US CFC CONSUMPTION (10'*3 MT/YR)
  ROW CFC CONSUMPTION (10««3 MT/YR)
  WORLD CFC CONSUMPTION (10*«3 MT/YR)
  WORLD CFC BANK (10««3 MT)
  WORLD CFC EMISSIONS (10*«3 MT/YR)
  WOKLD CFC CONCENTRATIONS (10**3 MT)
                                                         17.274    16.848
                                                         95.406    90.303
                                                        193.402   188.634
                                                        427.685   446.512
                                                      1,941.073 2,082.438
                                                        412.398   441.535
3,473.714 5,450.258  7,568.594 10,062.211 12,712.559 15,189.402 17,991.176
19.504
78.806
1*7.620
230.760
903.568
208.710
19.032
89.387
169.343
274.975
1,140.644
251.501
18.593
94.415
179.709
330.995
1,372.464
303.486
18.153
98.731
198.749
390.663
1,666.671
361.648
17.710
98.218
196.861
406.863
1,849.729
394.130

-------
                                                             TABLE III-*
                                                             (Continued)

                                                 25th tad  75th  Percentlle  Scenario*
                                                 Baaed on  Probabllltlstlc  Scenario*
                                                   1990
                                                               2000
                                                                           2010
                                                                                        2020
                                                                                                   2030
                                                                                                                2040
                                                                                                                            2050
CFC-12 Nonaerosols:

 231 Points from Highest

  RATIO OF CFC/CNP (US) (10**3 MT/YR)
  US CFC CONSUMPTION (10**3 MI/YR)
  ROW CFC CONSUMPTION (10**3 KT/YR)
  WORLD CFC CONSUMPTION (10««3 MT/YR)
  WORLD CFC BANX (10««3 MT)
  WORLD CFC EMISSIONS (10"3 KT/YR)
  WORLD CFC CONCENTRATIONS (10**3 MT)

 251 Points fro* Lowest

  RATIO OF CFC/CNP (US) (10**3 KT/YB.)
  US CFC CONSUMPTION (10**3 MT/YR)
  ROW CFC CONSUMPTION (10"3 KT/YR)
  WORLD CFC CONSUMPTION (10"3 MT/YR.)
  WORLD CFC BANK (10*«3 KT)
  WORLD CFC EMISSIONS (10"3 MT/YR)
  WORLD CFC CONCENTRATIONS (10**3 HI)

CFC-11 Aerosols:

 25Z Points fro« Highest

  RATIO OF CFC/CNP (US) (10«*3 MT/YR)
  US CFC CONSUMPTION (10*«3 MT/YR)
  ROW CFC CONSUMPTION (10«*3 KT/YR)
  WORLD CFC CONSUMPTION (10**3 MT/YR)
  WORLD CFC BANK (10««3 KT)
  WORLD CFC EMISSIONS U0*«3 KT/tt)
  WORLD CFC CONCENTRATIONS (10"3 Ml)

 25Z Points froa Lowest

  RATIO OF CFC/CNP (US) (10««3 MT/YR)
  US CFC CONSUMPTION (10**3 KT/YR)
  ROW CFC CONSUMPTION (10«*3 MT/YR)
  WORLD CFC CONSUMPTION (10««3 MT/YR)
  WORLD CFC BANK (10«*3 KT)
  WORLD CFC EMISSIONS (10**3 KT/YR)
  WORLD CFC CONCENTRATIONS (10**3 MT)
49.017
200.035
197. 649
406. 578
1,608.779
321.359
4.903.859
35.427
144.575
138.628
291.868
1.153.086
265.582
4.566.410
31.297
6.386
198.482
203.958
0.000
203.958
3.807.616
24.282
4.905
134.384
140.497
0.000
140.497
3,503.788
62
301
322
651
2.448
538
8,251
.846
.57
.568
.229
.530
.702
.828
33.448
160
158
345
1.404
318
6.784
.505
.029
.501
.957
.594
.160
40.068
9
346
355
0
355
6.139
24
5
157
166
0
166
4,655
.614
.312
.553
.000
.553
.672
.314
.710
.610
.609
.000
.609
.246
77
398
545
1.000
3.859
841
13.770
33
171
183
409
1.738
376
9.187
49
13
603
612
0
612
.288
.559
.165
.736
.858
.222
.059
.261
.519
.845
.812
.043
.784
.453
.272
.491
.360
.198
.000
.198
10,213.488
24
6
172
183
0
183
5,898
.348
.202
.506
.693
.000
.693
.242
94.457
523.771
892.341
1,629.301
6.011.305
1.321.166
21.886.211
33.281
181.010
208.512
490.486
2.103.559
449.639
11.772.969
60.222
19.172
1.004.243
1,014.916
0.000
1.014.916
17.174.477
24.365
6.626
195.365
201.608
0.000
201.608
7.181.227
115
.397
642.762
1.220
2.387
8.782
1.971
34.148
33
184
211
522
2,325
501
14,651
73
23
1.387
1.400
0
1.400
27,287
24
6
198
214
0
214
8,488
.446
.655
.383
.746
.199
.288
.616
.656
.164
.642
.927
.266
.574
.528
.192
.137
.000
.137
.613
.371
.758
.280
.583
.000
.583
.150
140
793
1,663
3,372
11.837
2,905
52,692
33
187
211
559
2,656
537
17,508
89
28
1.868
1,883
0
1,883
40,535
24
6
198
207
0
207
9,805
.958
.560
.748
.282
.477
.516
.902
.291
.421
.673
.566
.364
.825
.289
.872
.312
.938
.608
.000
.608
.016
.373
.732
.298
.788
.000
.788
.414


2
4
15
4
78




2

20


2
2

2
58






10
172.172
983.937
,285.084
,602.164
,966.754
,033.716
.302.437
33.292
190.260
223.563
600.251
,813.909
576.768
,500.742
109.774
34.067
,517.841
.541.287
0.000
,541.287
,003.902
24.374
6.533
198.305
220.319
0.000
220.319
,991.805

-------
                                                             TABLE III-*
                                                             (Continued)

                                                 23th mad 75th Ferceatlle Scenarios
                                                 Baaed on Probabllltlatlc Scenario*
                                                   1990
                                                               2000
                                                                           2010
                                                                                        2020
                                                                                                    2030
CPC-12 Aeroaola:

 25X Polnta from Hlgheat

  RATIO OF CTC/Off (US) (10"3 MT/TR)
  OS CFC CONSUMPTION (10**3 MT/TR.)
  ROW CTC CONSUMPTION (10"3 MT/TR)
  WORLD ere CONSUMPTION (10"3 MT/TR)
  WORLD CTC BANK (10*«3 MI)
  WORLD Crc EMISSIONS (10**3 MT/TR)
  WORLD Cre CONCENTRATIONS (10**3 HT)

 25Z Polnta from Loweat

  RATIO OP CTC/ONP (OS) (10**3 MT/1H.)
  OS Cre CONSUMPTION U0*«3 MT/TR)
  ROW Crc CONSUMPTION (10**3 MT/TR)
  WORLD Cre CONSUMPTION (10««3 MT/TR)
  WORLD Crc BANK (10**3 MI)
  WORLD Crc EMISSIONS (10**3 MT/TR)
  WORLD CTC CONCENTRATIONS (10«*3 MT)
                                                                                                                2040
                                                                                                                            2050
41.016
8.286
315.540
322.711
0.000
322.711
5.327.379
31.797
6.360
222.848
230.090
0.000
230.090
4,890.773
52.284
12.278
551.745
561.088
0.000
561.088
8.798.227
31.690
7.294
274.189
283.735
0.000
283.735
6,671.895
64.133
16.536
896.992
920.720
0.000
920.720
14,816.363
31.716
7.853
328.231
339.614
0.000
339.614
8,723.535
78.236
22.636
1,505.762
1.509.080
0.000
1.509.080
24.085.199
31.736
8.142
380.385
395.121
0.000
395.121
11.047.801
95.559
27.324
2.061.926
2,064.678
0.000
2.064.678
37,460.031
31.743
8.251
382.926
403.926
0.000
403.926
13,335.801
116.727
32.857
2,770.571
2,836.096
0.000
2,836.096
55.562.504
31.746
8.334
405.643
438.033
0.000
438.033
15,284.191
142.576
40.740
3.853.907
3.944.146
0.000
3,944.146
80,272.687
31.747
8.418
436.901
475.294
0.000
475.294
17.503.582

-------
results suggest that it is equally likely that the value of future CFC




production will lie between the two paths as it is that it will lie outside




their boundary.




      A few words may be necessary to explain exactly what this and the




other dispersion measures are intended to convey.  At the present time, we




have some information, but only very imperfect information, about the




factors that determine future CFC production.  We are unsure about future




population levels, about the course of technological change, about new




products that will embody CFCs or substitutes, and so forth.  Using a




combination of statistical techniques and informed judgment, we have




attempted to measure the extent of the uncertainty about future trends.  To




take a particular case, we have surveyed experts on population and have from




them derived estimates of possible likely paths of population growth over




the coming decades.  From these estimates, we have formed a judgment about




how likely different CFC production outcomes seem to be.  When all of the




uncertain factors are incorporated, Table III-4 indicates, for example, that




it is equally likely that world CFC-12 (nonaerosol) production in 2020 will




lie between 490 thousand and 1600 thousand MT/yr as it  is that it will lie




outside that range.  That represents enormous uncertainty for a 35 year




glimpse into the  future, but it is our view  that such uncertainty accurately




reflects the current state of knowledge and  ignorance about future CFC use




trend.




     It should also be clear that relying upon maximum  likelihood or best




guess  scenarios to evaluate the severity of  potential CFC  damage could be  a




serious mistake.   If conditions in the future  turn out  to  correspond with




the combinations  of population growth, productivity growth, and CFC

-------
intensity that have here produced simulated trajectories above the best




guess, then the skewness or the results means that our present view of the




best guess will seriously underestimate the magnitude- of the future problem.









     Table III-5 records an alternate measure of dispersion, the standard




deviations of the various important variables.  Tracking these statistics




into the future reveals the ever increasing uncertainty that surrounds our




understanding.  Computing the associated t-statistics, a dimensionless




composite measure of dispersion based on these standard deviations, supports




the validity of an interesting conjecture: emissions of nonaerosols,  at any




point in time, should be less uncertain than the consumption that produces




them.  As revealed in Table III-6, this conjecture is true, but only to a




limited degree.  The estimated t-statistics for world consumption are,




indeed, always smaller than those for world emissions; i.e., the standard




deviation measured as a fraction of the corresponding mean is always higher




for consumption than for emissions.  This result obtains, of course,  because




depositing of nonaerosols into the bank delays their release into the




atmosphere, and thus spreads the full effect of their uncertainty into the




future.  Still, the net. effect of the delay is spent in less than ten years.

-------
                                                             TABLE III-5
                                                    Estimated Standard Deviation!
                                                   Rased  on Probabilistic Scenarios
                                                    1990
                                                                2000
                                                                            2010
                                                                                        2020
                                                                                                    2030
                                                                                                                2040
                                                                                                                             2050
Major Driving Variables:

  U.S. POPULATION (10**9)
  ROW POPULATION (10**9)
  US LABOR PRODUCTIVITY (1985$ 10**3/CAP*YR)
  RW LABOR PRODUCTIVITY (1985$ 10**3/CAP«YR)
  U.S GROSS OUTPUT (1985$ 10**12/YR)
  ROW CROSS OUTPUT (1984i 10««12/YR)
  WORLD CROSS OUTPUT (1985t 10"12/YJO

CFC-11 Nonaerosols:

  RATIO OF CFC/CNP (OS) (10"3 KT/tt)
  OS CFC CONSUMPTION (10««3 KT/TR)
  ROW CFC CONSUMPTION U0«*3 MT/YR)
  WORLD CFC CONSUMPTION (10"3 MT/tR)
  WORLD CFC BANK (10««3 HI)
  WORLD CFC EMISSIONS (10*»3 MT/YB.)
  WORLD CFC CONCENTRATIONS (10**3 Ml)
CFC-12 Nouserosols:

  RATIO OF CFC/CNP (US) (10*«3 MT/YR)
  DS CFC CONSUMPTION (10**3 MT/YR)
  ROW CFC CONSUMPTION (10"3 MT/YR)
  WORLD CFC CONSUMPTION (10«*3 KT/YRJ
  WORLD CFC BANK (10*«3 MT)
  WORLD CFC HUSSION (10"3 MT/YR)
  WORLD CFC CONCENTRAIONS (10«*3 XT)
CFC-11 Aerosols:

  RATIO OF CFC/CNP (US) (10**3 MT/tt)
  US CFC CONSUMPTION (10««3 KT/TR)
  ROW CFC CONSUMPTION (10««3 MT/TR)
  WORLD CFC CONSUMPTION (10"3 MT/YB.)
  WORLD CFC BANK U0*«3 MT)
  WORLD CFC EMISSIONS (10"3 MT/TR)
  WORLD CFC CONCENTRATIONS (10««3 MT)

CFC-12 Aerosols:

  RATIO OF CFC/CNP (US) (10**3 MT/YR)
  US CFC CONSUMPTION (10*«3 MI/YR)
  ROW CFC CONSUMPTION (10««3 MT/Ht)
  WORLD CFC CONSUMPTION (10«*3 MT/YR)
  WORLD CFC BANK (10»*3 MT)
  WORLD CFC EMISSIONS (10**3 MT/YR)
0.000
0.119
1.377
0.193
0.336
1.049
1.091
3.642
18.599
45.190
57.042
221.859
32.897
193.966
7.359
37.292
43.100
71.635
280.414
41.200
241.392
4.455
1.141
41.262
41.831
0.000
41.832
199.079
5.836
1.455
64.706
65.565
0.000
65.565
0.004
0.280
3.537
0.476
0.922
3.049
3.166
7.327
50.918
138.286
167.643
606.510
115.892
845.606
15.242
104.597
133.179
209.456
763.267
145.321
1,039.144
9.199
3.204
129.989
131.388
0.000
131.388
1,002.714
11.997
4.060
200.137
202.298
0.000
202.298
0.007
0.493
7.227
0.882
1.976
6.425
6.682
10.589
99.508
330.046
372.635
1,353.727
274.083
2,6720.045
22.516
208.125
317.307
443.787
1,647.498
331.728
3,150.009
13.763
6.474
323.232
325.117
0.000
325.117
3,062.425
17.885
8.195
482.012
485.095
0.000
485.095
0.010
0.746
12.077
1.421
3.436
11.578
12.006
14.133
174.904
721.560
777.273
2,838.618
587.715
6,459.406
30.740
373.992
694.822
Ml. 720
3,291.197
676.156
7,459.504
18.958
11.731
736.073
738.389
0.000
738.389
7,844.797
24.572
14.861
1,069.223
1,073.188
0.000
1 .073.1RR
0.011
0.988
15.860
1.947
4.576
17.008
17.504
18.260
263.278
1,281.422
1,356.666
5,165.273
1,084.152
13.892.355
40.498
575.910
1,248.089
1,508.547
5,830.914
1,212.880
15,415.832
25.132
18.118
1,350.855
1,354.089
0.000
1,354.089
17,152.004
32.554
22.932
1,943.094
1,948.455
0.000
1 .04R.4SS
0.013
1.253
0.029
2.551
5.839
23.784
24.332
23.066
384.038
2,230.666
2,327.909
8,840.082
1,865.854
26,636.168
52.209
859.543
2,194.427
2,541.875
9,793.219
2,049.568
28,678.437
32.555
27.101
2,427.698
2,432.022
0.000
2,432.022
33,552.543
42.153
34.271
3,453.305
3,460.241
0.000
1.4*0.741
0.015
1.549
25.019
3.271
7.371
32.587
33.191
28.706
555.135
3,930.552
4,050.651
15,249.957
3.231.867
48,350.137
66.369
1,271.675
3,894.938
4,341.871
16,570.477
3,484.455
50,766.086
41.545
40.170
4.415.059
4,420.520
0.000
4,420.520
62,959.516
53.771
50.772
6.185.703
6.194.250
0.000
f, tQ/, .7 VI

-------
                                  TABLE  III-6

                  T-Statistics  for  Emissions and Consumption*
                                1990   2000   2010   2020   2030   2040   2050
CFC-11 Nonaerosols

  World CFC Emissions
  World CFC Consumption


CFC-12 Nonaerosols

  World CFC Emissions
  World CFC Consumption
7.06
4.82
7.22
4.87
2.96
2.42
2.95
2.41
1.86
1.62
1.91
1.68
1.31
1.18
1.41
1.28
1.01
0.92
1.11
1.03
2.81
0.75
0.91
0.85
0.66
0.61
0.76
0.71
  *  Computed as the ratio of the mean estimates of Table III-l and the
     standard deviations of Table I1I-5.

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IV.  Worldwide Regulation of Aerosol Consumption.







     The results presented of the previous section do not reflect the




effects of any CFC regulation beyond the U.S. ban on nonessential use of




aerosols.  They are advanced as benchmark projection against which the




ability of further regulation can be judged.  They do not, therefore,




include the potential effects of either the voluntary cap on aerosol




capacity currently in place throughout the EEC or of other voluntary




restrictions on aerosol consumption now imposed by several other nations




around the world.




     The present section will report results for aerosols under an




alternative assumption that all of the regulation presently in place




throughout the world, be it voluntary or mandated by law, will remain in




effect for the next seven decades regardless of economic circumstance.




Future economic forces may, of course, cause some countries to weaken their




restraint; serious future environmental damage may, on the other hand, drive




more countries to impose stringent constraints upon themselves.  The future




regulatory environment is yet another source of uncertainty in projecting




ranges of emissions and concentrations for CFCs, but we will make no attempt




to endogenize the demand for regulation.  A  set of "worldwide status quo"




results  is, instead, reported in this section to provide some insight into




the potential effectiveness of current worldwide efforts to control aerosol




emissions.




     More specifically, we first assume that 1980 aerosol consumption in the




United States represents essential use.  We  apply, therefore, the frontier




growth model described in Sections I and II  directly to those initial




levels.  For the rest of the world, we assume (1) that the EEC capacity

-------
constraint will hold nonessential aerosol use at observed 1980 levels,  (2)




that the EEC capacity constraint will allow essential aerosol use to grow




and (3) that voluntary restrictions imposed by individual,  non-EEC nations




will hold their aerosol consumption fixed at 1980 levels (e.g.,  Japan:  25




percent reduction held fixed; Canada: 79 percent reduction held fixed;




Norway and Sweden: total ban held fixed). Finally, essential EEC use was




computed by applying the fraction of peak U.S. levels represented by 1980




U.S. consumption to the 1980 EEC consumption total.




     The significance of these assumptions for the two aerosol compounds is




displayed in Table IV-1.  Voluntary restraint across the world,  if it were




to continue as is for the next 70 years, would effectively fix 73,400 metric




tons of CFC-11 aerosol consumption at 1980 levels.  The remaining 38,500




tons of 1980 CFC-11 aerosol consumption  (35 percent of total) would thus be




allowed to grow as a reflection of essential use  in the U.S., essential use




in the EEC, or unrestrained essential and nonessential use across the rest




of the world.  Similarly, existing regulation would fix 106,400 metric tons




of CFC-12 aerosol consumption leaving 72,400 tons  (41 percent of 1980 world




consumption) to grow in one of the three categories just noted.




     Table IV-2 reports the major results of incorporating these assumptions




into the probabilistic scenario analysis.  All of  the statistics recorded




there — the base cases, the mean trajectories, and  the inner-quartile ranges —




\are all reduced by recognizing and projecting existing worldwide




regulation.  Annual growth rates of total world consumption over the 70 year




time horizon fall, for the mean trajectory (e.g.), from 4.22 percent per




year to 2.86 percent per year for CFC-11 aerosols  and from 4.20 percent per




year to 3.04 percent per year for CFC-12 aerosols.

-------
                                  TABLE IV-1

                 Distribution of 1980 CFC  Aerosol Consumption
               Between Constrained and Unconstrained Components*
                     U.S. Essential
CFC-11 Aerosols:

    Constrained
    Uncons trained
4.100
                EEC Essential
 6.170
                Rest of World
 73.390
 32.340
CFC-12 Aerosols:

    Constrained
    Uncons trained
5.400
10.730
106.400
 61.670
    *Measured in 10^ M tons of consumption.

-------
                                                  TABLE IV-2
                               Probabilistic Results—Consumption Responding to
                                    Voluntary Regulation Across the Worlda
A.  CFC-11 Aerosols
    United States:
                                     1980
     2000
25th
Mean
75th
Median
4.10(nc)b
4.10(nc)
4.10(nc)
4.10(nc)
5.71 (nc)
8.11 (nc)
9.61 (nc)
7.17 (nc)
                     6.63
                    15.47
                    19.17
                    10.67
        2020
          (nc)
          (nc)
          (nc)
          (nc)
       2050
  6.53
 34.02
 34.07
 15.43
(nc)
(nc)
(nc)
(nc)
    Rest of the World:
    World:
B.  CFC-12 Aerosols
    United States:
    Rest of the World:
    World:
25th
Mean
75th
Median
25th
Mean
75th
Median
111.90(nc)
111.90(nc)
111.90(nc)
111.90(nc)
116.00(nc)
116.00(nc)
116.00(nc)
116.00(nc)
127.63 (157.61)
162.88 (260.07)
192.55 (346.31)
153.36 (229.49)

135.93 (166.61)
170.99 (268.18)
200.43 (355.55)
159.53 (236.66)
25th
Mean
75th
Median
25th
Mean
75th
Median
25th
Mean
75th
Median
5.40(nc)
5.40(nc)
5.40(nc)
5.40(nc)
178.80(nc)
178.80(nc)
178.80(nc)
178.80(nc)
184.20(nc)
184.20(nc)
184.20(nc)
184.20(nc)
7.29 (nc)
10.02 (nc)
12.28 (nc)
9.34 (nc)
217.43 (274.19)
278.97 (426.18)
329.81 (551.75)
254.17 (364.94)
227.17 (283.74)
288.99 (436.19)
339.16 (561.09)
263.51 (374.28)
140.62   (195.37)
307.41   (680.14)
418.92 (1,004.24)
219.41   (424.39)

155.34   (201.61)
322.88   (695.61)
429.59 (1,014.92)
230.09   (435.06)
                     8.14
                    17.98
                    22.64
                    13.90
          (nc)
          (nc)
          (nc)
          (nc)
                   260.43   (380.39)
                   553.79 (1,104.89)
                   716.12 (1,505.76)
                   376.07   (665.99)

                   275.16   (395.12)
                   571.77 (1,122.87)
                   719.43 (1,509.08)
                   389.97   (679.89)
141.63   (198.31)
826.79 (2,189.74)
939.68 (2,517.84)
313.17   (696.89)

168.54   (220.32)
860.81 (2,223.76)
993.32 (2,541.29)
328.60   (712.31)
  8.42
 38.08
 40.74
 20.09
(nc)
(nc)
(nc)
(nc)
                      283.31   (436.90)
                    1,504.28 (3,452.26)
                    1,666.93 (3,853.91)
                      548.89 (1,092.79)

                      318.87   (475.29)
                    1,542.36 (3,490.34)
                    1,752.06 (3,944.15)
                      568.99  (1,12.88
a  Figures in parentheses are the comparable  results  in  the  absence  of worldwide  regulation (Section  III).

b  nc " no change.

-------
     Finally, to test the potential effectiveness of unilateral U.S.  aerosol




restriction, the model was manipulated to show that frontier growth rates




(CFC per GNP intensity) of -3.00 percent per year,  -1.95 percent per year,




and -1.20 percent per year for the 1980-2000, 2000-2025, and 2025-2500 eras




would be sufficient to hold CFC-12 aerosol consumption constant along the




base trajectory for the entire 70 year time horizon.  If these large




reductions in essential CFC use intensity were the result of economically




viable processes that were adopted by other producers around the world, then




the base case would lead to consumption in the rest of the world equal to




approximately 280,000 metric tons by the year 2050.  World consumption




would, as a result, be 50 percent lower than the regulatory base case




recorded in Table IV-2, but still 50 percent higher than in 1980.  Given




that the mean of the probabilistic runs is generally an order of magnitude




higher than the base case, even this extraordinary scenario does not allow




us  to expect that world aerosol consumption will not increase markedly over




the next 70 years.

-------
Appendix A: Specification and Estimation of the Demand for CFCs.


     The demand for CFCs is divided into two components.  The first,

designed to depict experience in the United States, is driven by the CFC

frontier described in Section I.  The second, designed to depict experience

outside the United States, is driven by U.S. demand and market development

in a way that is also described in Section I.  The precise specifications

and supporting estimation procedures of these two modeling structures are

recorded in this appendix.



A-l. Specification of Demand in the U.S. - the CFC Frontier.


     The fundamental construction underlying the U.S. model centers around

the specification of the potential frontier.  An asymptotic CFC intensity,

denoted by Z*(t), is assumed to grow over time at a constant growth rate

plus a random error term reflecting changing technology, price trends, and

incomes.  Accordingly,


           (A-l)     log  [Z*(t)] - a + gt + e(t)


where


   Z*(t) - potential CFC consumption per dollar of
           real GNP in year t;

       g — the growth rate of Z*  (positive or negative);

       a - an initializing parameter; and

    e(t) - a random error term.

According  to equation (A-l), the  asymptotic  frontier  in  Figure 1-2  should be

moving, on the average,  at an annual rate of g.  The  estimate for this

-------
average g is thus taken to be the middle value for the frontier growth rate


in the scenario analysis.  The high and low values are then simply the


reflection of the imprecision with which we can estimate that average g


given the uncertainty captured in (A-l) by the e(t).


     The two stage estimation procedure employed in Stage I of this work


turned out to be too sensitive to the initialization assumptions, and has


been discarded.  A second methodology based upon aggregate CFC proxies is,


instead, employed to estimate both the most likely value for g and its


surrounding range of uncertainty.  More specifically, we consider, for each


of the four chemicals (CFC-11 and -12, aerosols and nonaerosols), a time


series of indexed proxies defined by




     (A-2)       CFC(t) - •£ a (1973)X.(t),
                           >   J       J


where




              a (1973) - [CFC (1973)A1(1973)]
               J             J        J


are the CFC input/output coefficients for products X  computed using 1973


data.  The a.(1973) are, in other words, the product- specific CFC-usage


intensities that were observed in 1973.  Equation (A-2) uses these


intensities as weights in constructing a total use time series of derived


demand proxies based upon observed end product production levels recorded


over several decades.  Estimates of income elasticities for the  various CFC


chemicals can  then be obtained by estimating the income elasticities of the


constructed CFC(t) proxies over  recent years.  The result is a set of


reliable estimates of frontier income elasticities as long as  (1)  future


patterns of use for the  products are  close to historical ones  and  (2)  there

-------
is no systematic change in the CFC-usage intensities in future years.   The




desired estimates of frontier growth rates can,  finally,  be produced by




subtracting 1 from the elasticity estimates.




     The weights employed in this procedure are listed in Table A-l.  They




are expressed in terms of percent of total CFC use in each product category




because the actual CFC(t) proxy series are index number series normalized




for 1973 - 100.  Note, too, that CFC-11 and CFC-12 are distinguishable only




in nonaerosol form.  The end product use time series for the 12 product




groups listed are drawn from the U.S. National Income and Product Accounts;




their precise sources are noted in Table A-2.




     The resulting income elasticity estimates are recorded in Table A-3.




They conform, reasonably well, to less precise estimates that can be




obtained by computing the weighted average of end use income elasticities




produced by Houthakker and Taylor in 1970 (using, again, the weights of




Table A-l).  The standard errors of the income elasticity estimates are,




however, too small to be applicable as reasonable measures of the




uncertainty with which we project Into the future.




     As a way of estimating uncertainty about the growth of the CFC




frontier, we investigated the historical variation in growth rates of




different materials; Table A-4 displays the results.  The first line simply




records the standard deviation of the growth rate of 13 major materials over




the period 1900  to 1984:  a dispersion of 3.29 percent per annum.  A second




measure is the same statistic for 24 resources (both fuel and nonfuel)




studied by the Paley Commission.  Smaller dispersions are noted, probably




because the time period studied was one smaller  structural change.




     The most  appropriate measure is the error of forecasts of  24 materials

-------
                                   TABLE A-l
                            Weights for Estimating
                         the Derived Demand for CFCsa
New Construction

Household Furniture

Motor Vehicles

Textiles

Household Appliances

Marine Products

Electrical Equipment

Health Services

Food Products

Household Products

Personal Products

Industrial Products
                              Aerosols^
                            Nonaerosols
11
0
0
2.7
0
0
0
0
0
3.3
38.3
52.2
3.5
12
0
0
2.7
0
0
0
0
0
3.3
38.3
52.2
3.5
1J.
36.8
28.0
19.5
.9
9.2
2.2
0
0
3.4
0
0
0
12
19.8
56.9
3.9
0
4.0
.1
7.0
8.3
0
0
0
0
TOTAL
100.0
100.0
100.0
Notes:

    a  Expressed in percent of total in each category.

    t>  Source:  Exhibit 2-1 (1973 data), RAND, 1986.
100.0

-------
                               TABLE A-2

                        Sources for  Estimating
                     the Derived Demand  for  CFCs*
                                   Source                Series Name

New Construction              Table 1.2,  1.12               NC

Household Furniture           Table 2.5,  1.9                HF

Motor Vehicles                Table 2.5,  1.4                MV

Textiles                      Table 2.5,  1.27               TX

Household Appliances          Table 2.5,  1.10               HA

Marine Products               Table 2.5,  1.82               MP

Electrical Equipment          Table 1.2,  1.10               EE

Health Services               Table 2.5,  1.71               HS

Food Products                 Table 2.5,  1.20               FP

Household Products            Table 2.5,  1.37               CP

Personal Products             Table 2.5,  1.67               PP

Industrial Products           Table 1.4,  1.4                IP
*In each case, these refer to the U.S. National Income and Product
Accounts, Standard Tables, as In Survey of Current Business, July 1985.
Data are all in constant 1972 prices for the mentioned category.

-------
                                  TABLE A-3

                   Results for Estimates of Derived Demand
                             for CFC's:  1948-84*

                                             V                       _Q
Dependent Variable          Output Elasticity            Rho(p)      R

    Aerosols                     1.02                     .45       .999
                                 (.065)

    Nonaerosols-11               0.80                     .40       .926
                                 (.064)

    Nonaerosols-12               1.09                     .37       .979
                                 (.041)
Notes:
a
    Equation took the form ln(C.  ) « A + bln(GNP + pu  •, + e  where
    C   " weighted production of CFC-containing products; GNP ™ real GNP
    in 1972 prices; u  and e  " error terms;p  m estimated coefficient
    on first-order autoregressive error.
    Figures in parentheses under output elasticity are the standard error of
    the coefficient.

-------
                                  TABLE A-4

                      Standard Deviation in Growth Rates
                           for Different Materials
Source
    13 major materials,  1900-1984
        Standard Deviation of
Growth Rate (percent per year)

                3.29
    Paley Commission (24 materials)

         Actual 1950 vs. Actual 1972
         Forecast vs. Actual 1972
                2.49
                1.94
    Sources:   Data for the major materials were taken from U.S.  Department
              of Commerce, Historical Statistics of the United States;  data
              on the Paley Commission, from Richard cooper and Robert
              Lawrence, "The 1972-75 Commodity Boom," Brookings Papers  on
              Economic Activity, 1975.

-------
made by the Paley Commission for the period 1952 to 1972.   It is

conceptually closest to the uncertainty about the forecast of CFC use

prepared for this study.  We have rounded the figure to 2 percent per annum

when using it as the most likely forecast error for our CFC frontier growth

estimates.



A-2. Specification of Demand in the Rest of the World.


     In order to estimate the growth of CFC consumption in the rest of the

world, it is necessary  to estimate the demand for CFCs in regions outside of

the United States.  This task poses formidable difficulties because of a

lack of data on consumption throughout the rest of  the world, but

particularly outside of the OECD countries.  Rough  estimates are,

nonetheless, obtained in the following manner.

     The basic assumption, as stated in the text, is  that the trajectory of

consumption in the rest of the would will approach  the U.S. experience as

per capita incomes outside of the U.S. approach American levels.  To

represent this assumption formally, we consider


      (A-3)         InCCj^) - r In^/Y^ ,


where
      C,  - per  capita consumption or production of CFCs  in
           region k;

       k - 1 for the  U.S.,  2 for the EEC,  3 for developed
           developed  regions in the Pacific,  4 for the Eastern
           Block, 5 for Latin America,  6 for Africa,  and 7 for
           all  other  countries;

      Y,  - per  capita GNP for the same  country groupings; and

-------
      r — a coefficient to be estimated.







Data on CFC consumption, per capita incomes, and population are drawn from




the RAND report (1985).  The CFC consumption data is recorded in Table B-13.




The unallocated totals, labeled "other used in developed countries," were




allocated proportionally to CFC production identified for each region.  We




then estimated equation (A-3); the results are shown in Table A-5.  Moving




from the estimates of r to most likely middle values for the desired




"relative intensity elasticities" recorded in Table II-2 of the text is




again accomplished by subtracting 1 from the values recorded for the four




chemicals in Table A-5.  The ranges noted in II-2 are produced by assigning




values to the two outside 25 percent likelihood cells of plus and minus /2




times the standard deviations of the estimates also noted in Table A-5.




     The results confirm, in general, the initial impression that other




countries lag far behind the U.S. in their use of CFCs.  We may, therefore,




witness very rapid growth in CFC production and consumption in the rest of




the world if, in the absence of regulatory  restraint, economic growth




continues at historical levels in those countries.

-------
                                  Table A-5

                    Estimates of Cross Section Regression
                       —Per Capita Income Elasticities
Chemical              Elasticity (Standard Error of Coefficient)         R2

  11 Nonaerosols                   2.27 (.25)                           .848

  12 Nonaerosols                   2.15 (.20)                           .868

  11 Aerosols                      2.30 (.37)                           .729

  12 Aerosols                      1.93 (.27)                           .806

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Appendix B: The Data




     This appendix begins with a review of the procedure used to construct




the distributions for the exogenous variables identified in Section I of the




report: the rate of growth of population and productivity in the U.S. and




the rest of the world from 1980 through the year 2050.  Each distribution is




constructed to reflect not only statistical dispersion around published




estimates, but also judgmental dispersion evidenced by disagreement across




experts' best guesses.   A brief description of the CFG data used to




estimate the demand structure is also provided.







A. Population.




     The population growth estimates for the U.S. and the rest of the world




are both computed from a distribution of global growth rates  deduced from




the estimates recorded in Table B-l.  The upper part  of the table records




the projected rates of growth of the world population reported  in 9  separate




studies published since  1980.  The  averages  of  these  cited estimates are




caken  to be  the  maximum  likelihood  estimates  for world population growth  for




the periods  noted.  For  the  years  1980  through  2000,  for  example, the




published studies  include estimates ranging  from 1.3  percent  per year up  to




1.7 percent  per  year  with an average value of 1.6 percent.  The middle  cell




of a  three cell  distribution approximating the  true distribution of  our




uncertainty  about  future population growth rates should  therefore be




assigned the value  1.6 percent.




      For  this  study,  however, we needed more than point  estimates of the




most  likely  growth  estimates; we also  needed measures of the  uncertainty




associated with  each  future  projection.  One possible source  of these




measure was  the  cited authors'  own estimates of uncertainty,  but few authors




                                       1

-------
                                   Table B-l
                     Population Growth  Estimates  - Worlda

N-Y (1983)
EPA (1985)
UN (1985)
World Bank (1984)
Population Reference
Bureau (1985)
IIASA (1981)
Rotty and
Marland (1980)
OECD (1981)
Keyfitz (1985)
mean
(disagreement
dispersion)
1980-
2000
1.7
(.2)
1.6
1.6
(.13)
1.6
1.6
1.7
1.3
1.6
1.4
(.3)
1.6%
(.13%)
2000-
2025
1.1
(.36)
0.9
1.3
(.41)
1.2
1.2
0.9
1.3
-
0.9
(.3)
1.1%
(.182)
2025-
2050
0.3
(.35)
0.4
0.7
(.29)
0.7
_
-
_
-
0.4
(.3)
0.5%
(.15%)
judgemental dispersion
  (mean)                       .21%             .36%             .32%
Note:
    a   The numbers in parentheses represent cited or deduced judgemental
        estimates of standard deviation contained in source.

-------
provide these estimates.  Indeed, only 3 authors cited in Table B-l provided




error bounds of any kind for their forecasts.   For these three estimates,




though, the average of the judgmental uncertainty ranges does provide one




measure of dispersion.  It is identified as judgmental dispersion in Table




B-l and elsewhere; for the period from 1980 through 2000, an average of .21




percent per year is obtained.




     A second method of estimating the uncertainty around future trends




involves looking at the extent to which experts disagree in their




projections -- this measure is called the disagreement dispersion.




According to this technique, we examine, in the case of population covered




in Table B-l for example, disagreement across the 9 published estimates.




Taking these estimates as data and estimating the extent of uncertainty by




computing the standard deviation, we find a value of  .13 percent per year.




This second estimate  is of the same order of magnitude as the judgmental




dispersion just noted.




     Studies by behavioral psychologists and others have noted a nearly




universal tendency of people  to  underestimate the uncertainty associated




with many events.  Even experts  with knowledge  of statistics display this




tendency.   In a preliminary  paper designed  to quantify  this  tendency,




Nordhaus has considered the  issue of  translating disagreement  across




projections  of  the same event into  a measure of the  true uncertainty of the




event.   His  results,  rough but highly  suggestive,  imply  that both measures




of dispersion need to be  increased  by  a factor  of  50  percent before  they  can




be considered reasonable  indicators of the  true uncertainty  surrounding our




knowledge  about future  forecast  events such as  population  growth  rates  over




 the next 15 years.   Table B-2 records  this  expansion in columns  (D)  and (F)

-------
                                                    Table B-2
                                      Population Growth Estimates - World a
mean disagreement
years estimate dispersion
(A)
1980-2000
2000-2025
2025-2050
(B)
1.6%
1.1%
0.5%
(C)
.13%
.18%
.15%
adjusted
disagreement
(D)b
.20%
.27%
.23%
Judgemental
dispersion
(E)
.21%
.36%
.30%
adjusted
judgemental
(F)c
.32%
.54%
.45%
deduced
dispersion
(G)d
.30%
.40%
.35%
one standard
deviation range
(H)
1.3%/1.9%
o.2%/o!e%
Notes:
      a   Sources noted in Table B-l; based on 9, 8, and 5 published
          estimates for the three noted time periods respectively.

      b   Computed as 1.5 times column (C).

      c   Computed as 1.5 times column (E).

      d   Deduced estimation of standard deviation judged from the values
          noted in columns (D) and (F) adjusted in later eras to maintain
          consistency with the larger sample estimates of earlier eras.  The
          associated t-stats decline as the estimates apply further into the
          future (5.33; 2.75; 1.42).

-------
and ultimately proposes a deduced dispersion estimate for one standard




deviation around the sample mean of .3 percent.   The final assertion,




representing a slight adjustment for the sake of consistency within and




across time periods in the future, produces a one standard deviation range




of possible population growth rates of 1.3 percent per year and 1.9 percent




per year around a mean estimate of 1.6 percent.   The very same process




produces the recorded ranges for the other two time periods.




     World population growth estimates are not,  of course, estimates for the




United States.  To produce ranges of U.S. estimates, the well accepted




Keyfitz projections of .68 percent, .42 percent and .08 percent per year are




employed for the three time periods, respectively.  Requiring that the




ranges around these estimates have the same t-statistics as the world




estimates recorded in Table B-2, the estimates recorded for the U.S. in




Table B-3 are easily obtained.  Notice, though,  that the three possible




values are labeled "high", "medium" and "low" instead of plus and minus one




standard deviation.  That  is because the ranges recorded in Table B-3




represent the mean plus and minus  the square root of 2 times the deduced




dispersion estimate of one standard deviation.  Why?  Because a mean and a




standard deviation fully specify  a normal distribution for  a random




variable; and if that distribution is to be approximated by a three cell




discrete distribution with 25  percent,  50 percent and 25 percent probability




weights, then the values assigned to  the  two outside, 25 percent cells must




be the mean  plus and minus /2  times the standard  deviation.




      The rest of the world estimates  recorded in  Table B-3  were produced




similarly, but  have been adjusted slightly  from the world estimates by a




weighting process  that makes  them consistent with (1) the mean U.S.

-------
                                   Table  B-3
                          Population Growth  Ranges8


United States (percentage change per year)

      Era                           1980-2000       2000-25       2025-50

      High                              0.8            0.6           0.15
      Middle                            0.7            0.4           0.1
      Low                               0.6            0.3           0.0


Rest of World (percentage change per year)

      Era                           1980-2000       2000-25       2025-50

      High                              2.0            1.5           0.9
      Middle                            1.7            1.1           0.5
      Low                               1.3            0.7           0.2
      a  Source:  Table B-2; see text for procedure.

-------
estimates based on Keyfltz and reported in Table B-3,  (2) the mean world




estimates of Table B-2, (3) the standard deviations supporting the U.S.




ranges of Table B-3, and (4) the standard deviations reported in Table B-3.




The procedure that assures these consistencies is entirely algebraic.




Given, for example, an aggregate random variable, Z, that is the weighted




average of two other random variables, X and Y, according to




                      Z - aX + (l-a)Y,




knowledge about the distribution of Z and X can be translated into knowledge




about the distribution of Y according to




          mean(Y) - {[mean(Z)]-a[mean(X)]}/(l-a), and




           var(Y) - {[var(Z)-a2[var(X)]}/(l-a)2,




assuming that X and Y are uncorrelated.   Knowledge about the distribution




of population growth estimates for the world and the U.S. is thus sufficient




to produce consistent estimates about the distribution of population growth




across the rest of the world.







  . Productivity Growth.




     Productivity growth estimates for the U.S. and the  rest of the world




are based upon a similar procedure.  There exists a collection of studies




that report real GNP forecasts for the United  States.  A summary of their




content  is found on Table B-4, and its import  for present purposes indicated




in Table B-5.  Assuming an  independence between population  growth and GNP




growth that might not be justified,  the estimates and ranges  in Table B-5




for GNP  and Table B-3  for population are combined in Table  B-6  to produce




productivity growth estimates and ranges for the U.S.  Tables B-7 and B-8




display  the results of repeating the process for world productivity growth




projections so that Table B-9  records estimates and ranges  for the rest of




                                      4

-------
         Table B-4
GNP Growth Estimates - U.S.

Exxon (1980)
USDOE (1980)
H-K (1979)
RFF (high) (1980)
RFF (low) (1980)
WEC (high ) (1978)
WEC (low) (1978)
IIASA (high) (1980)
IIASA (low) (1980)
Mean
Judgmental
dispersion
1980- 2000-
2000 2025
2.7
2.5
3.0
2.7
2.3
3.5 3.1
2.5 2.5
3.7 2.2
2.4 1.0
2.89 2.20
.49 .88
2025-
2050
-
-
-
-
-
-
-
-

na
na

-------
                                            Table B-5
                                   GNP Growth Estimates—U.S.a


                    mean       judgmental      adjusted       deduced        one standard
 Years            estimate     dispersion     judgmental     dispersion     deviation range
  (A)                (B)          (C)            (D)b            (E)c               (F)

1980-2000            2.81%         .49%           .74%            .7%           2.1%/3.5%

2000-2025            2.20%         .88%          1.32%           1.3%           0.9%/3.5%

2025-2050             Data not available; world data used for both U.S. and rest of world.
a  Source:  Table B-4 based on 9 and 4 published estimates.

b  Computed at 1.5 times column (C).

c  Deducted estimation based on column (D).  The associated t-stats as the estimates apply
     further into the future (3.87 and 1.69).

-------
High

Middle

Low
                                 Table B-6

                     Productivity Growth Rates  - U.S.a
1980-2000
3.2
2.1
1.0
2000-2025
3.3
1.6
0.0
2025-2050b
2.2
1.1
0.0
a  Source:  Tables B-5 and B-3 assuming independence between
              population growth and GNP.

°  The world figures are used for both the U.S. and the rest of the
     world because of data deficiencies.

-------
                                  Table B-7
                    Productivity Growth Estimates - Worlds

N-Y (1983)
OECD (1981)
IEW (1985)
IIASA (1981)
Kahn (1977)
Lovins (1981)
E/R (1985)
Rotty and
Marland (1980)
RTF (1980)
EPA (1985)
WEL (1977)
Hudson
mean
(disagreement
dispersion)
judgemental
dispersion (mean)
1980-
2000
2.3
(0.7)
2.7
(.62)
1.47
(.67)
1.75
(.78)
2.75
1.29
2.67
(.67)
1.49
2.0
(.57)
1.60
1.74
(.76)
2.8
2. OX
(.59%)
.682
2000-
2025
1.6
(0.5)
-
2.77
(.47)
1.4
(.71)
3.1
0.9
-
1.50
1.95
(.21)
1.68
1.73
(.76)
1.4
1.8%
(.701)
.54Z
2025-
2050
1.0
-
-

1.19
0.5
—
-
-
1.67
-
.98
(.32)
1.1X
(.49%)
.32Z
Notes:
    a   The numbers in parentheses represent cited or deduced judgemental
        estimates of standard deviation contained in source.

-------
                                                   Table  B-8
                                    Productivity Growth Estimates - World3
             mean     disagreement    adjusted     judgmental
years      estimate    dispersion   disagreement   dispersion

 (A)         (B)           (C)          (D)b         (E)
                                                                 adjusted
                                                                judgmental
 deduced
dispersion

 (G)d
 one standard
deviation range

   (H)
1980-2000
2000-2025
2025-2050
2.0%
1.8%
1.1%
.60%
.70%
.49%
.90%
1.35%
.74%
.68%
.54%
.32%
1.02%
.81%
.48%
.95%
1.00%
.60%
1.05%/2.95%
.80%/2.80%
.50%/1.70%
NOTES:
    a  Sources noted in Table B-7; based on 12,  10,  and 5 published estimates for the three noted time
       periods respectively.

    b  Computed as 1.5 times column (C).

    c  Computed as 1.5 times column (E).

    d  Deduced estimation of standard deviation  judged from the values noted in columns (D) and (F) adjusted
       in later eras to maintain consistency with the larger sample estimates of earlier eras.   The
       associated t-stats decline as the estimates apply further into the future (2.11; 1.71;  1.38).

-------
                            Table  B-9




            Productivity Growth Ranges - Rest  of World3
Era
High
Middle
Low
1980-2000
2.9
2.0
1.1
2000-2025
2.8
1.8
0.9
2025-2050
1.7
1.1
0.5
a  Source:  Tables B-8 and B-6; see text.

-------
the world that are consistent with both the world estimates of Table B-8 and




the U.S. estimates of Table B-6.  The ranges reported in Tables B-6 and B-9




are not expanded by the same multiplicative factor of /2 to preserve both




the mean and the variance of the underlying normal distribution.  The




standard deviation estimates are used, instead, to reflect the effect of the




likely negative correlation between population growth and productivity.  The




procedure that assures consistency in moving not only from the U.S. and the




world estimates to the rest of the world,  but also from growth in total GNP




to growth in per capita GNP, is identical in spirit if not exact detail to




the algebraic process described above.




C. CFC Data.




     Two types of CFC emissions data are required to estimate the demand




structure.  The first, a time series of U.S. production for CFC-11 aerosols,




CFC-12 aerosols, CFC-11 nonaerosols, and CFC-12 nonaerosols, was found in




the TCF study.  They are recorded here in Tables B-10 through B-12.  It is




important to note that these series were, to a significant: degree,




constructed on the basis of a wide range of assumptions recorded in the




attached notes.  They may be the best data available, but they are therefore




far from perfect from a statistical perspective.  They are also production




data and not the consumption data that would usually be employed in demand




analysis.




     A second set of data, cross sectional production data for a specific




year, was also required (although, again, consumption data would have  been




more appropriate).  Table B-13 records the set that has been employed.  The




text surrounding its presentation as Table 4.1 in the January 1986 RAND




study [Quinn, et. al. 1986] outlined a series of steps employed to construct

-------
                            Table B-10
                   U.S. CFC Production - Total^
                                   CFC-llb        CFC-12b
         1958
         1959
         1960

         1961
         1962
         1963
         1964
         1965

         1966
         1967
         1968
         1969
         1970

         1971
         1972
         1973
         1974
         1975

         1976
         1977
         1978
         1979
         1980

         1981
         1982
         1983

Notes:

    a   Source:  IGF Table A-l.

    b   U.S. ITC.  Synthetic Organic Chemicals.  Annual
        Series.  These include CFC-22 used as an intermediate.
        Approximately 28 percent of CFF-22 is used in the
        production of teflon and other products.
22.90
27.40
32.80
41.20
56.60
63.60
67.40
77.30
77.30
82.70
92.70
108.20
110.90
117.00
135.90
151.40
154.70
122.30
116.20
96.40
87.90
75.80
71.70
73.80
63.70
73.10
59.60
71.30
75.50
78.70
94.30
98.60
103.40
123.10
129.90
140.50
147.70
166.80
170.30
176.70
199.20
221.70
221.10
178.30
178.30
162.50
148.40
133.30
133.80
147.60
117.00
134.30

-------
                                  Table  B-ll
                        U.S. CFC Production - Aerosals*

               Year                        CFC-11        GFC-12

               1958                         19.90t>         35.80C
               1959                         23 10          42.80
               I960                         26.70          45.30

               1961                         32.40          47.20
               1962                         43.20          56.60
               1963                         46.60          59.10
               1964                         47.50          62.00
               1965                         52.40          73.90

               1966                         50.20          77.90
               1967                         51.50          84.30
               1968                         55.20          88.60
               1969                         61.40         100.00
               1970                         60.004        102.10d

               1971                         63.10         106.20
               1972                         72.10         117.50
               1973                         83.40         135.20
               1974                         86.70         123.90
               1975                         73.30          94.50

               1976                         64.00          80.30
               1977                         36.50          47.30
               1978                         32.906         41.906
               1979                          9.50           5.30
               1980                          9.50           5.80

               1981                          9.50           5.60

Notes:

    a   Source:   ICF Table A-2

    b   Estimates for 1958-1969:  based on the assumption that in 1958 the
        U.S. dominates the OECD market as CFC-11.  In 1958, the CMA data
        (CMA.  Production, Sales, and Calculated Release of CFC-11 and 12
        through 1982; Expanded Data) show a market share of open cell.
        aerosol,  and all other production to be 87 percent of total CFC-11
        production.  Thus, the U.S. aerosol share of total CFC production is
        assumed to be 87 percent in 1958, declining smoothly to 54 percent
        in 1970,  where 54 percent is the aerosol proportion in 1970
        described in footnote C.  Total CFC-11 production is bsed on U.S.
        ITC data.

    c   Estimates for 1958-1969:  Based on the assumption that CFC-12
        aerosol production was 60 percent of total CFC-12 production, as it
        was in 1970.

    d   Data for 1970-1977:  U.S. EPA.  Regulation Chlorofluorocarbon
        Emissions;  Effects on Chemical Production.(EPA-560/12-80-0016)
        October 1980, pp. 73, 74, 80.  Reports production figures from pp.
        73-74,  using aerosol/nonaerosol proportions from p. 80.

    e   Estimates for 1978 and 1981 computed by subtracting usage in
        non-aerosol  applications  from  total  CFC  usage.   See Tables  10 and 12

-------
                                  Table B-12
                      U.S. CFG Production - Nonaerosalsa

               Year                        CFC-11         CFC-12
               1958                            OQ          23.8QC
               1959                          A. 30          28.50
               1960                          6.10          30.20

               1961                          8.80          31.50
               1962                         13.40          37.70
               1963                         17.00          39.50
               1964                         19.90          41.40
               1965                         24.90          49.20

               1966                         27.10          52.00
               1967                         31.20          56.20
               1968                         37.50          59.10
               1969                         46.80          66.80
               1970                         50.80d         68.00d

               1971                         54.00          70.80
               1972                         64.00          81.70
               1973                         68.00          86.60
               1974                         68.00          97.10
               1975                         49.00          83.90

               1976                         52.20          98.00
               1977                         59.90         115.20
               1978                         55. OO6        106. 50e
               1979                         66.30         128.00
               1980                         62.20         128.00

               1981                         64.30         142.00
               1982                         63.70f        117. 00f
               1983                         73.10         134.30

Notes:

    a   Source:   ICF Table A-3

    b   Estimates for 1958-1969:  CFC-aa non-aerosols are defined as CFC-11
        total minus CFC-11 aerosol (see table A-2).

    c   Estimates for 1958-1969:  based on the assumption that CFC-12 nonaerosol
        production was 40 percent of total CFC-12 production, as it was in 1970.

    d   Data for 1970-1977:  U.S. EPA.  Regulation Chlorofluorocarbon
        Emissions;  Effects on Chemical Production.  (EPA-560/12-60-0016)
        October 1980, pp. 73, 74, 80.  Reports production figures from pp.
        73-74, using aerosol/nonaerosol proportions from p. 80.

    e   Estimates for 1978-1981:  OECD.  Economic Aspects of CFC Emission
        Scenario*? prepared by the Chemical Groups and Management Committee, 15
        September 1982, p. 32.  Based on the assumption that the split between
        CFC-11 and cFC-12 in these years was the same as it was in 1977.

        Estimates for 1982-1982:  based on the assumption that production for
        aerosol applications is zero, which makes nonaerosol production equal to
        total production.

-------
                                  Table B-13
                        1980 Worldwide CFC Production3
                                    CFC-11                   CFC-12

      Region                   Aerosol   Nonaerosol     Aerosol   Nonaerosol

      Developing Nations          102.1     181.9          131.8     207.3

         U.S.                       4.1      67.6            5.4     128.4
         European Community        56.4      57.6           74.1      33.9
         Pacific                    8.2      35.7           10.8      36.9
         Other Uses in Developed
              Nations              33.4      21.0           42.6       8.1

      East Bloc                    10.7       8.8           45.2      36.9

      Developing Nations            3.2       2.6            6.2       5.0

         Latin America              1.7       1.4            3.4       2.7
         Africa                     1.4       1.1            2.2       1.8
         Other                      0.1       0.1            0.6       0.5


      Total                       116.0     193.3          184.2     249.2

      GRAND TOTAL                      309.3                    433.4



      a Source:  Rand Table 4.1.
(8304b)

-------
even this one year cross section from a variety of sources.   Of particular




note is the row labeled "Other Uses in Developed Nations" into which many




apparent discrepancies were collected.  Production listed there was, for the




purposes of estimation in this study, assumed to be distributed




proportionately across the non-U.S. developed countries.

-------
Appendix C: The Complete Model.







     The complete set of equations for the CFC projections produced in this




report is recorded here.  The form of the equations is identical for all




four chemicals, but the parameters differ according to the statistical




estimates.




     Equations (a) through (d) represent the exogenous projections of




populations (P) and per capita GNP (A) in the United States (US) and the




rest of the world (ROW):







     (a) PUS(t) exogenous     {3 paths):




     (b) PROW(t) exogenous    {3 paths);




     (c) AUS(t) exogenous     {3 paths); and




     (d) AROW(t) exogenous    {3 paths).







Equation (e) represents the growth in the CFC frontier in the United States,




where Z* is potential use of  CFCs per unit GNP.






     (e) log [Z*(t)] -  a + gt.   {3 frontier paths)







The ratio of actual to  potential CFC consumption  in the U.S.  [Z/Z*] is given




by a logistics curve for each frontier:






     (f) W(t) -  -b-ct    {1 for each frontier)







where the  definition of W(t)  is







     (g) Z(t) -  Z*(t)/U + exp[W(t)J)    (identity)

-------
Total CFG consumption in the U.S. is given by:


     (h) CFCUS(t) - Z(t) PUS(t) AUS(t)   {identity}


Total CFC consumption in the rest of the world is:


                            AROW(t)  E
     (i) CFCROW(t) - Z(t)  	   AROW(t) PROW(t)
                             AUS(t)


with 3 values of E.  Finally, the emissions of CFCs into the atmosphere,

ECFC(t), and the volume of the banks, BCFC(t), are be determined by Koyck

lag equations of the form


     (j) ECFC(t) - (1-d) BCFC(t-l)  + .1 CFCN(t) and


              {3 sets of equations defined by 3 d parameters)


     (k) BCFC(t) - d BCFC(t-l) +  .9 CFCN(t)


for nonaerosols and
      (j') ECFC(t) - CFCA(t) and
                                     {1 set of equations)
      (k') BCFC(t) - 0

-------
                              References
Camm, Frank, and James K. Hammitt, An Analytic Method for
      Constructing Scenarios from a Subjective Joint Probability
      Distribution, The Rand Corporation, N-2442-EPA, May 1986.

Chemical Manufacturers Association, Fluorocarbon Program Panel,
      World Production and Sales of Chlorofluorocarbons CFG-11 and
      CFG-12, various years.

Exxon Corporation, World Energy Outlook, New York, 1980.

Gibbs, Michael, ICF, "Scenarios of CFC Use:  1985-2075," presented
      at "Protecting the Ozone Layer:  Workshop on Demand and
      Control Technologies," U.S. EPA, Washington, D.C., March 6,
      1986.

Gibbs, Michael, ICF, "Summary of Historical Chlorofluorocarbon
      Production," ICF, presented at "Protecting the Ozone Layer:
      Workshop on Demand and Control Technologies," U.S. EPA,
      Washington, D.C., March 6, 1986.

Hafele, W., Energy In a Finite World, IIASA, Ballinger Publishing
      Co., Cambridge, Massachusetts, 1981.

Keyfitz, Nathan, et al., "Global Population 91975-2075) and Labor
      Force (1975-2050)," Institute for Energy Analysis, Oak Ridge
      Associate Universities, Oak Ridge, Tennessee, 1983.

Lovins, A.B., L.H. Lovins, F. Crause, and W. Bach, Energy Strategies
      for Low Climate Risks, prepared for the German Federal
      Environmental Agency, San Francisco International Project for
      Soft-Energy Paths, June 1981.

My T. Vu, World Population Projections 1984, World Bank, Washington,
      D.C., 1984.

National Academy of Sciences, Causes and Effects of Changes in
      Stratospheric Ozone;  Update 1983, Washington, D.C., 1984.

National Academy of Sciences, Causes and Effects in Stratospheric
      Ozone;  An Update, Washington, D.C., 1982.

National Academy of Sciences, Halocarbons:  Effects on Stratospheric
      Ozone, Washington, D.C., 1976.

National Academy of Sciences, Protection against Depletion of
      Stratospheric Ozone, Washington, D.c7, 1979.

Nordhaus, W.D. and G. Tohe, "Future Carbon Dioxide Emissions From
      Fossil Fuels," Changin Climate, National Academy of Sciences,
      Washington, D.C., 1983.

-------
References (Continued)                                          -2-
Palmer, Adele R., William E. Mooz, Timothy H. Quinn, and Kathleen A.
      Wolf, Economic Implications of Regulating Chlorofluorocarbon
      Emissions from Nonaerosol Applications, The Rand Corporation,
      R-2524-EPA, June 1980.

Population Reference Bureau, 1985 World Population Data Sheet,
      Washington, D.C., 1985.

Quinn, Timothy, Kathleen A. Wolf, William E. Mooze, James K.
      Hammitte, Thomas W. Chesnutt, and Syam Sarma, Projected Use,
      Emissions, and Banks of Potential Ozone Depleting Substances,
      The Rand Corporation, N-2282-EPA, January 1986.

Reilly, John,  Rayola Dougher, and Jae Edmonds, Determinants of
      Global Energy Supply to the Year 2050, Institute for Energy
      Analysis, Washington, D.C. 1981.

Ridker, R.G. and W.D. Watson, To Choose a Future, Baltimore,
      Maryland, The Johns Hopkins University Press, 1980.

Rotty, R.M. and G. Marland, Constraints on Carbon Dioxide Production
      From Fossil Fuel Use, ORAU/IEA-80-9(M), Institute for Energy
      Analysis, 1980.

Seidel, Stephen, and Dale Keyes, Can We Delay a Greenhouse Warming?,
      U.S. Environmental Protection Agency, EPA-230-10-84-001,
      Washington, D.C., 1983.

Tversky, Amos and Daniel Kahneman, "Judgment Under Uncertainty:
      Heuristics and Biases," Science, September 1974.

U.S. Department of Energy, Annual Report to Congress,
      DOE/EIA-0173C80), U.S. Department of Energy, Washington, D.C.,
      1980.

United Nations, World Population Prospects;  Estimates and
      Projections as Assessed in 1982, New York, New York, 1985.

Wolf, Kathleen A., Regulating Chlorofluorocarbon Emissions;  Effects
      on Chemical Production, The Rand Corporation, N-1483-EPA,
      August 1980.

World Energy Conference (WEC), The Full Report to the Conservation
      Commission of the World Energy Conference:  World Energy
      Demand, New York, IPC Science and Technology Press, 1981.
(1014c)

-------
 SCENARIOS OF CFC USE:   1985-2075

                 by
           Michael J. Gibbs
             Prepared for

        Strategic Studies Staff
       Office of Policy Analysis
Office of Policy,  Planning and  Evaluation
 U.S. Environmental  Protection  Agency
          401  M Street,  S.W.
        Washington, D.C.   20460
            February 1986

-------
                         EXECUTIVE SUMMARY
    Using recent historical trends as a guide,  potential future use and
emissions of chlorofluorocarbons (CFCs) are projected in a series of
scenarios.  The total use of CFCs 11, 12,  22,  and 113 worldwide is likely to
increase between 1985 and 2075 at an annual rate of approximately 2.4 percent
to 3.5 percent per year.   Use per capita is likely to increase at a rate of
1.7 percent to 2.7 percent per year.  At these  potential growth rates,  total
use of these CFCs may grow from the current annual level of approximately 1.2
million metric tons to between 10.0 and 27.5 million metric tons by 2075.

    The size of this range is driven by the uncertainties regarding the
primary determinants of future CFC consumption:  population growth and
economic growth.  A range of projections of global and regional population and
Gross National Product (GNP) was used to develop the CFC use scenarios.
Additionally, assumptions about the roles  of CFCs in future economies were
varied.

-------
                         TABLE OF  CONTENTS






                                                                        Page




EXECUTIVE SUMMARY 	     1




1.   INTRODUCTION 	     2




2.   DATA AND METHODS  	     3




    2.1  Data Sources  for CFC  Use  and Emissions  	     4




    2.2  Statistical Analysis  	     5




    2.3  Implementation of the Scenarios  	     7




3.   RESULTS 	    14




4.   LIMITATIONS 	    18




    4.1  Limitations  in Data 	    18




    4.2  Limitations  in Methods 	    19




    4.3  Next Steps  	    20




ANNEX A 	   A-1




ANNEX B 	   B-l




ANNEX C 	   C-l




ANNEX D 	   D-l




ANNEX E 	   E-l

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                                   -2-
I.   INTRODUCTION

    This paper presents scenarios of the potential future use of
chlorofluorocarbons (CFCs).  CFCs are a non-toxic, non-flammable class of
chemicals used as propellants in aerosol cans and for a variety of non-aerosol
applications (such as in making plastic foams and as the coolant in
refrigerators, air conditioners, and freezers).  In 1974, it was hypothesized
that CFCs emitted to the atmosphere will reduce the amount of ozone in the
stratosphere,1 thereby allowing greater amounts of ultraviolet radiation to
reach the earth's surface.  Since that time, considerable experimentation,
data collection, atmospheric monitoring, and modeling have been used to
investigate the potential for CFCs to induce stratospheric ozone depletion,
and the implications of such depletion.  In response to concerns over ozone
depletion, public use of CFCs as an aerosol propellant decreased in the United
States and abroad between 1974 and 1978 by two-thirds.  In 1978 the use of
CFCs in nonessential aerosol propellant applications was banned in the United
States.  Norway, Sweden, and Canada have adopted similar restrictions and the
European Economic Community has adopted a 30 percent cutback in the use of
CFCs as aerosol propellants.

    Due to concerns about potential ozone depletion that may be caused by CFC
emissions, the United States and other countries have initiated multilateral
negotiations regarding future uses and restrictions of CFCs.  Cooperation
among all countries is required in order to control the effects of CFC
emissions because the impacts of concern are global in nature; i.e., the
emissions have the same effects on stratospheric ozone regardless of their
point of origin.  In support of these negotiations, this analysis presents
potential future scenarios of CFC use and emissions worldwide through the year
2075.

    The effects of today's CFC use will be felt for a long time because the
chlorine released from CFCs remains in the stratosphere for a very long time,
up to hundreds of years.  If the chlorine that today's CFCs put into the
stratosphere cause problems in the future (e.g., by causing ozone depletion
after 2000), the only method we will have to correct those problems will be to
reduce CFC use at that time, i.e., in the future.   We will be unable to
remove from the stratosphere the chlorine put there by today's uses of CFCs.
Therefore, to evaluate the potential implications of policies to reduce CFC
use now or in the future, scenarios of CFC use into the fairly far off future
are required.
    1 M.J. Molina and F.S.  Rowland, "Stratospheric Sink for
Chlorofluoromethanes:   Chlorine Atom Catalysed Destruction of Ozone," Nature,
1974, pp. 810-812.

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                                   -3-
    This need to have long range scenarios  poses  a challenge  to  policy
analysts.   Most factors that will influence the use of CFCs  after  2000  can  be
projected only with great uncertainty.   Describing the potential changes  in
the economies and populations of developed  and developing countries  beyond
2000 is inherently uncertain.  Adding to this  demographic and economic
uncertainty is uncertainty regarding the roles that CFCs  will continue  to play
in the economies of various countries around the  world.   Within  the  next  90
years unforeseen technologies may develop that replace today's major uses of
CFCs or require additional use of CFCs.   The approaches developed  here  reflect
the key uncertainties in the analysis.   All the assumptions  that influence  the
scenarios are presented, and a range of  possible  scenarios is described.

    Even with the most advanced methods, however, scenarios  into the far-off
future must be considered somewhat speculative.  The later years of  the
scenarios can only identify what could possibly occur, but cannot  say with
any definitiveness what will actually occur.

    This paper first describes in section 2 the approach used to develop  the
scenarios.   Section 3 presents results of the analysis and section 4
summarizes  the limitations of the scenarios.

2.  DATA  AND METHODS

    This section summarizes the data and methods  used to project scenarios  of
CFC use and emissions worldwide.  The general approach is in three parts:

        •   collect data on the historical use of CFCs;

        •   analyze the data statistically to identify
            relationships between CFC use and population, GNP per
            capita, and the prices of CFCs; and

        •   use the results of the statistical analysis to project
            future use and emissions, also using  assumptions about
            future population and economic growth.

First the availability of historical CFC use data is described.
Then the statistical analysis is summarized.  Finally, the manner in
which the results of the statistical analysis are used to generate
the scenarios of CFC use and emissions  is presented.

-------
                                   -4-
    2.1  Data Sources  for CFC  Use and Emissions

    Data describing historical CFC use and emissions were collected from U.S.
Environmental Protection Agency (EPA) reports, U.S. International Trade
Commission (ITC) publications, Chemical Manufacturers Association (CMA)
reports, and Organisation for Economic Cooperation and Development (OECD)
reports.  A list of the data used and their sources are presented in Annex A.

    Data were generally available for the use of:

        •   CFC-11, CFC-12,  and CFC-22 in the U.S. from 1958 to
            1982;

        •   CFC-113 in the United States from 1958 to 1979;

        •   CFC-11, and CFC-12 in the OECD countries from 1958 to
            1982; and

        •   CFC-22 in the OECD countries from 1958 to 1975.

However, the division of total CFC use for CFC-11 and CFC-12 between aerosol
and non-aerosol applications was not available for the U.S. between 1958 and
1969 and not available for the other OECD countries between 1958 and 1975.
The distinction between aerosol and non-aerosol uses is important in order to
project separate scenarios of future aerosol and non-aerosol uses.  The
separate scenarios are needed because different control policies exist for the
two types of applications (and because different future control policies may
be contemplated).  The assumptions made regarding the aerosol/non-aerosol
division are described in Annex A.

    Data were generally not  available or not reliable for the following:

        •   CFC-113 in the OECD countries other than the U.S.; and

            CFC-11, CFC-12,  CFC-22 and CFC-113 in countries
            outside the OECD.

This lack of data is particularly troublesome because:  (1) the use of CFC-113
is expected to grow significantly (because it is used in the production of
electronic components); and  (2) the countries outside the OECD have the
overwhelming majority of the world's population, and their population and per
capita GNP are projected to  grow at a faster rate than in the developed
world.  Consequently these countries may represent potentially large future
users of CFCs.   As described below, alternative approaches (that are not based
on statistical analyses of historical data) were used to project scenarios of
potential use for these CFCs and portions of the world for which historical
data were not available.

-------
                                   •o-
    Data were also collected on the rate of emissions of CFCs.   Emissions do
not equal use for some CFC applications because the CFCs remain in some
products for many years (e.g., refrigerators).  Annex C describes the data
collected on emissions rates.  The emissions rates were used along with the
scenarios of future use to develop scenarios of future emissions.

    2.2  Statistical Analysis

    The objective of the statistical analysis was to describe the historical
behavior of CFC use over time using common economic and demographic variables
such as population and Gross National Product (GNP).  These variables were
used because CFC use can be shown to be related to them and because there are
a variety of projections for them that stretch far into the future.

    Basing the analysis on population and GNP is appropriate because the use
of most products and commodities in our modern economies is generally related
to the size of the economy and its wealth, or standard of living.  For
example, in various developed countries the use of products such as cars,
refrigerators, and housing is related to the number of people in the country,
and the average wealth per person.  The more people there are,  the greater the
use.  The wealthier the people, also the greater the use.  Cultural and other
local geographic and climatic factors are also important, but population and
wealth explain much of the observed differences between countries.

    This general idea of a product's use being related to population and
wealth applies not only to easily observable products such as cars and
refrigerators, but also to the things that are used to make these products.
For example, steel is used to make a large number of products,  including cars
and refrigerators.  The amount of steel used in different countries is
therefore related to the population and wealth of the country.

    The use of CFCs,  like steel, can also be thought of as being related to
the population and wealth of a country.  Using a statistical technique call
"regression analysis," the manner in which the use of CFCs has  varied in the
past with population and wealth can be estimated in the form of an equation.
These estimated equations can then be used to identify how CFC  use may change
in the future as population and wealth change.

    The equations estimated in this analysis relate historical  CFC use per
person on the one hand to GNP per person and the price of CFCs  on the other.
These equations are used with scenarios of future rates of growth in GNP per
person, the number of people, and the real price of CFCs to project the future
use of CFCs.

    The advantages of this method are that it is simple and straightforward,
it can be implemented with the type of data that exist, and it  can use
standard projection variables (population and GNP) to generate  scenarios.  The
primary shortcoming of this approach is that it does not describe the
underpinnings of the demand for CFCs.  Instead, it implicitly assumes that the
structure of the demand for CFCs remains constant through time.  If the
factors affecting demand change substantially, then the relationships
estimated using this approach will no longer be appropriate for projecting
future scenarios of CFC use.  Examples of important changes in the factors
affecting demand include:  changes in the relative prices of CFCs and their

-------
                                   -6-
substitutes due to changes in the prices of the raw materials used to make the
products or changes in the technologies used to make the products; and changes
in the ability to use or handle substitutes due to findings regarding their
toxicity.  Although it would be preferred to have available a rigorous demand
analysis that can reflect these potential changes, it was not undertaken
because:

        •   the data needed to perform the analysis was not
            readily available; and

        •   for the variables needed to project demand,
            established scenarios or estimates far into the future
            are not unavailable, and would have had to be developed.

The lack of good estimates of the future values of the detailed determinants
of CFG demand is particularly important because projections of CFC use will
only be as good as the projections of the variables used to derive CFC use.

    Using historical data on GNP, population, and prices (see Annex A for the
sources of the data) along with the historical data on CFC use, regression
analysis was used to estimate relationships for the following 10 combinations
of regions of the world; CFC type; and aerosol/non-aerosol application:

        1.   U.S.; CFC-11; aerosol
        2.   U.S.; CFC-11; non-aerosol
        3.   U.S.; CFC-12; aerosol
        4.   U.S.; CFC-12; non-aerosol
        5.   U.S.; CFC-22; total
        6.   U.S.; CFC-113; total
        7.   OECD-U.S.; CFC-11; aerosol
        8.   OECD-U.S.; CFC-11; non-aerosol
        9.   OECD-U.S.; CFC-12; aerosol
        10.  OECD-U.S.; CFC-12; non-aerosol.

Of note is that the analysis of U.S. aerosol applications only used data
through 1974.  The post-1974 use was assumed to be influenced by the rising
concern over ozone depletion and the subsequent U.S. ban on the use of CFCs as
aerosol propellants.  Similarly, the OECD-U.S. aerosol analysis only used data
through 1977.  By truncating the time series in this manner, the resulting
relationships reflect the level of CFC aerosol use in these locations in the
absence of existing restrictions.  Consequently, these relationships can be
used to assess whether the current restrictions are binding (i.e., the extent
to which use would be expected to have exceed the current levels absent the
attention given to the ozone-depletion issue and the subsequent regulations)
and to project scenarios of use in the absence of existing restrictions.
Results of the regression analysis are displayed in Annex B.

    Due to a lack of data, relationships could not be developed for the
following region of the world, CFC combinations:

            Non-OECD use of all CFCs (CFC-11; CFC-12; CFC-113;
            CFC-22);

-------
        •   OECD-U.S.  use of CFC-22 and CFC-113.

The next section describes how the relationships  estimated in the regression
analysis are used to generate the scenarios.   Also described are the methods
used to project potential use for the portions of the world for which
historical relationships could not be estimated.

    2.3  Implementation of the Scenarios

    Five scenarios of potential future use of CFCs were generated.   Three
scenarios, Low, Medium, and High, report the likely range of future CFC use.
In addition, two bounding scenarios were generated:  (1) "Limits to Growth," a
very low scenario; and (2) "No Limits to Growth," a very high scenario.
Although it is possible, it is unlikely that future use will fall outside
these bounding scenarios in the absence of government regulatory
intervention.   For total CFC use in the U.S., and for CFC-11 and CFC-12 use in
the OECD, the  scenarios were generated by inserting projections of population
and GNP per capita into the equations developed using the regression
analysis.  However, as described in the previous  section, equations could not
be developed for CFC-22 and CFC-113 use in the the non-LI.S. OECD countries and
for all the CFC use in the countries outside the  OECD.  Therefore,  alternative
approaches were used to project scenarios for these areas.

    All the approaches use population and GNP per capita as the basis for the
projections.  Consequently, these data are described first.  Then the manner
in which the regression equations were used is described.  Finally, the
alternative approaches are presented.

    Population and GNP Per Capita Projections

    The potential future use of CFCs will be driven by the growth in the world
population and the expected wealth of that population.  A variety of
projections have been published that provide estimates of potential future
population and GNP per capita through 2075.  These estimates were reviewed
along with information describing historical rates of growth.  Annex E
describes the data reviewed, and the assumptions  used to create five
projections of population and GNP per capita through 2075.

    Exhibit 2 summarizes the population projections for the world.  The
highest projection, 13.6 billion people by 2075,  is nearly double the  low
projection of 7.1 billion by 2075.  The growth rates implied in the
projections are also shown in the exhibit.  Of note is that all the
projections have the general trend of slowing growth rates over time.
Relative to the historical rate of population growth from  1925 to  1975  (1.9
percent), all the projections start out with slower growth.

    Not displayed  in Exhibit 2 are regional differences  in the population
projections.  The developing countries  are expected to grow more rapidly than
the developed countries  in all the projections.  Zero population growth  (ZPG)
is assumed to be achieved  in all  regions  in the  Limits to  Growth scenario by

-------
                                   -8-
                               EXHIBIT 2

                  SUMMARY  OF POPULATION PROJECTIONS
        (Billions of people -- rates of growth in  percent per year)

                                         SCENARIO
         1985
         2000
         2025
         2050
         2075
Limits to
Growth
4
(1
5
(0
6
(0
7
(-0
.6
.1%)
.4
.8%)
.5
.5%)
.3
. 1%)
Low
4.7
(1.5%)
5.9
(0.9%)
7.4
(0.2%)
7.7
(0.1%)
Medium
4.7
(1.5%)
5.9
(0.9%)
7.4
(0.4%)
8.2
(0.1%)
High
4.8
(1.6%)
6.1
(1.1%)
8.2
(0.6%)
9.5
(0.2%)
No Limits
to Growth
5
(1
6
(1
9
(1
12
(0
.0
.8%)
.5
.5%)
.5
.0%)
.1
.5%)
7.1
7.9
8.5
10.0
13.6
Source:  See Annex E.
2050.  The U.S.  and other OECD countries achieve ZPG by 2075  in the  Low and
Medium scenarios.   Annex E presents the regional breakdowns of the projections,

    Exhibit 3 displays the diversity among the GNP per capita projections.   By
2075, the highest  projection is over five times larger than the lowest
projection.  The range of uncertainty in the economic growth  projections is
larger than the  range for the population projections.  Compared to the
historical rate  of growth from 1925 to 1975 (2.1 percent per  year),  the
projections start  out slower.

    Scenarios Based on the Statistical Analysis

    The statistical analysis produced 10 equations that were  used to generate
scenarios for 10 region, compound,  end use combinations (see  Section 2.2 and
Annex B).  The scenarios were developed from each of the 10 equations by:   (1)
varying the population and GNP per  capita projections; and (2) modifying the
regression coefficients to reflect  uncertainty.

    The population and GNP per capita projections discussed above were  used.
For example,  the Low CFG scenario is based on the low population and low GNP
per capita projections.  The differences among the population and GNP per
capita projections account for the  majority of the differences in the CFC use
projections across the scenarios (over 80 percent).

-------
                                   -9-
                              EXHIBIT 3

                SUMMARY OF  GNP  PER  CAPITA PROJECTIONS
            (1975  U.S. $ -- rates of  growth in percent per year)

                                         SCENARIO
         1985
         2000
         2025
         2050
         2075
Limits to
Growth
1,
^
?
*™ »
(0
2,
(0
2,
(0
900
.0°,)
200
.5?;)
500
.5%)
850
.3%)
Low
1,900
(1.5%)
2,400
(1.2%)
3,200
(1.0%)
4,100
(1.0%)
Medium
1
(
2
>
1
»
(1
3
(
5
(
t
1
)
1
900
.7%)
450
.7%)
750
.7%)
700
.7%)
High
1
(1
2
(2
4
(2
6
(2
,950
.9%)
,550
.0%)
,200
.0%)
,883
.0%)
No
to
1
(2
2
(2
5
(2
9
(2
Limits
Growth
,950
.3%)
,750
~o/ \
,100
.5%)
,450
.5%)
3,050
5,250    8,650
11,242
17,550
Source:   See Annex E.
    The uncertainty in the estimates  of  the  regression  coefficients was  also
reflected in the scenarios.   Regression  analysis  provides  estimates of the
expected coefficients in the equations.   There  is uncertainty  in  these
estimates, which is expressed as  the  standard error  of  the estimated
regression coefficient.   The larger the  standard  error  relative to the size of
the coefficient, the more uncertain the  estimate  of  the coefficient  (and hence
the relationship).2  To reflect this  uncertainty, the coefficient on  GNP per
capita was varied across each of  the  scenarios.   Changing  the  coefficient by
plus and minus one standard error of  the estimate changed  the  scenarios  by
approximately 10 to 20 percent in each direction. These changes  are  small
relative to the differences caused by the alternative population  and  GNP per
capita projection.  The Low, Medium,  and High scenarios presented below  are
based on the estimate of the coefficient that is  produced  by the  regression
analysis.  The Limits to Growth scenario is  based in this  estimate
    2 It should be noted that the estimates of the standard errors are
probably biased downward as the result of serial correlation of the data.
Consequently, the relationships are more uncertain than indicated by the
regression results.   For more information on the influence of serial
correlation on uncertainty estimates in regression analysis see:   Pindyck,
R.S. and D.L. Rubinfeld, Econometric Models and Economic Forecasts,
McGraw/Hill  (New York),  1976, pp. 106-108.

-------
                                   -10-
minus one standard error of the estimate.   The  No  Limits  to Growth  scenario
is based on this estimate plus one standard error  of the  estimate.

    Several additional adjustments were performed  for all the scenarios.   To
reflect the current ban on the use of CFCs  as  an aerosol  propellant in
non-essential applications in the U.S., the annual aerosol use of CFC-11  and
CFC-12 was not permitted to exceed 4.5 million  kilograms  each.   Because  the
aerosol use in the U.S. would exceed this  level without the ban,  this
adjustment sets U.S.  aerosol use throughout the period examined at  this
level.  Similarly, the aerosol use restrictions in other  OECD countries  were
reflected.  Because the European Economic  Community (EEC) countries have
agreed to reduce their aerosol use to 70 percent of their 1976 use, the  EEC
use had to be projected separately.   To do  so,  the non-U.S. OECD estimates
were divided into an EEC portion and a non-EEC  portion using a constant
proportion.  The EEC portion is set at approximately 71 percent of  the aerosol
uses of CFC-11 and CFC-12 in the non-U.S.  OECD  (based on  data from  the
1970s).  To reflect the EEC aerosol restrictions,  the annual EEC use of  these
CFCs in aerosol applications is limitted to 54.5 million  kilograms  and 69.4
million kilograms, respectively.

    Other non-EEC countries have also instituted controls on the use of  CFCs
in aerosol applications.  Exhibit 4 shows  the  countries and the percent
reductions achieved to date.  As shown in  the  exhibit, the controls reduced
total use by approximately 40 percent.  This reduction is reflected in the
scenarios by assuming that future use would only be 60 percent of what it
would be estimated to be without the controls.

                                EXHIBIT 4

            REDUCTIONS IN CFC-I! AND CFC-12 USE IN  AEROSOL
           APPLICATION  IN NON-U.S., NON-EEC  OECD  COUNTRIES
  Country

Australia
Austria
Canada
Finland
Japan
New Zealand
Norway
Sweden
Switzerland
 Percent      CFC Use as Percent of
Reduction     Non-U.S.,  Non-EEC OECD

    35                  16
    30                   5
    79                  21
    20                   5
    25                  21
    49                   5
   100                   2
   100                   5
    23                  11
      Weighted
  Percent Reduction1

          6
          1
         16
          1
          5
          2
          2
          5
         _2
TOTAL:   40 percent
    1 Derived by multiplying first two columns.

Source:  Derived from:  Report on Chlorofluorocarbons,  OECD, April 1982.

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                                   -11-
    Scenarios Based on Alternative Approaches

    Because equations based on historical data could not be devloped for some
CFC uses in portions of the world, alternative approaches were used to
generate scenarios for these regions.   The scenarios for CFC-22 and CFC-113
use in the non-U.S. OECD countries were developed by assuming that the use of
these CFCs in the U.S. would remain a constant fraction of the total use in
the OECD.  For example, recent data indicate that the U.S. share of total
CFC-113 use in the OECD is approximately 65 percent.3  From the regression
equations, scenarios of the potential future U.S. use of CFC-113 are
generated.  To generate the scenarios for CFC-113 in the other OECD countries,
it is assumed that the 65 percent U.S.  share remains constant, meaning that
the use of CFC-113 in the non-U.S. OECD countries is approximately 54 percent
of the estimated U.S. use."  The U.S.  share of OECD use of CFC-22 is
approximately 80 percent.

    The implications of this approach is that the scenarios for non-U.S.
CFC-22 and CFC-113 use are based on projections for the U.S.  To the extent
that the U.S. data reflect the likely growth rate of the total use of these
CFCs in the OECD, the method provides a reasonable estimate of future OECD
use.  However, the share of OECD use accounted for by the U.S. may change in
the future, probably becoming smaller as the other OECD countries capture
larger shares of the electronics markets.  Consequently, even if the total
OECD CFC scenarios are reasonable, the U.S. share of this use may be biased
upward.

    Scenarios could not be based on historical data for the non-OECD
countries.  Instead, for purposes of projecting this use, it was assumed that
per-capita use would increase over time at a rate described by an "S-shaped"
curve.  This type of curve, shown in Exhibit 5, reflects the hypothesis that
as wealth per capita grows over time, the use of CFCs will also grow, but not
in a linear fashion.  Instead, once market penetration reaches a threshold (in
the exhibit shown as time T  to T9) the growth in CFC use may exceed the
growth in wealth.  Thereafter, the rate of increase in the use of CFCs
decreases relative to increases in wealth, as CFCs are used more efficiently
or as markets become saturated.
     3 Based on a comparison of U.S. data with OECD data.  U.S. data from:
A.D. Little, Preliminary Economic Impact Assessment of Possible Regulatory
Actions to Control Emissions of Selected Halocarbons. September 1976.  OECD
data from:  OECD (1981), Summary of the Conclusions Regarding Scenarios of
the  Ad Hoc Meeting. ENV/Chem/PJC/81.79.

     * The non-U.S. OECD share of the OECD use is 35 percent.  This quantity
is 35 * 65 = 54 percent of the projected U.S. use.

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                                   -12-



                                EXHIBIT 5

                    EXAMPLE  OF AN S-SHAPED CURVE
    Final Use
    Use/person
Current Use/person
                                      TIME
    To specify this S-shaped curve,  the logistic function was  used.5   The
shape of the curve is fully defined  by specifying the current  use  per  capita
at time T  and the final use per capita at time T^.   Current use per

capita estimates are shown in Exhibit 6.   For example,  in the  non-U.S.  OECD,
current use per capita of CFC-11 is  approximately 0.58  kilograms.   In  the
non-OECD countries, use per capita is currently approximately  1.2  percent  of
this value (or about 0.007 kilograms).  Using the logistic function, this
fraction of 1.2 percent will grow over time to the final fraction  specified
for 2075.
5 The logistic function is  f = l+exp(-a-bt); where
    are parameters defining the shape  of  the curve.
                                                       "t"
is time and 'a
            it/-u
and "b" are parameters defining the shape of the curve.   The value for 'f
computed for each time, t, is multiplied by ]th& expected finapuse to compute
the use at time t.  For example, the final (i.e., ending year) use is defined
as the use per capita expected to be achieved in 2075.   To estimate the use
per capita in 2050, the value of "f" in 2050 (which will be less than 1.0) is
multiplied by the final per-capita/ use.

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                                   -13-



                                EXHIBiT 6

                   CURRENT PER-CAPITA  USE OF CFCs
            CFC
      Annual
  Per-Capita Use
 in OECD Countries
Other than the U.S.1
    (kg/person)
                                               Annual Per-Capitalf Use
                                               in Non-OECD Countries
                                                 as a  Percentage
                                                of Annual Per-Capita
                                               Use in OECD Countries
CFC-11
CFC-12
CFC-22
CFC-113
0
0
0
0
.58
.58
.06
.04
1
5
3
3
.22
.32
.83
.83
    1  Estimated by taking the most  current  estimate  of  the total use
available (1982 or 1983)  and dividing by  the  total number of people in the
OECD.

    2  Current total use for CFC-11  and CFC-12 was taken from "Production,
Sales, and Calculated Release of  CFC-11 and CFC-12 through 1982," Chemical
Manufacturers Association (1983).   The CMA  cautions  that these  estimates are
uncertain because they are based  on extrapolation of data reported for earlier
years.  However,  estimates of the current use in the non-OECD countries do not
influence the overall scenarios significantly.

    3  Current total use of CFC-22 and CFC-113 was derived using estimates of
the share of total world use calculated for these countries from data  in OECD
(1976), Fluorocarbons:   An Assessment of  Worldwide Production,  Use and
Environmental Issues, pp. 30-35.

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                                   -14-
    Th e final fraction was estimated using the projected GNP per capita in the
non-OECD countries, and the current relationship between per capita use and
per capita GNP in the non-U.S. OECD countries.  For example, in the medium
population and GNP per capita projection, the GNP per capita in the non-OECD
countries reaches approximately 85 percent of the 1980 GNP per capita in the
non-U.S. OECD countries.  Consequently,  it was assumed that by 2075, CFC use
per capita in the non-OECD countries would reach this same fraction (85
percent) of the 1980 use per capita in the non-U.S. OECD.  The estimate for
the low and high projections were 53 percent and 111 percent.

    Exhibit 7 summarizes the assumptions in the scenarios.

3.  RESULTS

    This section presents five scenarios of future CFC use and emissions
worldwide.  These scenarios incorporate  the current restrictions on CFC use in
aerosol applications in the U.S. and elsewhere.

    Exhibit 8 summarizes the results for the scenarios.6  For example, the
Medium scenario for CFC-11 shows world use growing from approximately 400
million kilograms in 1985 to about 7,600 million kilograms by 2075.  This is
an average rate of growth of 3.3 percent per year.  The growth rate in the
Medium scenario is not constant, however.  The early years have nearly a 4.5
percent annual rate of growth, and the later years have growth at 2.0 percent
per year.

    The annual use of CFC-11 in the Low  scenario in Exhibit 8 grows on average
at only 2.6 percent per year throughout  the entire period examined, resulting
in 4.3 billion kilograms of use by 2075.  The High scenario has larger use of
CFC-11 over time, with an average annual growth rate of 3.7 percent.

    The growth in use per capita is smaller than the growth in total use
because population also increases over time.  For the total of all four CFCs
examined,  world per capita use reaches the following levels in the five
scenarios  (smallest to largest):  (1) 0.65 kilograms; (2) 1.3 kilograms; (3)
2.1 kilograms; (4) 2.8 kilograms; and (5) 4.6 kilograms.  Current per capita
use in the non-U.S. OECD countries is approximately 1.3 kilograms, and in the
U.S.  is approximately 1.6 kilograms (both these estimates reflect existing
restrictions on aerosol applications).   Consequently, per capita use in the
1.3 to 2.8 kilograms range from the Low, Medium, and High scenarios seems
plausible.  The Limits to Growth scenario has per capita use well below
current rates in the developed world.  Non-OECD countries would be required to
have very  low economic and population growth over the next 90 years to achieve
the per capita use estimates in the Limits to Growth scenario.  Similarly, the
No Limits  to Growth Scenario has very high per capita as rates, requiring both
large population growth and excellent economic performance to be achieved.
      Annex D presents scenario results for each of the major regions of the
world.

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                                                            EXHIBIT  7

                                                 SUMMARY  OF  SCENARIO ASSUMPTIONS
PopnI at ion
Project ion
CNP Per
Cap ila
Project ion
ciowth of
Use in OECD
Countries
                    Limits to
                 Growth Scenario
  (Grows at an average
  j rate or 0.5 percent
  I ( 1985-2075)
 Grows  at  an average
 rate of 0.58 percent
 (1985-2075)
  IGrows at average  real
  irate of 0.5  percent
  |(1985-2075)
 Grows  at  average  real
'rate of  I.I percent
 (1985-2075)
  (Historical  re lationship Based
  |reduced  to  reflect  un-
  Icertainty  (minus one
_ [standard errorj	
 "I
Growth of Use I Follows ;m S-shaped
in Non-OECO  (curve.   Reaches 30
Countries    (percent of current per
             (capita  use in non-U.S,
             (OECD countries
Restr ict ions
   Performed with current
   aerosol  use  restric-
   t ions
                               Low Scenario
       on  h i stor icaI
 relat ionship
                           Follows an S-shapod
                           curve.  Reaches 53
                           percent of current per
                           cap i ta use i n i
                           OECD countries
 Performed with
 aerosol  use  res
 t ions

je
ant
rea 1
nt
a 1
;d
3
t per
-U.S.
rrent
ic-
Medium Scenario
Grows at an average
rate of 0.65 per-
cent ( 1985-2075)
Grows at an average
rea 1 rate of 1.7
percent ( 1985-2075)
Based on h i stor ica 1
re lat ionsh i p
Follows an S-shaped
curve. Reaches 85
percent of current
per cap i ta use i n
rion-U.S. OECD
countries
High Scenario
Grows at an average
rate of 0.8 percent
( 1985-2075)
Grows at average real
rate of 2.0 percent
( 1985-2075)
Based on h i stor ica 1
re lat ionsh i p
N
Gr
Grows
rate
( 1985
Grows
ra te
( 1985
H i sto
i nc re
uncer
stand
Fo 1 lows an S-shaped Fo 1 lo
curve. Reaches III jcuive
percent of current perjperce
capita use in rion-U. S. j cap i t
OECD countries (OECD
Performed with cur- Performed witfi cur-
rent aerosol use rent aerosol use
restrictions restrictions
Perl o
aeros
t ions
                                                                                                No limits to
                                                                                               Growth Scenario
Grows at average real
rate of 2.5 percent
        a I  re I a tionship
        J to retlect
        i ty (plus one
         erro r )	
                                                                       iws an  S-shaped
                                                                          Roaches  IY?
                                                                       nt of  current per
                                                                       a use  in  non-U.S.
                                                                       count r i es
       3d wi tri current
        use rustric-

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                                                            EXHIBIT 8



                                                     SUMMARY OF CFC SCENARIOS
                              LOW SCENARIO
                                                                   MEDIUM SCENARIO
                                                                                                            HIGH SCENARIO

CFC- 1 1
CFC- 12
CFC-22
CFC-I 13
CFC-I 1
CFC-12
CFC-22
CFC- 1 13
CFC-I 1
CFC-12
CFC-22
CFC- 1 1 3
Potential Future Use
(millions of kilograms)
1985
2000
2025
2050
2075
Average Growth
1985-2000
2000-2025
2025-2050
2050-2075
«400
725
1,1475
2,550
14,325
Rate (%)
4.0
2.9
2.2
2.2
550
950
1,775
2,750
14, 175

3.7
2.6
1 .7
1.7
1 10
220
380
5*40
830

14.7
2.2
1 .>4
1 .7
95
200
3')0
1475
725

5.0
2.2
1 .14
1 . 7
400
785
2,035
14,625
7,650

14.5
3.9
3.3
2.0
560
1,065
2,525
14,825
7,350

14.14
3.5
2.6
1 .7
1 10
235
500
930
1,550

5. 1
3. 1
2.5
2. 1
95
210
«450
820
1 ,380

5.4
3. 1
2.5
2. 1
»430
980
3,850
8,2140
1 1,680

5.6
5.6
3. 1
1 .14
600
1 , 1450
14,620
8, 130
1 1,2140

6.0
14.7
2.8
1 .3
1 15
280
790
1 ,1480
2,1425

6.2
14.2
2.6
?.o
95
250
6/5
1 ,280
2, 170

6. '4
14. 1
2.6
2. 1
Source:   ICF Incorporated Estimate.

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                                          [XHIIilT  8  (continued)



                                         SUMMARY OF  CFG SCENARIOS
                                 LIMIIS  10 GROW III  SCENARIO
                                                                       NO LIMITS 10 GROW IH  SCENARIO

Potential Future Use
(mill ions of ki log rams)
1985
2000
2025
2050
2075
Average Growth Rate (%)
1985-2000
2000-2025
2025-2050
2050-2075
CFC-I 1

350
550
860
1 ,'lOO
2,050

3.2
1.9
1.9
1.6
CFC- 12

*460
700
1 , OUO
1 .520
2,000

2.8
1 .6
1 .5
1 .0
CFC-22

75
135
180
250
320

U. 1
1 .2
1 . 3
1 .0
CFC- 1 13

75
!30
175
230
290

t». 1
1 . 1
1 . 1
1 .0
CFC- 1 1

500
1,325
6,550
16, 100
25,850

6.5
6.6
3.7
1 .9
CFC-12

800
2, 120
8,020
16,075
25,250

6.7
5.5
2.8
1 .8
CFC-22

160
1*20
1 ,*400
3, 100
5,885

6.7
5.0
3.2
2.6
CFC- 1 13

125
3»45
1 , 150
2,570
5,075

7.0
U.9
3. 3
2.8
Source:  ICF  Incorporated Estimate.

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                                   -18-
    Also of interest is the projected "intensity of use" in each of the
scenarios.  Intensity of use measures the contribution that CFCs are expected
to make to overall economic activity, measured in kilograms per 1,000 dollars
of GNP (1975 U.S. dollars).  In 2075 the intensity of use in each of the five
scenarios is estimated as:  (1) 0.21 kilograms; (2) 0.24 kilograms; (3) 0.24
kilograms; (4) 0.25 kilograms;  and (5) 0.26 kilograms.  The current intensity
of use in the U.S. and in the non-U.S. OECD countries is approximately 0.2
kilograms.  The scenarios, therefore, do not reflect an unreasonably large
intensity of use of CFCs over the next 90 years.

4.  LIMITATIONS

    This section discusses the major limitations of the data and methods used
to project scenarios of CFC use and emissions.  Many of these limitations are
inherent in all projections far into the future.  Others, however, relate to
the lack of historical data describing CFC use in many parts of the world and
the simple methods used to generate the scenarios.  Individuals considering
using the scenarios should be fully aware of the limitations presented here.

    4.1   Limitations in  Data

    Historical data on CFC use and emissions form the basis for the
projections of the CFC scenarios.  The data are most detailed and complete for
the United States, from 1970 to the present.  Aggregate data (not
differentiated by CFC or use) are available for the OECD for CFC-11, CFC-12,
and CFC-22.  However, data are particularly sketchy in the following areas:

        •   Prior to 1970, the division of CFC-11 and CFC-12
            between aerosol and nonaerosol uses in the United States
            is not documented.   The division was made by assumption
            for purposes of this study.

        •   Data describing the historical use of CFC-113 outside
            the United States have not been developed.  Rough
            estimates of the current U.S. share of OECD use of
            CFC-113 were the only data available to describe the use
            of CFC-113 outside the U.S.

        •   The mix of uses of CFC-11 and CFC-12 in the OECD is
            only documented for selected years (i.e., the fraction
            used in foams, air conditioners, aerosol propellants,
            etc.).  The mix of uses in the United States was assumed
            to apply to the entire OECD for purposes of developing
            emissions rates from use.

        •   Data for non-OECD countries are unreliable or
            nonexistent.

    These data difficulties were overcome by adopting reasonable assumptions.
However, alternative assumptions are plausible that may influence the
scenarios.

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                                   -19-
    4.2  Limitations in Methods

    The methods used in this study to project scenarios of future CFG use are
simple and straightforward.  Historical data are used to develop relationships
between CFC use and population and GN'P.  These relationships are then used as
the basis for projecting future scenarios.  The limitations of this method
include:

        •   The structural underpinnings of demand are not
            estimated.  The method assumes that the determinants of
            demand, in relation to the variables used to make
            projections (population and GN'P), remain unchanged.

        •   The relationships are based on a fairly narrow range
            of experience, from a unique history.   In the future,
            population and GNP will be far outside the historical
            range for the OECD countries.  Therefore, even if the
            relationships among the variables are estimated
            correctly, there is considerable uncertainty surrounding
            estimates of future use.

        •   Estimates of population and GNP far into the future
            are inherently uncertain.  The range of estimates used
            may understate the full range of possible future
            outcomes.

        •   Non-OECD use of each CFC was projected by assuming
            that per-capita use in these countries would reach a
            portion of current per-capita use in the non-U.S. OECD.
            Of note is that the OECD experience may not be
            applicable to these non-OECD countries due to
            differences in culture, economies, climate, and other
            factors.
        •   By using historical data,  the scenarios reflect the
            historical rate of the introduction of new uses for
            CFCs.   However, the method does not explicitly explore
            the potential for new uses,  nor does it address the
            potential for new substitutes or more efficient use of
            CFCs in existing uses.

        •   Constraints in the future  production of CFCs were not
            explored.

    These limitations can be addressed by performing additional research and
analysis.  However, scenarios that project far into the future will always be
fairly uncertain.   The next section provides recommendations for next steps.

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                                   -20-
    4,3  Next Steps

    To improve the scenarios reported here,  analysis should focus  on potential
natural or man-made constraints to future CFC production and use.   This
analysis could first explore the implications of the scenarios of  future CFC
use in termes of demand for complementary products (e.g.,  automobiles,
housing, furniture).   Other issues include:

        •   the likely future availability of the raw materials
            needed to make CFCs;

        •   the capital investment required in plant and equipment
            needed to produce CFCs at the projected rate;

        •   the potential elimination of CFC substitutes in
            certain applications due to their toxicity (e.g., carbon
            tetrachloride used as a solvent in developing nations);

        •   increased refrigeration and space-cooling requirements
            as global warming occurs; and

        •   differences in potential future use among countries
            developing at different rates (e.g., rapidly developing
            countries like Taiwan, Brazil, Korea), and among
            countries that may follow very different development
            paths (e.g., Tanzania).

By examining these factors, the potential constraints on future CFC use can be
explored.7  These constraints may indicate when important turning points in
the scenarios occur, i.e., when use cannot grow at rates indicated by the
analysis of the historical data.

    If constraints are found to be important, the structural underpinning of
demand should also be explored.  This information will be required to assess
how the future constrained amounts of CFCs will be divided among potential
competing uses.  Additionally, this information may be useful  for  improving
estimates of future uses in the non-OECD countries by identifying  important
differences between these countries and the OECD countries.
     7 Of note is that as recently as 1976 it was reported that the projected
supply of fluorine in the world is "immense and provides no practical  limit to
CFM  [CFC] production," in Halocarbons:  Effects on Stratospheric Ozone,
National Academy of Sciences, 1976, p. 174.  Consequently, the availability
and/or price of this raw material may not pose a constraint on the future
production of CFCs.  More recent analyses confirm this conclusion, see:  Mooz,
William E., Kathleen A. Wolf, Frank Camm, "Potential Constraints on Cumulative
Global Production of Chlorofluorocarbons," The RAND Corporation, WD-2864-EPA,
December 1985, and Gibbs, Michael J. and Robin Weiner, "Assessment of  the
Availability of Fluorine for the Production of Chlorofluorocarbons," ICF
Incorporated, February 1986.

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                                   A-l
                               ANNEX  A
    This Annex presents the historical data used to project  scenarios  of
future CFC use.   The data are presented in a series of tables.   Each table  is
followed by a description and the footnotes that list  the sources  of the
data.  Exhibit A-l lists the tables presented.

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           A-2








        EXHIBIT A-1




LIST OF TABLES  IN ANNEX A
Table Title Page
A-1
A-2
A-3
A-4
A-5
A-6
A-7
A-8
U.S. CFC Production Data - Total
U.S. CFC Production Data - Aerosols
U.S. CFC Production Data - Non-Aerosols
Nominal and Real CFC Prices
U.S. Economic Data
OECD CFC Production Data
OECD Economic Data
Projections of GNP and Population Relative to 1975
A-3
A-5
A-7
A-9
A-ll
A-13
A-17
A-19

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                         A-3
                      TABLE A-1

          U.S. CFC PRODUCTION DATA  - TOTAL
                 (Millions of Kilograms)
YEAR
CFC-11 a/
CFC-12 a/
CFC-22 a/
CFC-113 c/
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
22.90
27.40
32.80
41.20
56.60
63.60
67.40
77.30
77.30
82.70
92.70
108.20
110.90
117.00
135.90
151.40
154.70
122.30
116.20
96.40
87.90
75.80
71.70
73.80
63.70
73.10
59.60
71.30
75.50
78.70
94.30
98.60
103.40
123.10
129.90
140.50
147.70
166.80
170.30
176.70
199.20
221.70
221.10
178.30
178.30
162.50
148.40
133.30
133.80
147.60
117.00
134.30
15.10 b/
16.60
18.20
20.50
22.30
24.50
26.80
29.10
31.80
35.50
39.10
42.70
45.50
50.90
55.90
61.80
64.10
59.80
77.00
81.40
93.30
95.60
103.20
114.20
79.00
106.90
0.00
0.00
2.00
3.00
4.00
4.50
5.40
6.40
7.30
9.50
11.40
13.60
16.40
19.50
22.70
26.80
29.00
31.00
37.10
45.20
51.20
58.80
45.90
48.20
50.00
52.70
    a/ See attached footnotes.

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                                   A-4
            TABLE A-1:   U.S. CFC PRODUCTION DATA -  TOTAL
Description:
Footnotes:
Table A-1 presents time series  data on the  total  U.S.
production of CFC-11,  CFC-12, CFC-22,  and CFC-113 for  the  years
1958 to 1983.  The primary source of these  data  is  the U.S.
International Trade Commission.   It was necessary to estimate
some values using assumptions based on actual  data.  The
footnotes which accompany the table describe these  assumptions.

a)  U.S. ITC.  Synthetic Organic Chemicals.  Annual Series.
    These include CFC-22 used as an intermediate.
    Approximately 28 percent of CFC-22 is used in the
    production of teflon and other products.

b)  Estimates for 1958-59 for CFC-22 are based on average
    annual percent changes over the period  1960-65.

c)  For 1958 to 1962,  U.S. production is assumed to be 100
    percent of total world production reported in:   OECD,  1981,
    Summary of the Conclusions  Regarding Scenarios of  the  Ad
    Hoc Meeting, ENV/CHEM/PJC/81.79, p. D.I.  U.S.  production
    in  1963 was assumed to be  90 percent of the world  total
    reported in the OECD document.  Data for 1964 to 1974  are
    from:  A.D. Little, Preliminary Economic Impact Assessment
    of Possible Regulatory Actions to Control  Emissions of
    Selected Halocarbons, September 1976.  Data for 1975  to
    1979 are estimated by taking the portion of world  CFC-113
    production accounted for by the U.S. in 1974 (64.6 percent)
    and multiplying by the world production reported in the
    OECD document.  The years  1980 to 1983  are projecrions
    reported in U.S. EPA, Economic Implications of
    Regulating Chlorofluorocarbon Emissions from Nonaerosol
    Applications, (EPA-560/12-80-001), October 1980,  pp.  67-68.

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                A-5
              TABLE A-2

U.S. CFC PRODUCTION DATA -  AEROSOLS
         (Millions of Kilograms)
      YEAR     CFC-11       CFC-12
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
19.90 a/
23.10
26.70
32.40
43.20
46.60
47.50
52.40
50.20
51.50
55.20
61.40
60.00 c/
63.10
72.10
83.40
86.70
73.30
64.00
36.50
32.90 d/
9.50
9.50
9.50
35.80 b/
42.80
45.30
47.20
56.60
59. 10
62.00
73.90
77.90
84.30
88.60
100.00
102.10 c/
106.20
117.50
135.20
123.90
94.50
80.30
47.30
41.90 d/
5.30
5.80
5.60
          a/ See  attached footnotes.

-------
                                   A-6
          TABLE A-2:   U.S. CFC PRODUCTION DATA - AEROSOLS
Description:
Footnotes:
Table A-2 presents time series data on the  total  U.S.  CFC
production of CFC-11 and CFC-12 for aerosol applications.  The
statistical analyses performed to project potential  aerosol
applications in the absence of government regulation used  data
for the years 1958 to 1974.  Use in the years  following  1974
may be influenced by expectations regarding government
regulation.

a)  Estimates for 1958-1969:   based on the  assumption that in
    1958 the U.S. dominates the OECD market as CFC-11.  In
    1958, the CMA data (CMA.   Production, Sales,  and Calculated
    Release of CFC-11 and 12 through 1982;  Expanded  Data)  show
    a market share of open cell, aerosol, and  all other
    production to be 87 percent of total CFC-11 production.
    Thus, the U.S. aerosol share of total CFC  production is
    assumed to be 87 percent in 1958, declining smoothly to  54
    percent in 1970, where 54 percent is the aerosol proportion
    in 1970 described in footnote C.  Total CFC-11 production
    is based on U.S. ITC data.

b)  Estimates for 1958-1969:   based on the  assumption that
    CFC-12 aerosol production was 60 percent of total CFC-12
    production, as it was in 1970.

c)  Data for 1970-1977:  U.S. EPA.  Regulating
    Chlorofluorocarbon Emissions:  Effects  on  Chemical
    Production.  fEPA-560/12-80-0016) October  1980,  pp.  73,  74,
    80.  Reports production figures from pp. 73-74,  using
    aerosol/nonaerosol proportions from p.  80.

d)  Estimates for 1978 to 1981 computed by  subtracting usage  in
    non-aerosol applications from total CFC usage.  See  Tables
    A-l and A-3.

-------
                      A-7
                    TABLE A-3

    U.S. CFC  PRODUCTION DATA - NON-AEROSOLS
              (Millions of Kilograms)
YEAR
CFC-11
CFC-12
CFC-22  f/
CFC-113 h/
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
3.00 a/
4.30
6.10
8.80
13.40
17.00
19.90
24.90
27.10
31.20
37.50
46.80
50.80 c/
54.00
64.00
68.00
68.00
49.00
52.20
59.90
55.00 d/
66.30
62.20
64.30
63.70 e/
73.10
23.80 b/
28.50
30.20
31.50
37.70
39.50
41.40
49.20
52.00
56.20
59.10
66.80
68.00 c/
70.80
81.60
86.60
97.10
83.90
98.00
115.20
106.50 d/
128.00
128.00
142.00
117.00 e/
134.30
15.10 g/
16.60
18.20
20.50
22.30
24.50
26.80
29.10
31.80
35.50
39.10
42.70
45.50
50.90
55.90
61.80
64. 10
59.80
77.00
81.40
93.30
95.60
103.20
114.20
79.00
106.90
0.00
0.00
2.00
3.00
4.00
4.50
5.40
6.40
7.30
9.50
11.40
13.60
16.40
19.50
22. 70
26.80
29.00
31.00
37.10
45.20
51.00
58.80
45.90
48.20
50.00
52.70
    a/ See attached footnotes.

-------
                                   A-8
        TABLE A-3:   U.S. CFC PRODUCTION  DATA - NON-AEROSOLS
Description:
Footnotes:
Table A-3 presents time series data on U.S.  CFC production for
non-aerosol applications.   The table contains  actual  data for
CFC-11 and CFC-12 for the  years 1970-1977;  CFC-22  for the years
1960-1983; and CFC-113 for the years 1965-1974. The  remaining
estimates are based on assumptions detailed in the footnotes.

a)  Estimates for 1958-1969:   CFC-11 non-aerosols  are defined
    as CFC-11 total minus  CFC-11 aerosol (see  Table A-2).

b)  Estimates for 1958-1969:   based on the  assumption that
    CFC-12 nonaerosol production was 40 percent of total  CFC-12
    production, as it was  in 1970.

c)  Data for 1970-1977:  U.S.  EPA.  Regulating
    Chlorofluorocarbon Emissions:  Effects  on  Chemical
    Production.  (EPA-560/12-80-0016) October  1980, pp.  73,
    74, 80.  Reports production figures from pp.  73-74,  using
    aerosol/nonaerosol proportions from p.  80.

d)  Estimates for 1978-1981:   OECD.  Economic  Aspects of  CFC
    Emission Scenarios prepared by the Chemical Groups and
    Management Committee,  15 September 1982, p. 32.  Based on
    the assumption that the split between CFC-11 and  CFC-12 in
    these years was the same as it was in 1977.

e)  Estimates for 1981-1982:   based on the  assumption that
    production for aerosol applications is  zero, which makes
    nonaerosol production equal to total production.

f)  U.S. ITC.  Synthetic Organic Chemicals. Annual Series.

g)  Estimates for 1958-1959:   based on the  average annual
    percent change for CFC production for the  period  1960-1965.

h)  For 1958 to 1962, U.S. production is assumed to be 100
    percent of total world production reported in:  OECD, 1981,
    Summary of the Conclusions Regarding Scenarios of the Ad
    Hoc Meeting, ENV/CHEM/PJC/81.79, p. D.I.  U.S. production
    in  1963 was assumed to be 90 percent of the world total
    reported in the OECD document.  Data for  1964 to  1974 are
    from:  A.D. Little, Preliminary Economic  Impact Assessment
    of  Possible Regulatory Actions to Control  Emissions of
    Selected Halocarbons,  September 1976.  Data for 1975 to
    1979 are estimated by taking the portion  of world CFC-113
    production accounted for by the U.S. in 1974  (64.6 percent)
    and multiplying by the world production reported in the
    OECD document.  The years  1980 to  1983 are projections
    reported in U.S. EPA, Economic Implications of
    Regulating Chlorofluorocarbon Emissions from Nonaerosol
    Applications,  (EPA-560/12-80-001), October 1980,  pp.  67-68.

-------
                                       (ABLE A-M

                              NOMINAI  AND KfAL CIC PRICES
                                       (cents/kg)

YEAR
1958
1959
1960
1961
1962
1963
1961
1965
1966
1967
1968
1969
1970
1971
19/2
1973
1971
1975
1976
1977
1978
1979
1980
1981
1982
1983

crc-i
Norn i na 1
16

18
18
16
11
11
11
11
11
11
39
11
11
39
11
5?
71
71
71

86
92
101


.20 a/
NA
.80
.80
.20
.00
.00
.00
.06
.80
.80
.60
.80
.80
.60
.80
.80
.80
.80
.80
NA
.00 d/
.00
.00
NA
NA
1

Real
69

71
70
65
61
60
59
57
52
50
15
15
13
39
39
15
59
56
53

52
51
53


.96 b/
NA
.03
.39
.13
.39
.16
.17
.10
.87
.61
.63
.71
.51
.60
.53
.88
.16
.52
.11
NA
.63
.56
.30
NA
NA

CIC-1
Noinj na 1
66.
68.
66.
66.
63.
63.
63.
61.
61.
59.
57.
55.
57.
55.
52.
52.
68.
90.
90.
88.

91.
105.
119.


oo a/
20
00
00
80
80
80
60
60
10
20
00
20
00
80
80
20
20
20
00
NA
00 d/
00
00
NA
NA
2 CTC-22
Re_al
199.
100.
96.
95.
90.
89.
87.
82.
80.
75
69!
63.
62.
57.
52.
19.
59.
71.
68.
62.

5?.
58.
60.


91 b/
89
07
20
36
02
67
81
25
13
30
37
55
29
80
93
26
71
16
83
NA
52
85
98
NA
NA
Nomina 1
156
151
151
151
117
115
136
131
138
136
132
123
1 12
112
107
99
123
173
156
119

135
1 10
192


.20 a/
.80
.00
.00
.10
.20
.10
.20
.60
.10
.00
.20
.20
.20
.80
.00
.20
.80
.20
.60
NA
.00 d/
.00
.00
NA
NA
Real
236.52 b/
221 . 56
221.16
222. 13
208.75
202.60
187.11
180.17
180.56
172.53
159.92
111.95
122.69
116.86
107.80
93.62
107.06
138. 17
118.03
106.82
NA
82.61
95.28
98.39
NA
NA
                                                                             crc-m
lorn i na 1
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
88.0 c/
88.0
88.0
85.0
95.0
107.0
111.0
123.0
NA
13'4.0 d/
1 52 . 0
159.0
NA
NA
Rea 1
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
96.2 b/
91.7
88.0
80.1
82.5
85.0
86. 1
87.8
NA
82.0
85.2
81.5
NA
NA
a/ See attached footnotes.

NA = Not ava i(able.
                                      I'l I R  KIVIIW DRAM -- Do Not Quote  or  Citt:  ***

-------
                                   A-10
              TABLE A-4:   NOMINAL  AND REAL CFC PRICES
Description:
Footnotes:
Table A-4 presents time series  data on the  nominal  and  real
prices of CFC-11,  CFC-12,  CFC-22  and CFC-113.  The  primary
source of this data is the SRI  Chemical Economics Handbook.

a)  Data for 1958-1977:  SRI.   Chemical Economics Handbook.

b)  Real prices computed using  implicit GN'P deflator.

c)  Data for 1970-1977:  U.S. EPA.   Economic Implications of
    Regulating Chlorofluorocarbon Emissions from Nonaerosol
    Applications.   (EPA-560/12-80-001) October 1980, p.  79.

d)  1979-1982:  List prices from  the Chemical Marketing
    Reporter.

-------
                               A-ll



                            TABLE A-5

                   U.S.  ECONOMIC DATA a/

Year
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
GNP
(bill. 1972 $)
680.9
721.7
737.2
756.6
800.3
832.5
876.4
929.3
984.8
1011.4
1058.1
1087.6
1085.6
1122.4
1185.9
1254.3
1246.3
1231.6
1298.2
1369.7
1438.6
1479.4
1475.0
1513.8
1485.4
1534.8
Population
(1000s)
174,882
177,830
180,671
183,691
186,538
189,242
191,889
194,303
196,560
198,712
200,706
202,677
205,052
207,661
209,896
211,909
213,854
215,973
218,035
220,239
222,585
225,055
227,704
229,849
232,057
234,249
GNP Per Capita
(1972 $/person)
3,890
4,060
4,080
4,120
4,290
4,400
4,570
4,780
5,010
5,090
5,270
5,370
5,295
5,405
5,650
5,920
5,830
5,700
5,940
6,220
6,465
6,575
6,480
6,587
6,400
6,550
                                                     Annual Growth Rate
                                                     of GNP Per Capita
                                                            f Of \
                                                            C/oJ
                                                             4.4
                                                             0.4
                                                             1.0
                                                             4.1
                                                             2.6
                                                             3.9
                                                             4.6
                                                             4.8
                                                             1.6
                                                             3.5
                                                             1.9
                                                             -1.4
                                                             2.1
                                                             4.5
                                                             4.8
                                                             -1.5
                                                             -2.2
                                                             4.2
                                                             3.8
                                                             3.9
                                                             3.0
                                                             -2.7
                                                              1.6
                                                             -2.8
                                                             2.3
a/ See attached footnotes.

-------
                                  A-12
                  TABLE A-5:  U.S.  ECONOMIC  DATA
Description:    Table A-5 presents time series data on U.S.  GNP  (in billions
               of  1972 dollars) and population (in thousands)

Footnotes:      a)  Economic Report of the President,  1984.  pp. 222, 253

-------
                                                 TAEJI E  A-6

                                          OEC1)  CFG  PRODUCTION  DATA
                                              (Mill ions of  Kg)


YEAR J CFC- 1 1
1958
1959
1960
1961
1962
1963
196U
1965
1966
1967
1968
1969
1970
1971
1972
1973
197'1
1975
1976
1977
1978
1979
1980
1981
1982
29.50
35.60
1(9.70
60.50
78. 10
93.30
111.10
122.80
1 <4 1 . 00
159.80
183. 10
217.30
238. 10
263.20
306.90
3'l9. 10
369.70
3 1 '4 . 1 0
339.80
320.50
308.90
289.50
289.60
286.90
282.60
Tola 1 Product ion
CFC-12
a/ 73.UO a/
87.60
99 . 140
108.50
128. 10
1 '46. 140
170. 10
190. Ill
216.20
2U2.80
267.50
297. 30
321. 10
3'41.60
379.90
1423.30
l4'42.80
381 .00
1410.70
382.80
372.10
357.20
350.20
351.30
328.00
CFC-22
7.60 b/
11.30
12.20
12.20
15.50
17.60
22.1)0
25.10
31.60
37.140
45. 70
56.00
58.80
6'4 . 60
70.10
76.60
87.90
73.70
80. 70 c/
88.140
96 . 80
106.00
116.10
127.10
139.20
A

CFC- 1 1
25. 70 d/
30.70
'42. 18
50 . 52
63.UO
73.63
85.90
92 . 50
102. 70
1 T4.53
127.50
1't7. 46
159.33
168.81
191 .81
211.142
222.53
183.79
195. 10 f/
16U. 70
143.60
111. 60
105. 10
9*4.00
92.50

Assumpt ion 1
it?. 140 d/
50.60
57.50
62.70
7 'i.OO
84.60
98.30
1 09 . 90
1 25 . 00
T40. 30
15U.60
171.80
185.60
197.140
219.60
2'4'4 . 70
255.90
220.20







                                                                 Aerosol  Producti on
t ion 1
0 d/
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Assumption 2
314.140 e/
145.50
53.70
59.00
74.20
87.20
1014.80
115.30
132.00
150.140
168.80
187.00
201.70
2114.30
236.60
263.00
276.10
229.80
Assumpt i on 3
I4U.OO g/
52.60
59.60
65.10
76.90
87.80
102. 10
1 1 '4 . 1 0
129.70
U45.70
160.50
1 78.140
192.70
205.00
2214. 10
258.20
2118.00
201 .90
    * Estimates of the aerosoI/non-aerosoI  division of CFC-12 for 1958 to 1975 were performed using three
sets of assumptions.   See footnotes,  d,  e,  and  q for details.

-------
                                 TAB!E A-6 (continued)

                                OECD CK; PRODUCT I ON DATA
                                    (Mi I I ions of Kg)


YEAR
1958
1959
1 960
1961
1962
1963
1 964
1965
1966
1967
1968
I960
1970
19/1
972
973
974
9/5
976
977
978
979
1980
1981
1982
L 	 _____

crc- i i
3.80 d/
4.90
7.60
9.98
14. 70
19.67
25.20
30.30
38.30
'45.27
55.60
69. 8'.
78. 11
9'l.39
1 15.09
137.68
1 '1 7 . 1 /
130.31
144. 70
155.90
165.40
1 7 7 . 90
18 ..60
193.00
190.20


As sump i ion I
31 .00 d/
37.00
41 .90
45.80
54.10
61.80
71 .80
80.20
91 .20
102.50
1 12.90
125.50
135.50
144.20
160.30
1 /8.60
186.90
160.80







Non-Aeroso 1
C. C-
As sumption 2
39.00 e/
42. 10
45. 70
49.50
53.90
59.20
65.30
74.80
84.20
92.40
98. 70
1 10. 30
119.40
127.30
143.30
160. 30
166. 10
151 .20







Product ion
2»
Assumption 3
29.40 g/
35.00
39.80
43.40
51 .20
58.40
68.00
76.00
86.50
97. 10
107.00
1 18.90
128.40
136.60
155.80
165. 10
194.80
152.40










_
-
-
-
-
-
-
-
-
-








1 /3.50 f/
196. 70
208.40
214.20
212.20
223.80
212. 10


CFC-22
7.60 b
1 1 . 30
12.20
12.20
15.50
17.60
22.40
25.10
31 .60
37.40
45. 70
56.00
58.80
64 . 60
70. 10
76.60
87.90
73. 70
80. 70 c
88.40
96.80
106.00
116.10
127. 10
139.20
    a/ See attached footnotes.

    * Estimates of the aerosoI/non-aerosoI  division of CFC-I2  for I958  to  I975 were
performed using three sets of assumptions.   See  footnotes,  d,  e,  and  g  for details.

-------
                                   A-15
                TABLE A-6:   OECD CFC PRODUCTION DATA
Description:
Footnotes:
Table A-6 presents time series data on OECD CFC production for
1958 to 1982.  The principal source for these data are the
Chemical Manufacturers Association (CMA) estimates based on the
reports of 21 companies involved in CFC production throughout
the world.  The assumption underlying the estimates is that
production by CMA reporting companies is used almost entirely
in the OECD countries.  The procedures for dividing total
production of CFC-11 and CFC-12 into aerosol and nonaerosol use
are described in footnotes d, e and g.
a)
               b)
CMA.  Production, Sales, and Calculated Release of CFC-11
and CFC-1" Through 1982.  12 August 1983,  Schedules 2,  3.
    1958-197
    Worldwid
            OECD.  Fluorocarbons:   An Assessment of
               c)
 	        reduction, Use, and Environmental Issues.
1976, Scuedule 4.   CFC-22 data are end use only and do not
include CFC-22 produced as an intermediate.

Estimates for 1976-1982:   based on the assumption that the
percent change remains constant at 9.5 percent, which is
equal to the average of the annual percent changes over the
period 1970-1975.
               d)  CMA.   12 August 1983.   Estimates  for 1958-1975:   based on
                   the 1976 proportions  for aerosol/nonaerosol  reported in
                   schedules 5  and 6:

                   •   CFC-11 production for aerosol is based on CMA
                       estimates assuming that all of the open  cell,  aerosols,
                       and all  other production category was  used for aerosols
                       in 1958.   It is  also assumed  that in 1976, aerosols
                       make up  76 percent of this  category, based on 1976
                       proportions for  aerosols found in schedules  5 and 6.
                       The aerosol share of total  CFC-11 production in this
                       time period (1958-1976) is  thus 87 percent in 1958,
                       declining smoothly to 57 percent of total CFC-11 in
                       1976.  The non-aerosol share  of CFC-11 is assumed to  be
                       total production  minus aerosol production.

                   •   CFC-12 production for aerosol =57.8 percent of total
                       CFC-12 production for nonaerosol =42.2  percent.

               e)  CMA.   12 August 1983.   Estimates  for 1958-1975:   based on
                   the 1976 proportions  for aerosol/nonaerosol  reported in
                   schedules 5  and 6:

                   •   CFC-12 for aerosol = 82.8 percent of CFC-12  for
                       aerosol  + open cell + all other

-------
                    A-16
f)  CMA.   12 August 1983.   Estimates for 1976-1982:   based on
    assumption that aerosol sales = aerosol production.

g)  Estimates for 1958-1975:  based on the assumption that OECD
    division between aerosol and nonaerosol use will follow the
    U.S.  experience (until the time of the U.S. ban on aerosol
    production).

-------
                              A-17








                           TABLE A-7




                  OECD ECONOMIC DATA a/
                                                      Annual Growth Rate
GDP
YEAR (Billions of 1975 S
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
2150
2251
2372
2485
2641
2781
2931
3039
3213
3385
3501
3635
3830
4061
4094
4080
4284
4449
4618
4776
4835
.38
.52
.62
.74
.22
.35
.17
.67
.59
.03
.64
.82
.22
.50
.72
.64
.42
.49
.97
.08
1 T
Population
) (1000s)


656
664
672
679
686
693
699
706
714
723
730
737
744
750
756
762
768
774
780
NA
NA
,444
,384
,171
,749
,837
,529
,995
,919
,281
,180
,617
,699
,409
,860
,724
,476
,355
,275
,643
GDP/Population
(1975 S/person)
of GDP/Population
C°.)
NA
NA
3614.
3741.
3929.
4091.
4267.
4382.
4590.
4788.
4902.
5027.
5242.
5505.
5500.
5434.
5661.
5835.
6011.
6168.
6193.
3
4
4
7
6
9
9
4
3
5
4
6
6
6
8
6
5
4
9

3
5
4
4
2
4
4
2
2
4
5
-0
-1
4
3
3
9
0
NA
NA
--
. 5
.0
.1
.3
.7
.7
.3
.3
.6
.3
.0
.1
9
. L.
.2
.1
.0
.6
.4
a/ See attached footnotes.




NA = not  available.

-------
                                   A-18
                   TABLE A-7:  OECD ECONOMIC DATA
Description:    Table A-7  presents  time  series data on OECD GDP (measured at
               1975  exchange  rates  and  in billions of constant 1975 U.S.
               dollars),  population,  and GDP/population.  Data are only
               available  for  the period 1960 to  1980.

Footnotes:      a)  OECD.   National  Accounts:  Volume 1, Main Aggregates
                   1951-1980.   1982.

-------
                             A-19
                          TABLE A-8

             PROJECTIONS OF GNP AND  POPULATION
                   RELATIVE TO 1975  a/
OECD REGIONS

UNITED
POPULA
1.0000
1.1890
1.3170
1.3470
1.3664
1.3664

EASTERN
AND
POPULA
1.0000
1.1960
1.3080
1.3510
1.3720
1.3720

STATES
GNP
1.000
1.877
3.021
4.505
6.537
9.484

EUROPE
USSR
GNP
1.000
1.815
2.943
4.442
6.445
9.351
CANADA AND
WESTERN EUROPE
POPULA GNP
1.0000 1.000
1.1760 1.978
1.3030 3.534
1.3650 5.709
1.3872 8.283
1.3872 12.019
CENTRALLY PLANNED AND
CENTRALLY
PLANNED ASIA
POPULA GNP
1.0000 1.000
1.3700 2.665
1.6450 5.468
1.7700 10.335
1.8081 14.996
1.8081 21.758

OECD PACIFIC
POPULA GNP
1.0000 1.000
1.2010 2.701
1.2790 5.432
1.3050 9.121
1.3176 13.234
1.3176 19.202
MIDEAST REGIONS

MIDDLE EAST
POPULA GNP
1.0000 1.000
1.8030 3.649
2.4480 8.959
2.8470 18.044
2.9595 26.181
2.9595 37,987


YEAR
1975
2000
2025
2050 b/
2075
2100



YEAR
1975
2000
2025
2050
2075
2100
DEVELOPING COUNTRY REGIONS


AFRICA
POPULA
1.0000
1.7450
2.3610
2.7580
2.8807
2.8807
GNP
1.000
3.069
7.327
13.806
20.032
29.065
CENTRALLY
LATIN AMERICA
POPULA GNP
1.0000 1.000
1.7280 3.475
2.2980 9.005
2.6310 16.395
2.7144 23.788
2.7144 34.515
SOUTH AND
EAST ASIA
POPULA GNP
1.0000 1.000
1.6850 3.079
2.2260 7.169
2.5560 13.502
2.6504 19.591
2.6504 28.425


YEAR
1975
2000
2025
2050
2075
2100
                                                                b/
                                                                b/
a/ See  attached footnotes.

-------
                                  A-20
            TABLE A-8:
           PROJECTIONS OF GNP  AND POPULATION
           RELATIVE  TO 1975
Description:
Footnotes:
Table A-8 presents  projections of GNP and population for the
nine regions of the world:   1) U.S.; 2) Canada and Western
Europe;  3) OECD Pacific;  4)  Eastern Europe and USSR; 5)
Centrally Planned Asia; 6) the Middle East; 7) Africa; 8) Latin
America;  and 9) South  and East Asia.

a)  Institute for Energy  Analysis, Oak Ridge Associated
    Universities.   The values in the table are relative to
    1975.  For example, in the U.S., population is projected to
    be 1.3664 times the 1975 population by 2100.

b)  The  post-2050 GNP  annual growth rates were assumed to be
    1.5  percent in  all parts of the world.

-------
                                ANNEX  B

                     REGRESSION ANALYSIS RESULTS
    The equations used to project scenarios of CFC use were  estimated  using
least squares regression.  The equations were evaluated using  t-statistics and
adjusted R-squared values (R2).   Most importantly, the variable  coefficients
were examined to see whether their signs and sizes conformed to  theoretical
and intuitive expectations.

    The regression equations estimated are presented in Exhibit  B-l.   The
t-statistics were used to determine whether the coefficients are statistically
significant at the 5% level.  (The t-statistics are shown in parentheses below
their corresponding coefficients.)  The R2, also presented in  Exhibit  B-l,
measures the proportion of variation in the dependent variable explained by
the right hand side variable(s),  while controlling for the numbers  of
explanantory variables.

    In general,  the regression equations explain a large portion of the
variation in the dependent variables.  For example, in equation  1,  the
variation in U.S. GNP per person  explains 90 percent of the  variation  in the
U.S. use per person of CFC-11 in  aerosol applications.   The  coefficient on the
U.S. GNP per person variable implies that a one unit increase  in this  quantity
will correspond to a 1.2E-07 unit increase in CFC use per person (in millions
of kilograms).l
    1  The format "1.2E-07" shown in Exhibit  B-l  means  1.2  times  10  raised  to
the -07 power.

-------
                                                   EXHIBIr B-1

                                     FSllMAltl) RELATIONSHIPS BFTWFEN CFC USE
                                          AND FXPLANA10RY VARIABLES J./
            I)op_erideia_Va rj.a^tile

I.   U.S. CFC-1 I  aerosol use/person


2.   U.S. CFC-II  nonaerosol use/person
3.   U.S. CFC-I2 aerosol use/person




4.   U.S. CFC-I2 nonaerosol use/person


5.   U.S. CFC-22 use/person


6.   U.S. CFC-II3 use/person


7.   OECD-U.S. CFC-II aerosol  use/person


8.   OECD-U.S. CFC-II nonaerosol use/person


9.   OECD-U.S. CFC-12 aerosol  use/person


10.  OECD-U.S. CFC-12 nonaerosol use/person
Exf) lanatory Variables and Coefficients

-3.IE-OU + I.2E-07 x U.S. GNP/POP
(-6.il)     ( I I .76)

-I.7E-05 + 8.5E-08 x U.S. GNP/POP
(-0.2)     (9.0)
         + -I.7E-06 x Price of CFC-II
           (-6.U)

7./E-05 + I.2F-07 x U.S. GNP/POP
(O.U)     (»4.2)
        + -2.0E-06 Price of CFC-12
          (-3.0)

-7.'4F-Oi4 -i- 2.0E-07 x U.S. GNP/POP
(-'1.8)     (7.5)

-6.2F-OU + I.6E-07 x U.S. GNP/POP
(-5.0)     (7.3)

-3.7F-OU + 8.9E-08 x U.S. GNP/POP
(-10.3)    (12.8)

-2.9F-OU + I.IF-07 x OECD-U.S. GNP/POP
(-23.6)    (36.0)

-2.9E-OU + 9.2F-08 x OECD-U.S. GNP/POP
(-12.5)    (16.8)

-2.6F-OU + I.IE-07  x OECD-U.S. GNP/POP
(-20.I)    (31.U)

-6.0F-06 +A.3F-03^< OECD-U.S. GNP/POP
(-0.2)    \HJL2±^
         + -5.07E-07 Price of CFC-12
           (-U.7)
Adjusted R-Squared

       0.90


       0.97




       0.98




       0.89


       0.88


       0.89


       0.99


       0.9U


       0.99


       0.98
    J/ CFC use/person  in thousands of kilograms per person.  U.S. GNP/POP  is  in  1972 dollars  per  person.
OFCD-U.S. GNP/POP  i"  1975 dollars per person.  Prices of CFC-II and CFC-12 expressed as an  index  with  1972  =  100.

-------
                               ANNEX C

                   THE RELATIONSHIPS AMONG  CFC  USE,
                   CFC EMISSIONS, AND  BANKED  CFCs


    Annual CFC use and emissions  are not equivalent.   Some  portion  of  the  use
may be released immediately (e.g.,  emissions  from solvent use).   However,  a
large portion may remain in the product  for many  years (e.g.,  the refrigerant
trapped in the appliance).   The CFCs remaining in products  are referred  to as
"banked."  Banked CFCs are  emitted  slowly over time (e.g.,  when a refrigerator
compressor is repaired or disposed  of,  the CFCs in  the refrigerator may  be
released).  Exhibit C-l displays  the manner in which CFC use,  emissions,  and
the CFC bank interact and are treated in this analysis.

    In year 1 of the analysis (e.g., 1985) there  is an existing amount of
banked CFCs from past uses  of products  containing these chemicals.   These  CFCs
contribute to emissions in  year 1.   Also in year  1, there  is  some level  of CFC
use.  Some portion of these CFCs  are emitted  promptly, and  become part of  the
year 1 emissions.  The remaining portion is banked, and becomes part of  the
bank in year 2.  These banked CFCs  are  then slowly  emitted  from year 2
onward.  This procedure repeats year after year.

    From the schematic in Exhibit C-l it is clear that the  following three
components must be specified in order to project  scenarios  of emissions:

        •   the future rate of CFC  use;

        •   current reservoir of banked CFCs; and

        •   the rate of prompt emissions directly from use  (e.g.,
            from CFC use as aerosol propellants)  and the rate of
            emissions from the banked CFCs (e.g., the rate  of
            releases of CFCs trapped in appliances).

    The future rates of use are developed as  scenarios.  Estimates  of the
current CFC bank and the rates of emissions  from use and the  bank were
developed.  The total world quantity of currently banked CFC-11 and CFC-12 was
estimated as 768.9 and 880.7 million kilograms respectively.1  No estimate
was available for the amount of CFC-22  banked.  Because CFC-113 is  only  used
in a prompt emitting applications,  there is no CFC-113 bank.

    The release rates from the existing CFC-11 and  CFC-12  banks are displayed
in Exhibit C-2.  For example, the exhibit shows that over  the next  ten years,
27.5 percent of the banked CFC-11 is expected to be released.  Of note is that
a fairly  large fraction of CFC-11 (22.8 percent)  is expected  to take a very
long time to be released.  These CFCs are banked in insulating foams.
      "Production, Sales ...", CMA, ojg. cit.  These data are for 1982.

-------
                    C-2
                 EXHIBIT C-l

SCHEMATIC  OF CFC  USE, EMISSIONS,  AND BANKS
                    EMISSIONS:
                      YEAR 1
                                         |  BANK:
                                        1  YEAR 1
   USE:
  YEAR 2
!   USE:
!  YEAR  3
     EMISSIONS:
       YEAR 2
->• ! EMISSIONS:  j
    I   YEAR 3   ;
                                           BANK:
                                           YEAR 2

-------
                                  C-3
                              EXHIBIT C-2

                    EMISSIONS FROM EXISTING BANKS
                                (percentage)
                     Years  from Now     CFC-11     CFC-12

                          1-10            27.5       85.0
                         11-20            27.0        6.3
                         21-30             6.2        7.5
                         31-40             3.9        0.1
                         41-50             3.8        0.1
                         51-60             3.3        0.1
                         61-70             2.8        0.1
                         71-80             2.7        0.1
                         81-150           22.8        0.7
                         Total           100.0       100.0
                     Source:   See  text.
    Exhibit C-3 shows  the rate of  release  after  the  use  of  CFCs  in  non-aerosol
applications.2  For example,  66.4  percent  of the use of  CFC-11  in
non-aerosol applications is  estimated to be  released promptly,  i.e.,  in  the
year of use (the exhibit shows this  66.4 percent being released  zero  years
after use).  Again, CFC-11 shows a substantial  fraction  being banked  over a
long period of time.

    These release rates were derived by:  (1)  identifying the mix of
applications of each CFC (i.e., the  fraction going to air conditioners,  foams,
refrigerators, etc.);  (2) identifying the  rate  of emissions from each of these
applications; and (3)  weighting the  rates  of emissions by the mix of  the
applications to estimate release rates for the  CFC type.  The data  describing
the rates of release by application  and the  mix of applications  are presented
in Exhibit C-4.  These release rate  estimates were developed from Environment
Committee Report on Chlorofluorocarbons by OECD (1982).   The mix of uses is
for the U.S. in 1976 as reported  in  Economic Implications of Regulating
Chlorofluorocarbon Emissions from  Nonaerosol Applications,  by The Rand
Corporation (June 1980).  The emissions rates  reported in Exhibits  3  and 4
were used for all parts of the world, throughout the entire period  examined.
    2 The release rate for the aerosol applications of CFC-11 and CFC-12 as
well as all the use of CFC-113 is assumed to be 100 percent in the year of use.

-------
                         C-4
                     EXHIBIT C-3

                 EMISSIONS FROM USE
                       (percentage)
Years After
Use
0
1
11
21
31
41
51
61

-10
-20
-30
-40
-50
-60
-70
71-80
81
-150
CFC-11
Non-Aerosol
66,
7,
7 ,
3,
2.
2,
2.
1
1
4
,4
.6
.2
.6
.5
,4
,1
.8
.7
.7
CFC-
12
Non-Aerosol
45
46
3
4
0
0
0
0
0
0
.0
.5
.7
.4
.1
.1
.1
.1
.0
.0
CFC-22
Non-Aerosol
45,
23,
23,
7
0
0
0
0
0
0
.0
.9
.4
.7
.0
.0
.0
.0
.0
.0
  Total            100.0           100.0           100.0
Source:  See text.

-------
                                                                    RXHIBIT C-4

                                                     PROMPT  VS.  BANKED  EMISSION  DATA  BY  END  USE

CPC
Product
CPC- 11



CFC-12











CFC-22



CPC- 113
Principal End Use
and Percent of
Product Use
Flexible Foam: 34%
Rigid Foams
Urethane: 35%
Nonurethane: 2%
Chillers: 8%
Other: 20%
Rigid Poams
Urethane: 1%


Nonurethane: 11%
MACS2: 48%
Chillers: 3%
H one Re f r I g . &
Freezer: 3%
Retail Pood
Refrlg. : 6%
Other: 28%
Chillers: 3%
Retail Pood
Refrlg.: 1%
Other: 96%
Solvents: 100%
Emissions
%
Prompt
100%
26.5
100.0
2.0
100. 0

26.5


100.0
11.0
2.0
7.0

3.0

100.0
2.0
3.0

100.0
100. 0
%
Banked
0%
73.5
0
98.0
0

73.5


n
89.0
98.0
93.0

97.0

0
98.0
97.0

0
0
Ypar of Release of Banked CFCs After Initial Use qreater
Life of 31- 41- 51- 61- 71- 81- 91- than
End use 1-10 11-20 21-30 40 50 t>0 70 80 90 100 100
1/2 life of 11% 10% 9% 7% 7% 6% 5% 5% 4% 4% 32%
emissions
= 60 year s

20 years 47.5 (46.5)1 47.5 (46.5) 5.0


1/2 life of 11 10 97765544 32
emissions
= 60 years

7 years 100 ( 89)
20 years 47.5 (46.5) 47.5 (46.5) 5.0
20 years 16.0 (14.5) 16.0 (14.5) 69.0 (64)

20 years 31.0 (30) 31.0 (30) 38.0 (37)

—
20 years 47.5 (46.5) 47.5 (46.5) 5.0
20 years 31.0 (30) 31.0 (30) 38.0 (37)

— —
—
    1  Nuntoers in parentheses refer to the rate of  release of  total  CPCs emitted (i.e.  Prompt  and hanked emissions).

    2  Mobile Air Conditioners.
Source:  ICF analysis of data in:  Environment Committee Report on Chlorofluorocarbons,  OECD,  1982,  and Economic Implications of Regulating
         Chlorofluorocarbon Emissions from Non-Aerosol  Applications,  The Rand Corporation,  June 1980.

-------
                                ANNEX  D

                      SCENARIOS BY TYPE OF  CFC
    This annex presents  a series  of  tables  that  describe  the  potential  future
use and emission of CFC-11,  CFC-12,  CFC-22,  and  CFC-113 in  five  scenarios:
Limits to Growth;  Low; Medium;  High;  and No  Limits  to  Growth.  These  estimates
are based on the assumption  that  current aerosol use restrictions  remain  in
force.

    For each CFC type in each scenario the  following information is provided
for the world total:

        •   annual use and the annual percent  growth in use;

        •   total  annual emissions;

        •   portions  of  emissions that come:

                directly from use

                from  the banked CFCs  created due to projected use
                (referred to as the  "simulated use  bank"  and
                labelled "UBANK")

                from  the banked CFCs  that already exist today
                (referred to as the  "other  bank" and labelled
                "OBANK");

        •   total  banked CFCs,  labelled "TBANK;"

        •   banked CFCs  from simulated future  use,  labelled
            "UBANK;"  and

        •   banked CFCs  that already exist  today, labelled  "OBANK."

-------
RESULTS FOR LIMITS TO GROWTH SCENARIO

-------
   WOR10 IOTAI:  ClC-11
COMI'ONI Nl S  I NCI IJDI I)  :
 UNI III) SIAIIS  NUN-AI KOSOI  I)S( 01  CIC-11:  IINIAK MODI I  2
 ON I IN) SIAIIS  Al KOSOI   USI  Of CIC-11:   I  I Nl AR  MODI I   +  AlROSOI RE SI  = I). 5
 IIC  NON-AI ROSOI  USC Ol  CfC-11:   I I Nl AR MODll  ?
 IIC  Al ROSOI USE  01  CSC-ll:    MNIAR  MODI L 2  +  UIKR1NI  Al ROSOI S  RE SIR.
 OI Cl) - US - I I C  NON-AI ROSOI   USI  01  CIC-11:   MNIAR  MODll  2
 01 Cl) - US - I 1C  Al ROSOt  USI   Ol CIC-11:  I  INI AH MODll  2
 NON-OI CD NON-AI KOSOI  USI  01   CIC-11:   I OG I  I / I'OI'UI A I  I ON MODE I
 NON-01 CO AIKOSOI  USI  Ol  CIC-11:   I 00 I  I / I'OI'UI A I I ON MODll
 EMISSION EKOM  WORI D HANK 01   CEC-11:   BISI  I SI I MA IE   -  NO KISIRICIIONS
  (All  I SI IMAMS IN Ml I I IONS 01  KIIOGRAMS)
% ANNUAI
GROW III
1985
1991)
1995
2IIIIO
'Iin5
>(} 10
•015
'O2O
'0. '5
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'II 15
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'O'l5
2(151)
MI55
2060
2065
'070
'0/5
O
3
3
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1
1
1
1
1
1
1
2
2
2
1
1
1
1
1
0
3
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(1
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8
9
9
9
9
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6
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1 196
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EMI SSIONS
IOIAI
29'l
351
'11 2
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517
5/2
631
696
7 /()
8 '1 8
935
1013
1 1 '1 3
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1 756
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d
/
9
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0
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9
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?
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9
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6
IMI SSIONS
1 ROM U'
2/3
322
3/ 5
'|27
'168
513
562
618
680
/'I6
82 1
906
1003
1112
1203
1303
I'll 3
1533
1661
MISSIONS 1
MISSIONS
il (ROM UliANK (ROM OI1ANK
5
(1
1
/
3
n
6
0
•t
1
1
6
0
;j
0
'i
6
2
6
O
8
18
10
'I'l
5'l
65
75
86
98
1 10
1 2 'I
1 18
153
169
186
20'4
221
238
0
•>
8
6
0
5
(>
9
8
5
9
1
'I
6
9
/
0
0
6
21 .
21 .
20.
20.
'1.
l\ .
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
1
1
8
8
8
8
0
0
9
9
5
5
2
2
1
1
5
5
5
IBANK
795
1056
1352
16/7
2039
?'l'l9
28/3
3318
3/85
'12/5
'1791
5338
5920
65'l't
7192
7852
8530
9232
9966
lj
8
3
5
2
6
3
2
2
6
7
5
9
9
3
8
3
2
5
UliANK
68
'l 3 5
836
1265
1698
2133
25/7
3037
3518
'1023
'4553
5113
5 70 7
63'l2
7000
76/1
8160
907I|
9821
8
9
14
3
9
1
1
0
9
8
8
3
6
'I
1^
3
0
U
2
OBANK
726.
620.
515.
1412.
3140.
316.
296.
281 .
266.
251.
237.
225.
213.
202.
191 .
181 .
170.
157.
1U5.
6
9
9
1
3
5
2
2
3
7
9
2
3
5
9
5
3
8
3
ANNUAI  AVI RAGE  GKOW1II  RAIIS:

              2.011        2.010
2.09
-------
   WORl0  IOFAI :  CFC-12
COMI'ONI NIS  I NCI UOI I) :
 UN I  I CD SI AllS NON-AIROSOt USE Of CIC-12:   IINIAK MOOT I  2
 UNITED SIAIIS Al ROSOl  US( OK CIC-12:   IINIAR MODI 1. + Al ROSl RFS1  -  '(. 5
 tlC NON-ALROSOL  USF 01  CIC-1?:  I INtAR  MODEL 2
 TIC AEROSOL USE  OE CFO-12:  IINIAR MODEL  2 + CUKRtNl Al ROSOL  RESER.
 OICD  - US  - EEC  NON-AI ROSOl  USE OF CFC-1?:   I IMIAR MODI I. 2
 01 CO  - US  - EEC  AEROSOl  USE OE CEC-12:   I INEAK MODE I 2
 NON-OECD NON-AEROSOL USE Ol  CIC-12:   I 00 I I / POI'UI Al I ON MODEL
 NON-OE CD Al ROSOl  US!  Of  CEC-12:  I 00 I 1 / POI'Ul A I I ON MODI I
 EMISSIONS  FROM WOULD HANK OF CEC-12:   EHS1  ESIIMAIE - NO RESIRICIIONS
  (AIL ESI I MATES IN MILLIONS OF  KILOGRAMS)
ANNUAl
GROW III
0.0
2.9
2.7
2.5















.6
.6
.6
.6
.6
. 5

. 5
.5
. 5
.0
. 0
.0
.0
.0
u s
'160
535
61 5
696
75')
81 7
885
959
1039
1 120
1208
1 !03
11)06
1516

1681

1860
195't
I
2
1
5
2
2
0
1
6
6
6
1

2

3
I)

EMISSIONS EMISSIONS (MISSIONS (MISSIONS
10 (Al (ROM USl FROM UHANK E ROM OHANK
M09.9 335. 1 0.0 7').9
56/!/ 1)36.9 125.3 5.5
650.? ')92. 7 151.9 5.5
720
790
855
929
1007
1087
11 73
1266
1365
l')/3
1558
16') 3
1 730
1821
1911)
.2
.0
.8
.0
.8
.9
. 7
.2
.8
.2
_ ?
.8
.8
. 1
.2
535
582
633
688
7'l8
809
8/1)
9')5
1021
1 102
1161
1223
1287
1353
1U22
7
>j
3
6
6
;>
'j
1
1
9
9
l)
l|
/
2
1 //
200
222
2')0
259
2/8
299
321
3')')
3/0
396
<420
'l')3
1)67
1.91
9
9
')
J
1
6
1
0
/
2
2
i
3
3
9
6.6
6.6
0.
0.
0.
0.
0.
0. 1
0. 1
0. 1
0. 1
I). 1
0. 1
0. 1
0. 1
IBANK
856. 1
1016.6
1126.6
1357.9
1 552 .
1 700.
1836.
1985.
2138.
2299.
2'469.
2651.
28'! /.
305 /.
3259.
3')') 9 .
36MO.
3835.
14035.
14
5
7
2
7
3
5
6
1
2
5
5
1)
i)
1
UBANK
125.2
659.9
1005.6
1 26
-------
    WORI U IOFAI :  Cf O22
COMI'OW NtS  INCIUDM) :
 UNI IIU SIA1IS  101AL USL Of  GIC-22:   I INI AH MODI I  2
 NON-US 01 CD USt  01  CIC-22:   IINEAK MODI I  2 DtKIVH)  I I
'(
2
'1
0
'£
1
O
8
2
0
O
?
6
MISSIONS f
MISSIONS EMISSIONS
1 HOM USI fKOM UHANK f ROM OBANK
33
'|2
01
60
6'l
67
71
76'
80
86
91
9 7
101
10
16
22
29
30
l'(2
5
i
'I
6
1
9
<•)
;>
9
1
6
•j
9
1
1
9
2
/
3
O
9
22
16
0 1
63
73
79
80
91
96
102
109
1 16
123
1 M
1 58
1 '1 6
1 O'l .
O
8
0
6
O
6
't
9
0
0
0
6
1
1
0
1
«
')
!
0.
0.
O.
0.
0.
o.
0.
0.
0.
0.
o.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
o
0
0
0
o
0
0
0
0
0
o
0
0
0
IBANK
l|0.
2'(8.
'lOO .
600 .
801 .
909 .
990.
1008.
1 1 2'l .
1 1 9'l .
1269.
I3'|9.
Hi 36.
1 029 .
1620.
1 720.
1816.
1912.
2010.
7
'j
fj
3
l|
')
1
l\
9
2
0
7
'j
^
1
6
2
6
3
UBANk
'10
2'(8
'( 0 0
600
801
909
990
1008
1 1 2'l
1 19'l
1 269
1.3'l9
Hi 3 6
1029
1620
1 720
1816
1912.
2010.
7
0
•y
3
'1
0
7
il
9
2
0
7
0
0
1
6
2
6
3
OBANK
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
. 0
.0
.0
.0
ANNUAL  AVI RAC[ (iKOWIII KAIIS:

               1.6514        1.628
                                                                               0.0
                                                                                                                      0.0

-------
   WORI D  101AL:  CFC-113
COMPONI NIS  I NCI UDI I) :
 UNI II I) STA1ES FOIAl US! Ol  CIC-113:   IINIAK MODI I  ?
 NON-US 01 CD USf  01  CFC-113:   MNFAR  MODH  2 DtKIVIl)  I KOM U.S. USE
 NON-OICO NON-AEKOSOI. USE.  OF  CtC-IU:   LOG I'l /I'OI'lll A? I ON MOOtl
  ( Al L  LSII MATES IN Ml I I IONS  OF  K11OGRAMS)
ANNUAI
GROW 1 M
0.0
'1.5
3. /
3.2











. 1
. 1
. 1
. 1





! i
.0
0.9
0.9
0.9
0.8
u s
1?.
92
1 12
13?
139
I'l 6
1'j'l
163
1 1?
182
191
20'4
216
??tt
?l|0
251
263
275
28 /
LMISSIONS EMISSIONS (MISSIONS EMISSIONS
E 101 Al FKOM US! 1 ROM UBANK FROM OBANK
.2
. 1
. 1
.3
.3
.9
.8
.3
. 3
.3
. 0
.2
.2
.9
.3
.9
.6
.5
.5
I?.
9?.
1 12.
13?.
139.
1«l6.
15'l.
163.
1 12.
18?.
193.
20'» .
?16.
2?8.
?'|U.
251.
?63.
2/5.
287.
2
1
1
3
3
9
8
3
3
3
0
2
2
9
3
9
6
5
5
/?
9?
1 1?
13?
139
I'l6
1'j'l
163
172
182
193
20'»
216
2?8
?'lO
?")!
263
?75
287
2
1
1
1
3
9
8
3
3
3
0
2
2
9
{
9
6
')
•>
0.
0.
().
0.
0.
0.
0.
0.
0.
0.
o.
0.
0.
0.
0.
o.
0.
0.
0.
0
0
1)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
TBANK
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
UBANK
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
(I
0
0
0
.0
.0
.0
.0
. 0
.0
.0
. 0
.0
.0
. 0
.0
.0
.0
.0
.0
.0
.0
.0
OBANK
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
  1985
  1990
  1995
  21)00
  2O05
  2010
  2015
  2020
  2025
  2030
  2(1 !5
  20'U)
  20'l5
  20SO
  20'; 5
  2060
  2065
  211/0
  ?0/5
ANNUAL AVI RAGE GROWTH RAMS:

              1 . 554        1 . 51
                                       1 . 5't 7
                                                                0.0
                                                                             0.0
                                                                                          0.0
                                                                                                       0.0
                                                                                                                   0.0

-------
RESULTS FOR LOW SCENARIO

-------
WORLD TOTAL: CFC-11
COMPONINIS  INCLUDED  :
 UNITED STAIES NON-AEROSOL  USE  OF CFC-11:   LINIAR  MOOR  2
 UNIIH) SIATES AEROSOL  USE  OE CFC-11:  LINIAR  MODFI  +  AlROSOl  RES I  = 4.5
 EEC NON-AEROSOL USE OE CEC-11:   LINEAR MODEL  2
 EEC AEROSOL USE OF CFC-11:   LINEAR MODEL 2  +  CUKRFNI  Al ROSOLS RESTR.
 OECD - US - EEC NON-AIROSOl  USE  OE CFC-11:  LINIAR  MODI L  2
 OECO - US - EEC Al ROSOl  USL  OF CIC-11:   MNEAR  MODF I  2
 NON-OECD NON-AEROSOL USE 01  CFC-11:   I OCI I/POPUI AT I ON MODFI
 NON-OFCD AEROSOL USE 01  CEC-11:  LOCI f/POI'ULAl I ON MODII
 EMISSION FROM WORlD BANK Of  CEC-11:   BEST  ESTIMATE  -  NO RFSIRIC1IONS
  (AIL ESTIMATES  IN MILLIONS  OF  KILOGRAMS)
% ANNUAL
GROW 1 H
1985
1 990
1995
2000

2O10
2015
2020
2025
2O 30

2O'|0
2O'45
2O 50
2055
2060
2O65
20/0
20/5
0

3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
1
. 0
. 3
.8
.5
.0
.9
.8
. 7
. 7
.2
.2
.2
.2
. 1
.14
. 3
. 1
.0
.8
U S
'10(1
'199
60 /

8<4'l
9/6
1 122

1 '4 / 1
16'4?
1832
20'43
2276
2533
2855
3199
356 i
3939
U322
E
j
.2
. 0
.5
.8
.3
.5
.3
.'4
.9
.7
.2

!2
.?.
. 7
.0
.5
.7
EMISSIONS
TOTAL
336
1421
515

715
83»4
965
1113
1281
lt'42
1619
1816
203'4
2275
2568
288'4
3221
35/1
3931
.5
. 0
.'4
.2
.9
.5
.6
.7
.14
.0
.5
.7
. 7
.0
.4
.9
. 7
.9
.0
EMISSIONS t
MISSIONS EMISSIONS
(ROM USf (ROM UBANK FROM OBANK
315
389
'4/0
559
651
/52
866
9 9 '4
1 I'lO
12/7
1'429
1600
1/89
1999
2259
2539
283'4
31 '41
3<453
. 3
. 1
. ;>
.9
.3
. 7
2
. >)
.H
. ?
]
. o
/
1
.9
.3
/
. 3
.5
0
10
2'4
'lO
59
77
96
1 16
138
161
187
2I<4
2'42
2/3
306
3'(3
38't
'428
t/5
. 0
.8
.'4
.6
.8
. 1
. J
.2
. 1
.9
.3
. y
. 8
.2
.5
.5
.5
. 1
.0
21
21
20
20
*4
It
3
3
2
2
2
2
2
2
2
2
2
2
2
. 1
. 1
.8
.8
.8
.8
.0
. 0
.9
.9
.5
.5
.2
.2
. 1
. 1
.5
.5
.5
TBANK
812.
11/5.
1606.
2103.
2682.
3365.
'4117.
'49'49.
5863.
68<46.
7886.
8992.
10169.
1 1'427.
1280'4.
1'4322.
1 59 76 .
1/762.
19673.
0
5
8
2
9
7
8
0
7
2
7
2
7
5
1
3
7
7
9
UBANK
85.14
55'4.6
1090.9
1691 . 1
23'l2.6
30149.2
3821.6
'4667.9
5597.14
659U.5
/6'48.8
8/6/.0
9956. tl
1 122U.9
12612.2
1 '4 1'(0.8
15806. «t
1/6014.9
19528.7
ANNUAL AVERAGE GROWTH  KATFS:

             2.680        2.6/8
                                                                         OBANK
                                                                         726.6
                                                                         620.9
                                                                         515.9

                                                                         3<4o!3
                                                                         316.5
                                                                         296.2
                                                                         281 .2
                                                                         266.3
                                                                         251 .7
                                                                         237.9
                                                                         225.2
                                                                         213.3
                                                                         202.
                                                                         191
                                                                         181
                                                                         170.
                                                                         157.8
                                                                         1<45.3
                                                                                                                  .5
                                                                                                                  .9
                                                                                                                  .5
                                                                                                                  .3
2.769
2.695
                        0.0
                                   -2.3'42
                                                 3.605
                                                             6.222
                                                                        -1.773

-------
WORLD TOTAL: CFC-12
COMPONENTS  INCIUDfl)  :
 UNI HI) STAILS NON-AtROSOl  USF OT CfC-1?:  I  INIAR MODf I  2
 UNIIEl) SIAIES AEROSOl USE  OJ CEC-12:   I INIAR MODEL +  ALROSL  REST  =  4.5
 EEC NON-AEROSOL USE Of CFC-12:   IINEAR  MODEL 2
 EEC AEROSOL USE OF CFC-12:   LINEAR MODEL 2  + CURRENI  AEROSOL RESTR.
 OECD - US - EEC NON-AIROSOL  USE  OF CFC-12:  I INIAR MODI L  2
 OfCO - US - EEC AEROSOL  USl  OF CFC-12:  I  INfAK MOOfl  ?
 NON-OFCD NON-AEROSOL USE 01  CfC-12:   LOG I 1/POI'UI AT I ON MODEl
 NON-OECD AEROSOL USE OT  CIC-12:  I OG I T/POI'W Al I ON MOON.
 EMISSIONS FROM WOULD BANK  OF CfC-12:   BESF  ESIIMAIE - NO  RESTRICTIONS
  (AIL ESTIMATES  IN MILLIONS OF  KILOGRAMS)
ANNUAI
GROWTH
0.0
3.9
3.6
3.3
2. 7
2.6
2.5
2.5
2.4
1.8
1 .8







.7
. 7
.6
.9
. 7
.6
.5
1.4
USE
545.3
666 . 5
/99.8
946 . 5
1083.3
123J.6
1399.0
1581 . 1
1/81.6
1 952 . 1
2133.4
2325.8
2529.0
2/42.8
3D13.0
3292.5
3579.7
3872.5
4168.5
EMISSIONS
TOTAL
457.2
612.0
724.8
866 . 9
1010.0
1163.5
1323.7
1500.9
1695
1871
2052
2242
2442
2652
2900
3167
3447
3734
4026
.5
.0
.6
.2
.3
. 7
.7
.0
.3
.6
.8
EMISSIONS (MISSIONS EMISSIONS
TROM USl FROM UBANK FROM OBANK
382.4 0.0 74.9
461.2 75.9 74.9
548.9 170.3 5.5
646.7 214.6 5.5
742.0 261.4 6.6
847.8 309. 1 6.6
965.0 358.6 0.1
1095.0 405.8 0.1
1238
1362
1493
1633
1/81
1937
2125
2319
2519
2723
2929
y
1
b
•t
6
6
1
4
?
O
1
456
508
558
608
660
715
7/5
847
928
1011
1097
.5
.8
.9
.5
.6
.0
.5
.5
.0
.5
.6
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
1
1
1
1
1
1
1
1
1
1
1
IBANK
893.9
1239.5
1510.5
1899.6
2278.3
2633.8
2993.6
3384.3
3802.
4216.
4619.
5031 .
5458.
5902.
6423.
7028.
76/7.
8356.
9058.
6
6
4
6
9
7
4
5
4
7
5
UBANK
162.9
882.8
1389.5
1806.3
2214.9
2603.4
2983.2
3374.4
3/93.1
4207.5
4610.7
5023.4
5451.1
5895.4
6416.5
7022.0
76/1.4
8351.2
9053.4
  1985
  1990
  1995
  2000
  2005
  2010
  2015
  2020
  2025
  2030
  2055
  2040
  2045
  2050
  2055
  2060
  2065
  2070
  2075
ANNUAI  AVERAGE GROWTH RATES:

             2.288       2.286
2.447
            2.288
                        0.0
-7.221
2.607
4.565
                                                                         OBANK
                                                                         731.0
                                                                         356.7
                                                                         121 .0
                                                                          93.3
                                                                          63.4
                                                                          30.4
                                                                          10.4
                                                                          10.0
                                                                           9.5
                                                                           9. 1
                                                                           8.6
                                                                           8.2
                                                                           7.7
                                                                           7.3
                                                                           6.9
                                                                           6.4
                                                                           6.0
                                                                           5.5
                                                                           5.1
-5.366

-------
   WORI0 TOTAl:  CFC-22
COMI'ONI N ! S  I NCI UOEI) :
 UNIIED  STAILS  TOTAl  USI  Of  CIC-22:   IINIAK MOON  2
 NON-US  OECO  USE  01  CFC-22:   UNLAR MODtl  2 I)E in VI D I KOM U.S.  USE
 NON-OECD NON-AEKOSOI  USE Of  CFC-22:   LOGI T/POI'Ul A[ ION MOOt L
  (AIL ESTIMATES  IN Ml I LIONS OF KILOGRAMS)
  1985
  1 990
  1995
  2000
  2005
  2010
  2015
  2020
  2025
  2030
  20.55
  20'IO
  20')0
  2055
  2060
  2065
  20/0
  20/5
ANNUAL
GROW I II
   0.0
   5. 1
   '1.3
   3.8
   2.U
   2.3
   2.2
   2. 1
   2.0
    .5
     .3
     . 3
     .9
     .8
     . /
     .6
     .5
EMISSIONS EMISSIONS EMISSIONS EMISSIONS
USE
109.5
1 l| 3 . 7
180.2
218.9
21)6.9
276. 7
308.6
5142.8
579.5
'109 . 1
i|39. 7
'(71.5
50'l . 5
53H.6
59'i . 9
652 . 3
no. /
769 . 8
829 . 3
TOIAl
'49
79
11<4
155
195
229
265
298
332
36')
395
1)28
'460
»493
537
585
637
691
7t«9
. 3
.14
. 7
.5
.5
.6
. 3
. 5
.8
.2
.9
.0
.5
.5
.8
. 7
. 1
.9
.2
H
-------
    WORl 0 IOIAI : CfC-1 1 5
COMI'ONI NIS I NCI Ul)[ I)  :
 UNIHDSIAIIS I01AI  USE  0(  CIC-IU:   I I Nl AH  MODI I  2
 NON-US 01 CO USt  01  CH> 113:  LINIAR MODI I  7  UIKIVIO H(OM U S
 NON-OhCD NON-AF.KOSOL  USE OF CfC-113:   LOG II/POI'UI AT I ON MODf L
   (All  t'SIIMAIES  IN Ml I I IONS 01  KI IOGRAMS)
% ANNUAI
GKOWIII
1985 0.0
1 990 5 . 5
1995 '1.6
2OOO 3.9
?005 2. '4
2010 2.3
2(115 2.2
21)20 2. 1
2(>;"> 2.0
20 10
20 i 5
20'|0
2O'|5
2(l')0
2 (155
2060
2065
20/0
20/5
.5
.'1
.3
. 3
. 2
.9
.8
. /
.6
• 'I
U S
9 »
125
150
33 /
363
)90
'll/
'i'l5
'!/ i
5? I
57 i
6 2 'l
6/6
72H
F
. 1
9
0
8
3
6
8
6
1
3
2
9
'1
9
9
5
"4
FMI SSIONS EMISSIONS (MISSIONS EMISSIONS
IOIAI (ROM USt (ROM UBANK FROM OBANK
93.2 93.2 0.0 0.0
125. 1 125. 1 0.0 0.0
158.9 158.9 0.0 O.O
19'l. / 19'l. / O.o O.o
220.0 220.0 0.0 0.0
2'46.8 2'l6.H O.I) 0.0
2/5.3 2 1'j. j O.O 0.0
305 . 6 305 . 6 0 o o 0
337
363
390
'41 /
'1 '4 5
*4/3
523
5/3
62'i
6/6
728
8
6
1
3
2
9
<4
9
9
5
*4
337
363
390
'117
*I'I5
'1/3
523
5/3
62'l
676
728
H
6
1
3
2
<)
'1
9
9
V
'4
0
0
0
0
O
0
0
0
0
0
0
1)
I)
1)
(1
II
I)
0
0
1)
0
0
0.
0.
0.
0.
o.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
o
0
0
0
0
IBANK
0.0
0.0
o.o
o.o
0.0
0.0
0.0
0.0
o.
o.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
0
0
0
0
0
UBANK
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
0
0
0
0
0
OBANK
0.0
0.0
0.0
0.0
0.0
0.0
0.0
on
o
o
o
0
0
0
0
0
o
0
0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
ANNUAL AVI RAGt  GKOVUII RAITS:
              2. 319
2.311
                                       2.311
                                                   2.311
                                                                0.0
                                                                            0.0
                                                                                         0.0
                                                                                                      0.0
                                                                                                                  0.0

-------
RESULTS FOR MEDIUM SCENARIO

-------
   WORl0 TOIAL:  CFC-11
COMPONINIS  INCIUUM) :
 UNI III) SI AHS  NUN-AI ROSOL USI  OF  CIC-11:   IINIAK MODI I  2
 UNI III) SIAIbS  AIROSOL  USE 01  CIC-11:   LINIAR MODI.L + AlKOSOL  REST  =  4.
 (1C NON-AlROSOl  USE 01  CIC-11:   LINEAR MOLJEL 2
 EEC AEROSOL USE  01  CEC-11:   IINEAR HOUEl  2 + CIIKKENI AIROSOLS RES1R.
 OECD - US  - EtC  NON-Al ROSOI  USI  OF CIC-11:  IINIAK MODI I 2
 OfCD - US  - EEC  AEROSUl  USI  OE  CEC-11:  LINIAIi MODEL ?
 NON-OECD NON-AE ROSOI USE  01  CIC-11:   L OG I 1 /TOI'lll Al I ON MODEL
 NON-01 CO AEROSOL USt 01  CfC-11:   LOG I I/POI'UI Al I ON MODI L
 EMISSION EROM  WORl D BANK  01  CFC-11:   BEST  ESTIMATE - NO RESTRICTIONS
  (AIL ESI (MATES  IN  Ml I LIONS OF KILOGRAMS)
  1985
  19'JO
  1995
  200(1
  2005
  2010
  2015
  2020
  2025
  2030
  20 i 5
  2040
  2045
  2050
  2055
  2060
  2065
  2070
  20/5
ANNIMl
GROW III
   0.0
   4. /
   4.2
   4 . 0
   4. 1
   3.9
   3.8
   3. /
   3.6
   3.7
   3.5
   3.2
   3.0
   2. /
   2.6
   2.2
   1 .9
   1 .6
   1 .4
EMISSIONS
U S
408
519
643
/85
966
11 /'(
1416
1 700
2O34
24 5<>
293(1
3 '( 5 5
4022
4616
52 //
5920
6531
7105
7636
E
. l|
.0
.5
.4
.9
.8
.5
. 1
. /
.2
.6
.6
.3
. 3
.8
.2
.0
.6
.6
TOTAL
342.
436.
545 .
6/0.
816.
998.
1211.
1463.
1 /62.
2134.
2558 .
3U31 .
3546 .
4091.
468 / .
52/5.
5843 .
6382.
6889.
5
8
0
9
0
5
0
1
2
9
t|
4
4
0
9
9
7
1
9
EMISSIONS EMISSIONS EMISSIONS
1 ROM USI I ROM UUANK FROM OBANK
321
404
498^
607
74 7
909
1 099
1 324
1592
1928.
2309
2733.
3192
56 74
4202
4713
5198
5649
6067.
. 3
.5
.9
. s
. /i
.2
. 1
.2
. (I
, l|
.5
ll
'. 1
.9
.6
.9
. 2
.6
.2
0
1 1
25,
42,
63,
84 .
108,
135,
167,
203,
246
295,
351 ,
413,
483
559,
643,
730
820,
. 0
, 1
.4
.6
.8
.5
.9
.9
.2
.6
. \
.5
.5
.9
.2
.9
. 1
. 0
.2
21.
21 .
20.
20.
14 ,
4.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
1
1
8
8
8
8
0
0
9
9
5
5
2
2
1
1
5
5
5
TBANK
813.
1192.
1652.
2193.
2859.
3689.
4656.
57/6.
/U66.
8575.
10333.
12350.
14627.
1/156.
19980.
2309/.
26452.
29995.
33681.
7
8
5
0
0
5
1
9
9
3
8
7
2
4
/
6
8
8
7
UBANK
87,
571
1136.
1 /80.
2518,
33/3.
4359,
5495,
6800,
8323,
10095
12125
14413,
16953,
19/88
22916,
26282,
29838
33536
. 1
.9
6
8
.7
.0
.9
.7
.5
.5
.9
.5
.9
.9
. 7
. 1
.5
.0
.5
                                                                                      OBANK
                                                                                      726.6
                                                                                      620.9
                                                                                      515.9
                                                                                      412. 1
                                                                                      340.3
                                                                                      316.5
                                                                                      296.2
                                                                                      281 .2
                                                                                      266.3
                                                                                      251.7
                                                                                      23/.9
                                                                                      225.2
                                                                                      213.3
                                                                                      202.5
                                                                                      191.9
                                                                                      181.5
                                                                                      1 /O. 3
                                                                                      157.8
                                                                                      145.3
ANNUAL AVERAGE CROW1H  RATES:
             3.312
i.307
                          3.391
                                                  3.319
                                                              0.0
                                                -2.342
                                                                           4.224
                                                                                                    6.838
-1.773

-------
    WORID TOTAL: CFG-12
COMI'ONFNIS INCIUDII)  :
  UNIIFD SIAILS NON-Af ROSOI  USE 01  CIC-1?:  I  I Nl Al< MODI I  2
  UNIIfl) SIAIFS Al KOSOI  USL  Oh  CFC-12:  UNIAR MODI L  +  At ROSL RfSF = 4
  FfC  NON-AFROSOL USI  OF  CFC-12:   UNFAR MODEL 2
  HC  A( ROSOI  USE 01  CFC-12:   I INFAR MODF I ? -I- CIJRKtNl  At ROSOL RESFR
  01 CD - US -  ILC NON-At ROSOI  USL Of CFC-12:  I  INIAR  MODI L  2
  01 CD - US -  FFC At ROSOI  USt  OF  CfC-12:  IINtAK MODU  2
  NON-OFCD NON-AFROSOI  USL 01  CFC-12:   I OC I I /POI'UI AT I ON MODF I
  NON-OFCD AFKOSOI USF  Of  CTC-12:  LOG II /CO I'Ul A I I ON MODI I
  (MISSIONS FROM WORLD  HANK  OF  CFC-12:  FHSI LSMMAIE - NO RESTRICTIONS
   (AIL  LSdMATES IN MILLIONS OF KILOGRAMS)
   1985
   1990
   1995
  2000
  2005
  2(1 10
  2015
  2020
  2025
  20 id
  20 i5
  20'|0
  21H45
  2050
  2055
  2060
  2065
  2070
  2075
ANNUAL AVIRAGF  CROW!!! RA1IS:
ANNUAI
GROW III
0.0
'4.6
'1.2
(4.0
3.8
3.6
3^3
3. 1
3.0
2.8
2.5
2. 3
2. 1
2.0
1 .8
1 .6
1 .<4
1 .2
u s
558
/O'l
871
106'4
1287
15441
1831
2158
252')
29'l'l
3390
3858
'I3'40
'4828
53/2
5900
6'l()/
689?
735'!
E
. 7
.5
.6
. 3
.5
.9
.2
.6
.8
.8
.8
.'I
. 1
.0
.6
.14
.6
.2
.2
EMISSIONS
TOFAl
<467.9
61(3.9
788. '1
973.5
1189. 7
1137.5
1 7 1 U . 2
2028
2381
2 / 7*4
3202
3656
'4 1 26
'4606
5115
5628
613'4
6620
708 /
5
2
8
2
0
6
5
0
1
1
1
2
(MISSIONS (MISSIONS EMISSIONS
(ROM USI FROM UBANK FROM OBANK TBANK
393. 1 0.0 7'4.9 896. /
'•91.1 78.0 7(4.9 1266.2
606.0 176.8 5.5 157'4.(4
7*41.0 226.9 5.5 20 13. '4
899.8 283.2 6.6 2'i89.9
1083.0 3'4/.9 6.6 2998.8
1293.2 1420.9 0.1 3552.0
1532
1802
2100
2'419
2752
3095
3'l'4l
380'!
'H55
'('489
'1806
5106
6
0
9
3
6
1
o
7
1
5
6
5
1495
579
673
782
903
1031
1 165
1310
1'4/3
16 '4 '4
18 Hi
1980
.8
. 1
.8
.8
. '1
.3
.'I
. 3
. 0
.5
. 0
.6
0.1 14175
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
(1869
5671
6579
756(4
8611
970<4
10928
12268
13635
1(4998
163*43
.6
.2
. 1
.6
.7
.3
.3
.8
.9
.6

./4
UBANK
165.7
909.5
H453.14
1920. 1
2(426.5
2968. '4
35'll.6
'4165. 7
(4859.7
5662.0
6570.9
7556.5
8603.5
9697.0
10921 .9
1 2262 .*5
13629.6
H4992.9
16338.2
                                                                           OBANK
                                                                           731.0
                                                                           356.7
                                                                           121 .0
                                                                            93.3
                                                                            63.1
                                                                            30.»4
                                                                            10. U
                                                                            10.0
                                                                             9.5
                                                                             9.1
                                                                             8.6
                                                                             8.2
                                                                             7.7
                                                                             7.3
                                                                             6.9
                                                                             6.14
                                                                             6.0
                                                                             5.5
                                                                             5.1
              2.910
                          2.905
3.066
                                                   2.890
                                                               0.0
                                                                           -7.221
                                                                                        3.278
                                                                                                     5.23(4
                                                                                                                -5.366

-------
   WORl D  101 Al : CIC-22
COMI'ONI NI S  I NCI UDI I)  :
 UNI iiu siAirs  IOIAI  usi  or  cu;-22:   IINIAH MODI i  2
 NON-US OICD USF  01  cic-22:   IINEAK  MOOI i  2 DIRIVID i KOM u.s. usi
 NON-OICD NON-AtKOSOI. USt 01  CrC-22:   LOG I I/POI'UI A I I ON MODLL
  ( Al L I SI I MAI IS  IN  Ml I I IONS 01  KllOGRAMS)
% ANNUAL
GROW 1 M
1985
1900
199!)
20UO
2O05
?010
2015
2020
2025
;>o so
2iH5
2040
2045
2()')0
2055
2(160
2065
20/0
20/5
0,
5,
'1.
'1,
3.
3.
3
2
2
2
2
2
2
2
2
2
1
1
1
. 0
.6
.7
, 1
. '1
^>
. 0
.8
. /
.8
.6
.4
.2
. 0
.5
. 2
.9
. /
.-3
II S
1 10.
149.
190.
235.
28(1.
329.
!82.
'I'lO.
504.
58 i.
666.
752.
841.
931.
106(1.
1 I8/.
ini.
143 i.
r>5;>.
I
9
3
6
5
3
1
5
9
6
6
5
7
4
5
3
1
5
2
1
IMISSIONS 1
IOIAI
'19.
82.
120.
165.
216.
263.
315.
368.
425.
1)92.
565.
6'13.
725.
811.
918.
1030.
1 146.
1265.
1385.
9
2
6
/
1
3
4
2
'1
5
1
0
6
7
9
9
7
6
6
MISSIONS I
MISSIONS EMISSIONS
1 KOM US! I KOM IMANK f ROM OBANK
49.
61 .
05.
106.
126.
I'l8.
1 12.
198.
22 /.
262.
299 .
338.
378.
'119.
>>n.
53').
590.
6'4'l .
698.
9
'>
8
0
1
1
1
'I
1
6
9
/
6
O
1
•J
'1
9
1)
0.
15.
3«4.
59.
90.
115.
1')3.
169.
198.
229.
265.
30'),
3'l/,
392.
l)')l
')96
556
620
687
0
1
8
1
. 0
,2
, J
,8
lj
.9
.2
. 3
. 0
.5
. /
. /
.6
.6
. 1
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0
. 0
. 0
. 0
. 0
.0
. 0
.0
.0
. 0
. 0
.0
. 0
. 0
. 0
.0
.0
.0
.0
IBANK
61
385
730
1081
1 ') 1 <)
1 710
2073
2425
2808
32')0
3727
1)259
'1827
5') 1 9
6086
68')0
76')9
8i48'4
9319
.0
.3
.6
. 3
. 7
. '1
.4
.14
.0
.2
.2
.8
.14
.2
. 1
.2
.U
.0
.5
UBANK
61.0
385. 3
730.6
1081.3
1 ') 1 ') . 7
1 7'40.l|
20/3.4
2425.4
28O8.0
3240.2
3727.2
4259.8
4827.4
5419.2
6086. 1
6840.2
7649.4
8484.0
9319.5
ANNUAL AVfRAGE  GROWTH RAIIS:

              2.981        2.975
3. 762
            2.9/5
                        0.0
                                     0.0
                                                 5. 747
5. 747
                                                                                                                OBANK
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                          0.0

-------
   WORLO TOTAL: CFC-113
COMI'ONINIS  I NCI 1)1)1 I)  :
 UNIITl) SIAIES IOIAI  USf  01  CFC-113:   IINFAR  MODI I  2
 NON-US OFCO USE 01  CFC-113:   MNtAR  MOOH.  2  IJIKIVN) I ROM U.S.
 NON-OECD NON-AEROSOL USE OF CFC-113:   LOG! T/POI'ULAT I ON MOOEL
                          USE
  (AIL ESTIMATES  IN Mil I IONS  OF  KILOGRAMS)
  1985
  1990
  1995
  2000
  2(105
  2010
  2015
  2020
  2025
  2030
  2035
ANNUAL
GROW III
0,
5.
ti
it.
3
3.
2.
2.
?.
2,
2
2
?
2,
2
2
2
1
1
,0
9
.9
2
.5
2
9
,8
6
.8
.6
. 3
. 1
,0
.5
.2
. 0
.8
.6
U S
9.
587.
662.
738.
816.
933.
H)'l8.
1 161 .
12/2.
1381.
'>
U
.()
.9
.\
.9
o
,9
9
,2
!>
2
9
9
1
0
'*
!•>
.8
0.
0.
0,
0.
0.
0,
0.
0.
o.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
.0
, 0
.0
.0
, 0
.0
. 0
.0
.0
, 0
0
0
.0
,0
.0
.0
. 0
. 0
.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
,0
0
,0
. 0
.0
,0
.0
, 0
. 0
,0
.0
0
,0
0
,0
, 0
,0
.0
0
  20/15
  2050
  2055
  2060
  2065
  20/0
  2075
ANNUAL AVI RAGE GROWTH  F
-------
RESULTS FOR HIGH SCENARIO

-------
   WORID JOTAL:  CEC-I 1
OOMPONINIS  INCIUDM) :
 UNITED SIAIIS  NON-AIROSOL USE 01  CIC-11:   IINIAR MODI t 2
 UNIIIU SI AlfS  AtROSOL  US!  OK CIC-11:   LINIAK MODH + A( ROSOL  REST  = 4.5
 I EC NON-AEROSOL  USE  01  CIC-11:   LINEAR MODEL ?
 EEC AIROSOL USE  01 CIC-11:   IINfAR MODI L  2 + CIIKKINI Al ROSOI S RESIR.
 OECD - US  - EEC  NON-AEROSOI  USE 01  CIC-11:  II Nl AK MODI I  2
 01 CD - US  - EEC  AtROSOI  USE 01  CIC-11:  LINEAR MODH
 NON-OECD NON-Al ROSOI  USl  01  CfC-11:   I OCI  I/I'OI'Ul Al ION  MODEL
 NON-OICD AEROSOL  USl  01  CEC-11:  LOGI1/I'OI'UI Al ION MODI I
 EMISSION EROM  WORID  BANK OF CEC-11:   BESI  ESMMATE - NO RESIRIC1IONS
  (AIL ESI I MATES  IN  Ml I I IONS OE KILOGRAMS)
  1985
  1990
  1995
  2000
  2OU5
  2(110
  2015
  201'0
  20?5
  2050
  20.15
  2O40
  2045
  2050
  2055
  2060
  2065
  20/0
  20/5
ANNUAL AVIRACE  CROWIII RA1IS:
ANNUAI
CROWIII
0
5
5
5
6
5
5
5
'l
'1
3
2
2






0
/
l)
'1
0
8
6
3
8
2
'1
/
2
8
/
'1
3
2
1
U S
I|3D
5/4
/'>1
9//
1 115
1/51
2114
301 /
3849
4802
'jf'jl
6661
/4B9
8;'4 1
9009
il)92
1868

8
1
9
3
9
1
5
9
0
6
9
/
5
5
'4
21
21
20
20
14
14
3
3
2
2
2
2
2
2
2
2
2
2
2
. 1
. 1
.8
.8
.8
.8
.0
.0
.9
.9
.5
.5
.2
.2
. 1
. 1
.5
.5
.5
IBANK
818
123/
17/5
21)1)7
3 3 '40
«45')1
6066
798'4
H)3')2
13209
1657/
2036/
2')'l86
288')8
33U80
383/9
1)3490
48/77
54216
. 3
.8
. /
.8
.9
.3
.9
. 1
.3
.2
.2
.7
.8
. /
.4
. 1
.2
.6
.2
UBANK
91.6
616.9
1259. /
2035. 7
300O.6
4224.8
5/70.7
7702.9
100/6.0
1295/.5
16339.3
20142.5
242/3.5
28646.2
33288.5
38197.5
43320.0
48619.9
540/0.9
 OBANK
 726.6
 620.9
 515.9
 412.1
 340. 3
 316.5
 296.2
 281 .2
 266.3
 251 . 7
 237.9
 225.2
 213.3
 202. 5
 191.9
 181.5
 170.3
 157.8
 145.3
              3. /53
                          3. /36
                                      3.829
                                                   3. 745
                                                               0.0
                                                                          -2.342
                                                                                        4. 770
                                                                                                    7.346
-1.773

-------
    WOKl0  I01AL:  ClC-12
 COHI'ONI NIS  I NCI (11)1 I)  :
  UNHID SIAIIS NON-AIROSOI  USI Ol CIC-12:   I I Nl AK  MODI I  2
  UNI II I) SIAIIS Al ROSOI  USI  Ol CIC-12:   I INI AH MODI I  + Al ROSI  RISI  --  *4 *
  IIC  NON-AfROSOl  USt Ol  CIC-12:  I INfAR MODH  2
  IK:  AIROSOL  USI  01  CIC-12:   MNIAR  MODI I  2 + CIIRKINI Al ROSOI  RCSIR.
  OICD - US  -  IIC NON-AI HOSOI  USI Ol  CIC-12:   IINIAR  MODI I  2
  01 CD - US  -  I I C Al ROSOI  USI  01 CIC-12:   MNIAR MODI I  2
  NON-OtCD NON-AIROSOI  USt  Ol  CIC-12:   I OG I I /('Ol'lll Al I ON MODI I
  NON-01 CD Af ROSOI  USI  Ol  CIC-1?:  I OGI I /I'OI'UI A I I ON MODI I
  EMISSIONS  H'>
  2005
  2010
  2015
  20,"'0
  2025
  2030
  2035
  20'IO
  20'(5
  2050
  2055
  21)60
  2065
  20/0
ANNUAI
GROW III
<).(>
6. 1
rj.fl
b.6
-3.1)
•). 1
'1.6
'(.0
3.'j
3.0
2.1)
2.0
. /
.5
.'j
.3
2
. 1
. 1

U S 1
6()H . 1
H2l|.r>
1 100. 1
HIM. \
1 ')1 '> . '1
2M/6.2
JI2H.9
3H'ji.5
'(61H.2
•>'l() 5 . 'l
6 1 'j'l . 2
6Hl>8. /
/'>!(>. 1
813:'. 9
8/9'».ll
9'l29.2
lOO'l ». f
1061(6. 1
1 121(1. !>
LMISSIONS
TOIAI
509.0
7'l / . 2
992 . 1
1323.6
175/.2
228 /. 3
2901. 1
3592. 1
'(326.8
50/'l.9
5811.0
6515.9
/180.U
7806.0
8'(2/.5
9()'l6.2
9659. /
10260.6
1085'(. /
{MISSIONS
1 ROM USI
'(3'(. 1
588. /
/91 . 5
1055.0
l'lO'(.l)
I82/.5
2318.9
2860.'!
i'(26.'(
3985.2
'15)3.5
5003. 8
51(56.5
58/6. f
628 /. 8
66/6. 3
/()'(9.2
/'(I 1 .9
//68.'l
1 MISSIONS
f ROM UlfANK
0.0
83. /
1 95 . 3
263. 1
3 '(6. 6
'(53.2
'j8«4. 1
/ 11 . /
900. '(
1089. /
1 29 / . '(
1512.0
1 /23.'(
1929. 5
21 !9.6
2 !69.8
26 10. '(
28'(8.6
3086.2
1 Ml SSIONS
IROM OBANK IBANK
/'1. 9 90'(.9
/'1. 9 13'(1.5
5.5 175/.8
5.5 2355.5
6 . 6 3086 . 2
6.6 3969.3
0.1 5018.0
0.
0.
0.
0.
o.
o.
0.
o.
0.
0.
0.
0.
625'(. 8
/65'(.9
9232.3
1092/.2
126'(5. 3
1'(3'(1 . 1
1599'(.'(
1 / /62 . 9
1 965 7 . /
215/5.9
23500.5
25'l32.3

UBANK
1 /'(.()
98'(.8
1636.8
2262. 3
3022.8
3939.0
500 / . 6
62'l'( . 8
/6'(5.'»
9223.2
10918.6
1263/. 1
1'(333.3
1 598 / . 1
1 //56.0
19651.3
215/0.0
23'(95.0
25'(2/.2
                                                                                           OBANK
                                                                                           731 .0
                                                                                           356.7
                                                                                           121 .0
                                                                                            93.3
                                                                                            63.'(
                                                                                            30.14
                                                                                            10.14
                                                                                            10.0
                                                                                             9.5
                                                                                             9. 1
                                                                                             8.6
                                                                                             8.2
                                                                                             7.7
                                                                                             7.3
                                                                                             6.9
                                                                                             6.'4
                                                                                             6.0
                                                                                             5.5
                                                                                             5. 1
ANNUAL  AVI RAGL CROW III RAMS:
              3.311
1. 29'l
                                        3.'(58
3.25/
                                                                  0.0
                                                                              -7.221
                                                                                            3. 116
                                                                             5.695
                                                                                                                     -5.366

-------
   WORLD  TOTAL:  CfC-22
COMPONENTS  I NCI UOEI) :
 UNITED STATES  TOTAL USE  OE CFC-22:   I INIAR MODII  2
 NON-US OECD USE  Ol  CFC-22:  LINEAR MODEE  2 01 HIVED fROM U.S.  USE
 NON-OECD NON-AEROSOI  USE OF CFC-22:   LOCIT/POPUI AT ION MODEL
  (ALL ESTIMATES  IN  Ml I LIONS OE KILOGRAMS)
  1985
  1990
  1995
  2000
  2005
  2010
  2015
  2020
  2025
  2OJO
  21135
  20'tO
  21 Hi 5
  2050
  2055
  2060
  2065
  20/0
  2(1/5
ANNUAL AVI RAGE GKOWIH KATIS:
ANNHAI
GROW III
0.
6
5
5
<4,
'1
'»
3
3
3
2
2
2
\
2
2
1
1
1
.0
.6
.7
. 1
.8
,»4
. 1
. 7
.3
.2
. 7
. 3
. 0
.8
.3
. 1
.9
. /
.6
U S
1 15
163
219
283
360
'l'49
552
666
/89
933
1076
1215
1 !5U
1'lHi
16 /'l
1H63
2051
2238
?'42'4
E
.2
.6
. 1
.»»
. <4
.8
.H
.6
.3
.(4
.2
.4
.9
.()
.9
.9
.U
.0
.6
EMISSIONS
TOIAl
51.
89.
136.
1 9'l .
266.
3'I3.
432.
530.
63/.
762.
892.
1026.
1161.
1296.
Hl61
1630.
18()'l.
198'4.
3169.
8
/
/
9
9
2
*4
,0
8
1
6
5
8
,8
. 1
3
, /
,8
, 1
EMISSIONS
EMISSIONS EMISSIONS
(ROM USf EROM UBANK E ROM OBANK
51.
73.
98.
127.
162.
202.
2'48.
30O.
355.
1420.
l|8<4.
5'4/.
607.
66 /.
/53.
838.
923.
1007.
1091 .
8
6
6
6
'1
i|
6
O
2
U
3
0
9
'4
/
8
1
1
1
0.
16.
38.
6/.
I0<4.
I'm.
183.
230.
282.
3'l2.
1408.
'4/9.
553.
629.
707.
/91.
881 .
9//.
10/8.
0
0
1
3
/
8
8
0
/
1
3
5
9
5
'4
6
6
/
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
TBANK
63.
»412.
808.
12'40.
1698.
2205.
27/8.
3'428.
»415/.
<4977.
58/3.
6810.
7/5/.
869'4 .
9/11.
108*12.
12052.
13308.
1*4581.
3
9
8
1
/
2
6
8
6
U
8
<4
'4
/
8
9
6
3
8
UBANK
63.
'412.
808.
12140,
1698.
2205.
2//8.
3*428.
»4157.
149/7,
5873.
6810.
7/57,
869<4,
9/11.
H)8'l2.
12052,
13308,
114581
3
,9
.8
. 1
7
2
6
8
.6
.14
8
.14
.'4
. /
.8
,9
.6
. 3
.8
                                                              OBANK
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
                                                                0.0
              3.1456
                                      14.236
3.<4'l'4
                                                               0.0
                                                                           0.0
                                                                                       6.230
                                                                                                    6.230
                                                                                                                0.0

-------
   WORID 10FAL: CFC-113
COMI'ONLNIS  INCIUDH)  :
 UNIHO SIAItS 101AI  USE  OF  CfC-113:   I I NEAR MODI I  2
 NON-US OtCD USE 01  CFC-113:   UNEAR  MOD El 2 PI l< I Vf 0  I ROM  U.S.  USE
 NON-OECD NON-AEROSOL  USE Of  CFC-113:   LOCI T/POI'ULAT ION  MODEL
  (AIL ESMMAFES  IN Ml I I IONS  OF  KILOGRAMS)
% ANNUAL
GROW 1 II
1985
1 990
1995
2000
201)5
2010
2015
2(120
2025
2030
2(1 <5
2U'lO
20'l5
2050
2055
2060
2065
20/0
2075
0.
7.
5.
5.
i*.
b.
3.
3.
3.
3.
2.
2.
2.
1 .
2.
2.
2.
1.
1 .
0
0
8
1
I
3
9
6
2
2
7
i»
1
9
5
2
0
8
7
11 S
98.
1'|2.
192.
2') 8.
m.
391.
Ull.
575.
6/
.0
.0
.0
.()
. 0
. 0
.()
.0
.0
.0
.0
.0
.0
. o
. o
. 0
.0
0
0
0
u
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
                                                                                      TBANK
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        o.o
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                                                        0.0
                                                 UBANK
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                                   0.0
                                     OBANK
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
                                       0.0
ANNUAL AVERAGE GROWTH RAFES:
             3.513
                          3.501
                                      3.501
3 . 50 1
                                                             0.0
0.0
                                                                                      0.0
0.0
0.0

-------
RESULTS FOR NO LIMITS TO GROWTH SCENARIO

-------
    WORLD  10IAL: CFC-11
COMI'ONI NIS  I NCI 1)1)1 I) :
 UN I III) SI AIIS NON-AI KOSOl  t)SI  01  CIO 11:   I INIAK MODI I  2
 UNI I JO SI AIIS AIKOSOI  USI  Ol  Cl C- 1 I :   I  I Nl AK MODI I  + Al KOSOl  RfSI    l|. 5
 LlC  NON-AIROSOL  USI  Ol CIC-11:   IINIAR MODI I  2
 IIC  Al IU)SOl  USI  Ol  ClOU:   IINIAK  MODI I  2 + l.UKRINI Al KOSOl S KISIR.
 Ol CD - US  -  IIC  NON-AI KOSOl  USI  01  CIC-11:   I INIAK  MODII  2
 01 Cl) - US  -  IIC  AIKOSOI   USI  01 CIC-11:   I  INIAK MODII  ?
 NON-OI Cl) NON-AIKOSOI  ItSI  01  CIC-11:   I OG I I /I'OI'UI A I I ON MOON
 NON-01 Cl) AIKOSOI  USI  Ol   CIC-11:   I OG I I / I'OI'UI A I I ON MODI I
 I Ml SSI ON fKOM WOK I I) HANK 01  CIC-11:   BIS I  I S I I MA 11  - NO Kt SI K 1C I IONS
   (All  ISIIMAIIS  IN  Ml I I  IONS OF KILOGRAMS)
% ANNUAI
GROW 1 II
I9H5
1990
1995
2OOO
2O05
2010
2015
21)20
2025
20 !O
2< t i 5
201)0
20')5
POM)
2055
2060
2065
20/0
20/5
0.
6.
6
6.
/
6
6
6.
5.
I).
'1.
3.
2.
2.
2.
2.
1 .
1 .
1 .
. 0
.6
.2
. 1
. S
. y
.5
.0
. 3
.9
.0
.2
6
;>
2
. 0
.8
6
.5
U S
518.
/2 !.
98 '1
1 12 /
1906 .
26/6.
3690.
'498 I .
6'>'lO
8'4/9.
1()'|85.
12'45'j.
I'l (29,
16096.
18110.
20065.
21992.
2391 /.
25858.
L
. /
, 5
. j
. 2
.8
.6
.9
y
6
. 3
8
, /
.8
5
. 7
. O
. 1
3
8
IMISSIONS
101AL
'426.
59 / .
82O.
Ill/,
1 596 .
225 / .
313/.
'12/0.
56'l / .
/ Cl6.
9128.
1O902.
12612.
1 ')2')l4 .
16036.
1 / /9'4 .
195'46.
2 1 309 .
23100.
3
.6
.2
.6
.6
.6
. 5
.8
.9
.6
5
.2
. /
/
/
.8
.2
5
'4
I Ml SSIONS
1 ROM USI 1
'105. 1
56 1 . 5
/63.6
1033. /
l')91 . .i
2 to/, i
2928. 1
(983. 1
5259.8
(.832.O
M'15/.B
IOOM /.8
1 1551 . 6
1/958. 8
1M508. O
15999.9
1 /'I62. /
1891 /. 9
20380.8
IMISSIONS IMISSIONS
ROM UBANK (ROM OBANK
O
15
(5
63
1OO
1 <|5
206
28'4
385
51 1
668
85 1
1O59
1283
1526
1/92
2081
2389
2/1 /
. O
.O
. 8
. 1
. •>
.6
.')
/
.2
.6
. ;>
.8
.0
. H
. /
.8
.()
. ;>
. I
21 .
21 .
20.
20.
'4.
l|
3'
3,
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
1
. 1
.8
.8
.8
.8
. 0
.0
.9
.9
, 5
•j
.2
2
1
1
. •>
5
. 5
IBANK
8')0,
I'lOl .
2 l')2 .
3096
'l'42'l .
6292
8//9
12015,
16113
21 300,
2/6<46.
3503i«.
'13305 .
5230'4
622'4l '.
/3209.
85O9'4.
9/815.
111309.
, 1
.2
.6
. 1
.2
/
. 0
/
.9
.3
.6
. 5
.'4
.6
.8
.2
. S
'4
. 1
UBANK
113
/80.
1626
268')
1)083
5 9/6
8'482
1 t/3'4
1 58'4 /
2IO'l8
2/'4()8,
3'l809
'43092,
52 1O2
6201)9,
7302/,
8'l92'l
9 /65 / .
1 1 1 163.
. 5
. 3
/
. 0
.9
. 3
.8
. ',
.6
. ',
. /
.2
. 1
. 0
.9
/
.2
, /
.9
OBANK
726
620
515
1)12
3 '40
316
296
281
266
251
237
225
213
202
191
181
1 70
157
1145
.6
.9
.9
. 1
.3
. 5
.2
.2
.3
.7
.9
.2
. 3
. ;>
.9
. *y
.3
.8
.3
ANNUAI  AVI RAGl  CKOWIII KAIIS:

               'I.'l60        'I.'139
'4.536
'). '4Ml
                           0.0
-2.3'l2
                                                       /.952
-1.7/3

-------
    WORLD 10TAL:  CFC-12
COMPONtNIS INCIUDEO :
  I1NIIU)  SIAIES NON-AEKOSOI  USF Of C1C-12:  IINIAR MODI I 2
  UNITIO  SIATIS AEROSOl  USE Of CEC-12:  LINIAR MODEL +  Al ROSI  REST  --  4.5
  I LC  NON-AEROSOI  USE Ol  CIC-12:  IINEAR MODEI  ','
  EEC  AEROSOL  USE  Of  CFC-12:  I  INtAR MODEL 2 + CURRENT  Al ROSOl  RESTR.
  OECD -  US -  EEC  NON-AtROSOL USE OE CFC-12:  LINIAR MODEL 2
  OECO -  US -  EFC  AlROSOL USI  01 CIC-12:  IINEAR MODEI   2
  NON-OECD  NON-AEROSOL USE 01  CIC-12:  LOG I  I/POPUI AT ION MODEI
  NON-OfCD  AEROSOI  USE  OF CfC-12:  IOC I T/POI'Ul Al I ON MODI I
  EMISSIONS FROM WORLD BANK OF CFC-12:  BES1 ESIIMA1E - NO RLSIRICflONS


   (AIL ESTIMATES  IN Mil LIONS OF KIIOGRAMS)
ANNUAL
CROW III
0.0
6.9
6.'j
6.2
6.5
5
5
if
3
3
3
2
2
1
2
1
1
1
1
9
2
5
9
6
0
5
2
9
1
9
1
6
5
u s
/98
1 12H
1559
2119
29 43
3962
51/3
6'>4 )
801 /
969V
1 1359
1298U
14550
I6(l/ 1
1 /90/
19/26
21548
23 J84
25245
E
.2
. 3
.2
.2
.3
.6
.3
. /
. 7
. 1)
.'(
.8
.2
.9
.5
.8
. 1
.5
.14
EMISSIONS
TOTAL
618.2
996.8
1399.3
1924. •>
2670.2
3623
'1/59
6053
71)60
9U1 /
10616
12210
13766
1528'!
169'! lj
1867'j
20l»56
2?256/3
1 i /90
MI900
16012
1 /133
/
'4
6
6
>l
2
6
6
6
i
9
8
/
7
EMISSIONS EMISSIONS
ROM UISANK FROM OBANK IBANK
0.0 7'4.9 955.9
109.9 /U.9 1658.8
261.6 5.5 23'4l./
363.0 5.5 3242.6
'195.0 6.6 '4'437.5
6/6.
910.
1 183.
1501 .
18/3.
2308.
2/80.
3262.
3/'48.
'4?/2.
'IBS^.
5555.
62'4l.
69'45.
b
'>
1
/
3
0
/
/
8
D
o
/62.
'408 /'4.
'1625'!.
51830.
57591.
'4
2
0
1
0
2
<4
1
9
3
2
0
3
1
   1985
   1990
   1995
  2OOO
  2005
  2010
  2015
  2020
  2025
  2050
  2035
  20'lO
  20'45
  2050
  2055
  21)60
  2065
  20/0
  20/5
ANNUAL AVI RACE GROWTH  KA11S:

             3.9(1        3.912
4.098
3. 8'4 /
                                                              0.0
                                                                         -7.221
                                                                                      4.659
                                                             6.356
                                                                          OBANK
                                                                          731.0
                                                                          356.7
                                                                          121 .0
                                                                           93.3
                                                                           63.4
                                                                           30.'4
                                                                           10.4
                                                                           10.0
                                                                            9.5
                                                                            9. 1
                                                                            8.6
                                                                            8.2
                                                                            7.7
                                                                            7.3
                                                                            6.9
                                                                            6.4
                                                                            6.0
                                                                            5.5
                                                                            5. 1
                                                            -5.366

-------
   WORLD TOTAL:  CFC-22
COMF>ONtNTS  INCLUDEO  :
 UNITED SIAtES  TOIAI  USE  01  CFC-22:   UNFAR MODI I  2
 NON-US OFCD USE  OE  CFC-22:   LINEAR MODEI  2 DERIVED I ROM U.S. USE
 NON-OFCO NON-AtROSOl  USE OF  CFC-22:   LOGI F/POPUI AfION MODEL
  (ALL ESTIMATES  IN  Ml I LIONS OE KILOGRAMS)
%

1985
1 990
1995
2000
2005
2010
2015
2020
2O25
2030
2O35
2O40
2045
2050
2O55
2O60
2O65
20/0
20/5
ANNUAF
GROW III
0.
7.
6.
5.
5.
5.
4.
4.
3.

3.
2.
2.
2.
3.
2.
2.
2.
2.
0
2
1

8
2

2
7
0
4
9
6
3
1
7
'l
2
0
U S
159.
231.
31 /.
418.
561.
/3 1 .
929.
1 154.
1400.
1 /2()
2()6o
239H.
2/39.
3082.
3622.
41 70.
4/29.
5300.
5885.
E
0
7
1
5
6
5
9
8
/
3

1
3
/
l)
/
j
9
6
EMISSIONS
TOTAL
/I.
126.
196.
284
405!
541.
705.
891 .
1103.
136/.
1655.
1962.
2284.
2618.
3055.
3522.
4020.
4550.
5108.
6
6
1
9
9
/
5
8
0
1
2
2
7
5
2
5
5
7
4
EMISSIONS
EMISSIONS EMISSIONS
I ROM USE FROM UBANK FROM OBANK
/I .
104.
142.
188.
252.
329.
418.
519.
630.
/ /6
92/.
10/9.
1232.
I38/.
1630.
18/6.
2128.
2385.
2648.
6
3
I
3
I
2
4
I
3
8
2
l|
f
2
1
8
4
i|
5
0.0
22.4
54.0
96.6
153.2
212.5
28/.0
3/2.2
4/2. /
590 . 3
728.0
882. /
1052.0
1231. 5
1425. 1
1645. /
1892. 1
2165. 3
2459.9
0.
0.
0.
0.
0.
0.
0.
o .
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0
0
0
0
0
0
()
0
0
0
0
0
0
0
0
0
0
0
0
TBANK
8 / .
578.
1 150.
1/93.
2528.
3408.
4461.
5/00.
7121 .
8800.
10740.
12866.
15108.
1/411.
20050.
23137.
26569.
30246.
34080.
5
5
8
3
6
8
9
5
4
1
4
4
0
1
3
3
3
5
4
UBANK
8/.5
578.5
1 150.8
1/93.3
2528.6
3408.8
4461 .9
5/00.5
7121.4
8800. 1
10/40.4
12866.4
15108.0
1/411.1
20050. 3
2313/. 3
26569.3
30246.5
34080.4
ANNUAL AVI KAGF  GROWTH ISAFIS:
              'I. 106
'4.094
                                      14.856
                                                  4.094
                                                               0.0
                                                                           0.0
                                                                                       6.852
                                                                          6.852
                                                                                                                OBANK
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                  0.0
                                                                                                                0.0

-------
    WORI i> loiAL:  CM:-in
COHI'ONI Nl S I NCI 1)01 I)  :
  UN I I II) SI AMS IOIAI  USI  Ol  CIC-1U:   IINIAK  MODI I  2
  NON-US 01 CO USE 01  CK:-113:  I  I Nl AH MOOI I  2  1)1 l< I VI D I KOM  U  S   USI
  NON-01 CD NON-AEKOSOI  USE 01 CEC-113:   LOG I T/POI'ULAT I ON MOOI L


   (AIL  ESI I MATES  IN  Ml I I IONS Of KILOGRAMS)
%

1985
1990
1995
?0l)0
2005
POIO
2015
2020
2025
20 so
20 1'>
?()'io
20'45
?(!')()
2055
2OM»
2065
20/0
20/5
ANNUAL
CROW III
0.0
1.6
6.3
5.5
5.8
5.2
'I. /
14.2
3. /
1.0
3. '4
3.0
2.6
2.14
3.3
2.9
2.6
2.3
2. 1

U S E
1211.5
18/. 1
259 . 8
3'4'4.8
'46'4. 3
6()'l . 5
/66 . 3
9'48.5
1 1 'I / . 2
1 '11 H . /
U>99.()
198'l.8
?:J /'».()
2569.8
3l)'l9.5
3538.6
'I03H.5
'4 5 5(1. '4
50/i|.9
EMISSIONS
TOTAL
1 2'4 . 5
187. 1
259.8
3'|l4.8
14614.3
60»4.5
/66.3
9'48.5
1 1 '4 / . 2
1U18. 7
1699.0
198'4.8
2275.0
2569.8
30119.5
3538.6
'4038.5
'4550.'4
5074.9
LMISSIONS EMISSIONS EMISSIONS
II«)M IJSL fROM UBANK FROM OBANK
12'4.
18/.
259.
3'l'4.
«46'4.
60'4.
766.
9'48.
11 'I/.
1 '4 1 8 .
1 699 .
198'4.
22/5.
2569 .
30'49.
.5538.
'1038.
'1550.
50/4.
5
1
8
8
3
5
3
5
2
/
0
8
0
8
5
6
5
'4
9
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
O.
0.
0.
0.
0.
0.
0.
0
I)
O
0
0
I)
O
0
O
0
O
O
0
I)
O
O
0
0
0
0.0
0.0
0.0
0.0
o.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
FBANK
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
UBANK
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.o
0.0
0.0
0. 0
0.0
0.0
0.0
0.0
o.o
0.0
0.0
OBANK
0.0
0. 0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0. 0
0.0
0.0
0. 0
0.0
0.0
0.0
0.0
ANNUAL AVI KAGE GKOWTII KATIS:

              4.219        '4.206
14.206
                                                   14.206
                                                                             0.0
                                                                                          0.0
                                                                                                      0.0
                                                                                                                   0.0

-------
                                ANNEX E

              POPULATION  AND GNP  PER CAPITA PROJECTIONS


    Projections of population and GNP  per  capita  in  the U.S., non-U.S. OECD,
and the non-OECD countries were developed  to  provide a basis  for projecting
scenarios of potential future CFC use.  Five  projections were developed:

        (1)  "Limits to Growth," a likely  lower bound on future GNP
             per capita and population growth;

        (2)  Low;

        (3)  Medium;

        (4)  High; and

        (5)  "No Limits to Growth," a  likely  upper bound on future
             GNP per capita and population growth.

    Exhibit E-l displays the population projections. First,  global  population
projections were adopted from a review of  published  estimates; these are  shown
at the top of Exhibit E-l.  Edmunds'  (1984)  low scenario was  the  lowest
published projection, only 7.1 billion people in  2075.1  For  this population
to be achieved, all portions of the world  must achieve zero population growth
by the middle of the next century.

    The highest published estimate is  from the United Nations  (1981), over
13.6 billion people in 2075.2  The middle  three projections were  developed
from Lovins (1981),3 the World Bank (1985),"  and  Edmunds'  (1984)5 middle
scenario.  To divide these global estimates  into  three regions, the  expected
share of world population in each region  over time was estimated  from Edmunds'
three scenarios.6  These shares (shown in  Exhibit E-l) are
    1 J.A. Edmunds and J. Reilly, et al.   An Analysis of Possible Future
Atmospheric Retention of Fossil Fuel CO .   Prepared for United States
Department of Energy, Washington, D.C.   September,  1984.

    2 Long-Range Global Population Projections 1984.   World Bank,
Washington, D.C., 1985.

    3 Amory Lovins et al.  Least Cost Energy:   Solving the C00 Problem,

Brick House Publishing Company, Andover,  MA. 1981.

    u My T. Vu.  World Population Projections 1984.  World Bank,
Washington, B.C., 1985.

    5 Edmunds, op. cit.

    6 Ibid.

-------
                               E-2
                          EXHIBIT E-1
                    GLOBAL  POPULATION PROJECTIONS
                              (MILLIONS)
YEAR
1985
2000
2025
2050
2075

LIMITS
TO GROWTH
4536
5377
6505
7324
7131

LOW MEDIUM
4745 4745
5901 5901
7384 7384
7664 8223
7944 8491
REGIONAL POPULATION SHARES
HIGH
4835
6147
8160
9496
9960

NO LIMITS
TO GROWTH
5000
6500
9500
12100
13600

YEAR
US SHARE
OECD-US SHARE
NON-OECD SHARE
1985 0.048
2000 0.043
2025 0.038
2050 0.036
2075 0.035





0.120
0.107
0.094
0.088
0.087





0.832
0.850
0.868
0.876
0.879





REGIONAL POPULATION PROJECTIONS


YEAR REGION
1985 US POP
OECD-US POP
NON-OECD POP
TOTAL
2000 US POP
OECD-US POP
NON-OECD POP
TOTAL
2025 US POP
OECD-US POP
NON-OECD POP
TOTAL
2050 US POP
OECD-US POP
NON-OECD POP
TOTAL
2075 US POP
OECD-US POP
NON-OECD POP
TOTAL

LIMITS
TO GROWTH
219
545
3772
4536
232
576
4569
5377
249
612
5644
6505
262
644
6418
7324
247
617
6267
7131
(MILLIONS)

LOW
229
570
3946
4745
255
632
5014
5901
283
695
6407
7384
274
674
6716
7664
275
688
6981
7944


MEDIUM
229
570
3946
4745
255
632
5014
5901
283
695
6407
7384
294
723
7206
8223
294
735
7462
8491


HIGH
234
581
4020
4835
266
658
5223
6147
313
768
7080
8160
339
835
8322
9496
345
862
8753
9960

NO LIMITS
TO GROWTH
242
601
4158
5000
281
696
5523
6500
364
894
8243
9500
432
1064
10604
12100
471
1177
11951
13600

-------
                                   E-3
multiplied by the global values to produce population projections by region
over time.  As indicated by the increasing share of world population in
non-OECD countries, this region's population is projected to grow faster than
the other regions'.

    To project GNP per capita we reviewed projections and historical data on
the rates of growth of GNP and GNP per capita.   Historically,  the rates of
growth of these quantities have varied significantly across regions and
throughout time.   The largest reported sustained growth of GNP per capita is
for Japan, 1874 to 1967, 2.8 percent per year.7  It is unlikely that global
GNP per capita will grow this rapidly over the  next 90 years.   The lowest
projected rates of growth are in Lovins (1981),8 with growth declining from
one percent per year through 2000, to under 0.3 percent per year by 2075.  For
purposes of developing projections, we assumed  that all our scenarios would
fall within these wide boundaries.  To compute  the five scenarios, we assumed
the following growth rates in GNP per capita:
Limits to Growth

Low

Medium

High

No Limits to Growth
1985-2000

  1.0%

  1.5%
  2.0%

  2.5%
2000-2025

  0.5%

  1.2%

  1.7%

  2.0%

  2.5%
2025-2050

  0.5%

  1.0%

  1.7%

  2.0%

  2.5%
2050-2075

  0.3%

  1.0%

  1.7%

  2.0%

  2.5%
These values reflect the full range of likely global GNP per capita over the
next 90 years.

    To develop estimates for each of the three regions of interest, we
performed the following 5 steps:

        (1)  compute global GNP per capita through 2075 for each of
             the five projections (see top of Exhibit E-2);

        (2)  compute global GNP by multiplying the global GNP per
             capita by the number of people estimated in Exhibit E-l
             (see middle of Exhibit E-2);
      Simon Kuznets.   Economic Growth of Nations, The Beltnap Press of
Harvard University Press, Cambridge, MA., 1972.
    8 Lovins, op. cit.

-------
       E-4
  EXHIBIT E-2
PROJECTIONS OF GLOBAL



YEAR
1985
2000
2025
2050
2075



LIMITS
TO GROWTH
1900
2206
2499
2831
3051

GNP PER
(1975

LOW
1900
2375
3201
4105
5264
GLOBAL
COMPUTED USING GNP PER


YEAR
1985
2000
2025
2050
2075

YEAR
1985
2000
2025
2050
2075

LIMITS
TO GROWTH
8618
11861
16254
20731
21755

US SHARE
0.227
0.215
0.179
0.159
0.162
(BILLIONS OF

LOW
9016
14017
23635
31459
41818
REGIONAL
OECD-US
0.
0.
0.
0.
0.
CAPITA
us $)

MEDIUM
1900
2447
3729
5683
8662
GNP
CAPITA AND
1975 US S)

MEDIUM
9016
14438
27535
46735
73553
GNP SHARES
SHARE
391
387
374
365
369


NO
HIGH TO
1900
2557
4195
686.3
11292

POPULATION

NO
HIGH TO
9187
15719
34233
65359 1


LIMITS
GROWTH
1900
2752
5102
9458
17535



LIMITS
GROWTH
9500
17886
48465
14443
112468 238474

NON-OECD
0.
0.
0.
0.
0.

SHARE
381
399
447
475
469

-------
EXHIBIT E-2  (continued)
 REGIONAL GNP PROJECTIONS
YEAR
1985



2000



2025



2050



2075



REGION
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
(BILLIONS
LIMITS
TO GROWTH
1959
3372
3287
8618
2547
4584
4730
11861
2909
6074
7272
16254
3303
7573
9855
20731
3520
8023
10211
21755
OF 1975
LOW
2049
3528
3439
9016
3010
5418
5590
14017
4229
8832
10573
23635
5012
11492
14955
31459
6766
15423
19629
41818
U.S. S)
MEDIUM
2049
3528
3439
9016
3100
5580
5757
14438
4927
10289
12318
27535
7446
17072
O "> "> 1 "*
46735
11901
O ~* 1 1 "•
_ i 1 .. /
34525
73553
HIGH
2088
3595
3504
9187
3375
6075
6268
15719
6126
12792
15315
34233
10413
23575
31071
65359
18198
-+1-+79
52791
112-468
NO LIMITS
TO GROWTH
2159
3717
3624
95GO
3841
6913
"™ 1 "^ *X
17886
8673
18111
21682
48465
18234
-130-
5-*-C5
11-+-43
355S"
S'95C
111937
23347-

-------
                                   E-6
        (3)  estimate regional shares of global GN'P from Edmunds'
             (1984) estimates9 (see middle of Exhibit E-2);

        (4)  multiply the regional GNP shares by the global GNP
             estimates to compute regional GNP estimates (see end of
             Exhibit E-2);  and

        (5)  divide the regional GNP projections by the regional
             population projections (Exhibit E-l) to compute
             regional GNP per capita projections (see Exhibit E-3).


The values shown in Exhibit E-3 show GNP per capita in the U.S. growing at an
average rate between 0.5 percent and'2.5 percent per year.  The rates in the
non-OECD countries are larger:  0.7 percent to 2.7 percent per year.
      Edmunds , OJD •

-------
             E-7
         EXHIBIT E-3
REGIONAL GNP PER CAPITA PROJECTIONS
YEAR
1985



2000



2025



2050



2075



REGION
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
US GNP
OECD-US GNP
NON-OECD GNP
TOTAL
(1975
LIMITS
TO GROWTH
8932
6189
872
1900
10965
7964
1035
2206
11674
9927
1288
2499
12625
11758
1536
2831
14243
12998
1629
3051
U.S. $)
LOW
8932
6189
872
1900
11808
8577
1115
2375
14953
12716
1650
3201
18308
17051
2227
4105
24576
22429
2812
5264
MEDIUM
8932
6189
872
1900
12162
8834
1148
2447
17421
14814
1923
3729
25350
23609
3083
5683
40441
36908
4627
8662
HIGH
8932
6189
872
1900
12711
9233
1200
2557
19599
16667
2163
4195
30699
28591
3734
6883
52718
48112
6031
11292
NO LIMITS
TO GROWTH
8932
6189
872
1900
13678
9935
1291
2752
23834
20268
2630
5102
42186
39289
5131
9458
81863
74711
9366
17535

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R-3386-EPA
Product Uses and
Market Trends for
Potential Ozone-
Depleting Substances,
1985-2000
James K. Hammitt, Kathleen A. Wolf,
Frank Camm, William E. Mooz,
Timothy H. Quinn, Anil Bamezai
May 1986

Prepared for the
U.S. Environmental Protection Agency

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                           PREFACE
  This report is one of a series of papers  written at The Rand Cor-
poration on policy  issues associated with chemicals that could poten-
tially deplete ozone in  the  stratosphere ("potential ozone depleters").
Stratospheric ozone is important because the ozone layer helps  shield
the earth from harmful ultraviolet radiation.  Increases  in ultraviolet
radiation  may threaten  human health, speed  deterioration of certain
materials, reduce crop  yields,  and  have  a wide  range of potentially
important ecological effects.  Atmospheric models  developed and  tested
over the last decade suggest that global human emissions of potential
ozone  depleters may lead to  chemical reactions that reduce  strato-
spheric ozone, thereby increasing ultraviolet radiation with its concom-
itant effects. Substantial scientific uncertainty persists about whether
human emissions of these chemicals actually threaten the stratospheric
ozone  layer  and,  if they  do, whether  lower ozone  levels  actually
threaten human health  and other activities at the earth's surface that
concern policymakers. Policymakers must act in the face  of this uncer-
tainty, however, and Rand's work is designed to help them act with the
best information available.
  To that end, The Rand Corporation is  developing a series of reports
addressed to analysts and policymakers responsible for policy decisions
on emissions of potential ozone depleters in  the United States and else-
where.  These documents report the results of research  that includes
extensive  literature reviews, interviews  with  knowledgeable  officials
associated with  the production and use  of potential  ozone depleters,
and formal  chemical, cost,  economic,  and  statistical  analyses.  The
series should also interest the  much broader audience of analysts and
decisionmakers whose organizations would  feel the effects of govern-
ment policies with respect to emissions of such chemicals.
  Published papers in the series include the following:

    •  A. R. Palmer, W. E.  Mooz, T.  H. Quinn, and K. A.  Wolf,
       Economic Implications  of Regulating Chlorofluorocarbon  Emis-
       sions from Nonaerosol Applications, R-2524-EPA, June 1980.
    •  A. R. Palmer, W. E.  Mooz, T.  H. Quinn, and K. A.  Wolf,
       Economic Implications of Regulating Nonaerosol Chlorofluorocar-
       bon Emissions: An Executive Briefing, R-2575-EPA, July 1980.
    •  K. A. Wolf,  Regulating Chlorofluorocarbon Emissions: Effects on
       Chemical Production, N-1483-EPA, August  1980.
                                 111

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IV
    •  A. R. Palmer and T. H. Quinn, Economic Impact Assessment of
       a Chlorofluorocarbon  Production  Cap,  N-1656-EPA, February
       1981.
    »  A. R.  Palmer and  T.  H. Quinn, Allocating Chlorofluorocarbon
       Permits:  Who  Gains,  Who Loses,  and  What Is  the  Cost?
       R-2806-EPA, July 1981.
    •  W. E. Mooz, S.  H. Dole, D. L. Jaquette, W. H. Krase,  P.  F.
       Morrison, S. L. Salem, R. G. Salter, and K. A. Wolf, Technical
       Options    for    Reducing    Chlorofluorocarbon    Emissions,
       R-2879-EPA, March 1982.
    •  E. M.  Sloss and T.  P. Rose, Possible  Health Effects of Increased
       Exposure to Ultraviolet Radiation,  N-2330-EPA, July 1985.
    •  T. H.  Quinn, K. A. Wolf, W. E.  Mooz, J. K. Hammitt, T. W.
       Chesnutt, and S. Sarma, Projected Use, Emissions, and Banks
       of Potential Ozone-Depleting Substances, N-2282-EPA, January
       1986.
    •  F. Camm and  J. K.  Hammitt, An  Analytic Method for Con-
       structing Scenarios from a Subjective Joint Probability Distribu-
       tion, N-2442-EPA, May 1986.
    •  F.  Camm,  T.  H.  Quinn, A.  Bamezai, J.  K.  Hammitt,  M.
       Meltzer, W. E. Mooz, and K. A.  Wolf, Social Cost of Technical
       Control Options  to Reduce the Use of Potential Ozone Depleters
       in the United States: An Update,  N-2440-EPA, May 1986.
    •  W. E. Mooz, K. A. Wolf, and F. Camm, Potential Constraints  on
       Cumulative    Global    Production    of   Chhrofluorocarbons,
       R-3400-EPA, May 1986.

  This report was  produced under  Cooperative  Agreement No.
CR811991-02-0 with the U.S. Environmental Protection Agency.

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                         SUMMARY
  Global human emissions of chlorofluorocarbons (CFCs) and several
related chemicals may reduce the concentration of stratospheric ozone
and, in so doing, may induce significant negative  effects  on human
health and a variety of economically important activities.  Emissions of
these "potential ozone depleters" depend fundamentally on their pat-
terns of production over time. For the United States and the world as
a whole, this  report  describes current  patterns of  use  and projects
future production levels for the seven most important potential ozone
depleters—CFC-11,  CFC-12,  CFC-113,  carbon tetrachloride, methyl
chloroform,  Halon 1211, and Halon  1301—over  the period 1985 to
2000.  The projections are based on detailed analysis of the major
applications of these chemicals.   The analysis is  particularly detailed
for  CFC-11 and CFC-12, which are believed to be the most important
potential ozone depleters.
  Table S.I summarizes the findings on estimated  current and pro-
jected use for the world  as a  whole.  Each projection  includes a
midrange estimate  and a range of uncertainty around this estimate for
2000 that reflects three sources of uncertainty:
                            Table S.I

         ESTIMATED CURRENT AND PROJECTED WORLD USE OF
             POTENTIAL OZONE-DEPLETING SUBSTANCES

Use
(thousands of metric tons)

Average Annual
Projected in 2000
Chemical
CFC-11
CFC-12
CFC-113
Methyl chloroform
Carbon tetrachloride
Halon 1301
Halon 1211
1985
341.5
443.7
163.2
544.6
1029.0
10.8
10.8
Midrange
560
620
420
840
1550
20
20
Uncertainty (%)
-25 to +32
-26 to +34
-31 to +44
-26 to +34
-25 to +33
-38 to +59
-39 to +60
Growth
Lower
1.4
0.3
3.9
0.9
0.8
1.1
0.9
Rate (%)
Upper
5.2
4.3
9.2
5.0
4.8
7.6
7.6

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VI
    •  The rate of general economic growth,
    •  The rate of growth in demand for products using each chemical
       relative to the rate of general economic growth, and
    •  Economic, technical, and regulatory effects on demand for each
       chemical relative to the demand for the products in which it is
       used.

The projections assume  no change in the regulations of these sub-
stances relating to potential ozone depletion, although they do consider
other regulations such as the U.S. ban on land disposal of waste chlori-
nated solvents.
  CFC-11 and CFC-12 are used in a variety of applications.  Both  are
widely used as aerosol propellants.  CFC-11 is used extensively as a
blowing agent in manufacturing plastic foams and CFC-12  is widely
used  as a  refrigerant.  Carbon tetrachloride's principal use is  as a
chemical intermediate in  the  production  of CFC-11  and  CFC-12,
although it is also used as a solvent and grain fumigant. CFC-113 and
methyl chloroform are both solvents.  CFC-113 is widely used in  the
electronic industry,  whereas methyl chloroform  is a general purpose
solvent used in everything from  electronics  to  shipbuilding. Halon
1301 and 1211 are newly marketed fire extinguishants used to protect
valuable equipment.
  In  general,  production of these  chemicals  will likely grow in step
with the global economy, but average annual growth rates for individ-
ual  chemicals could range from near 0 to 8 and 9 percent over the next
15 years. CFC-113 and the Halons are likely to grow the fastest.
  Atmospheric modelers could use subjective probability distributions
for  chemical production, such as those reflected in the limits on  the
production  ranges shown in Table S.I, to construct emission scenarios.
In doing this,  they should  keep in mind  that the joint probability of
observing all low or all high growth rates is far smaller than the proba-
bility of observing a  low or high growth rate for any chemical individu-
ally.  Moreover, the growth rates for each chemical are probably corre-
lated  because  of  their relationship to  general economic growth.   To
construct emission  scenarios that account for the correlation among
individual chemical growth rates, we propose a method  and a resulting
set  of production scenarios in Camm and Hammitt (1986).  By taking
account of the time pattern  of emissions  from  various applications
these production scenarios can be translated to  emission  scenarios
similar to those reported in Quinn et al. (1986).
  In  assessing the  importance of each chemical to the possibility of
significant  depletion of  stratospheric  ozone (or other concerns,  like
climatic change), it  is not  appropriate to simply compare production

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                                                                 vn
levels. Both the fraction of production that is ultimately emitted and
the time pattern of emissions vary among chemicals.  Moreover, the
estimated effect of an equal quantity of each chemical on the ozone
differs dramatically, perhaps by a factor of one hundred or more for the
seven potential ozone depleters we consider. Thus, even though carbon
tetrachloride and methyl chloroform are produced in the largest quanti-
ties, CFC-11  and  CFC-12 are  probably the most important of the
chemicals considered here.  Consequently,  the  report examines their
use in the greatest detail.
   The  development  of the projections reported  here involves the
development of a transparent set of accounts that can be used to calcu-
late the joint implications of a  large number of necessarily subjective
judgments  about the future.   Wherever possible, we have sought the
best expert judgment available as a basis for these  projections.  In the
end, of course, the reader may disagree with judgments reported here.
To the full extent possible, we have attempted to make it as simple as
possible to trace the  implications of changes  in the assumptions that
underlie the current results.
   The accounts developed differ from one chemical to another to suit
differences in the quality of data available.  The production of CFC-11
and CFC-12  and U.S. chemical production  generally receive the most
attention because  data on other chemicals  and  regions are in  general
less complete.  Other world production  outside the communist coun-
tries receives  the next most detailed treatment, although gaps  in the
available data often require that we rely on U.S. data to infer produc-
tion  levels elsewhere.  Production in the communist countries  is the
most  difficult to analyze.  To  estimate  global totals we estimate com-
munist country  use based on the best available data, but these esti-
mates are the least certain of all.
   In  general, the accounts work from the bottom up, building from
information about chemical use in particular products and regions to
global production.  But this method does not always yield global totals
that  are  consistent with "top-down" information from other sources,
like the Chemical Manufacturers Association. We review our  differ-
ences with top-down sources and suggest a  way to  reflect them  in the
projections developed here.
   Rand's work on current and likely future  production of these chemi-
cals  is continuing,  particularly with  regard  to  U.S.  production.
Although the  information presented here represents the  best informa-
tion  we have today,  we  expect our  understanding of current  and
future trends to improve as the work proceeds.

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                  ACKNOWLEDGMENTS
  We  are  indebted to many individuals and organizations for assis-
tance in writing this report.  Much of the information contained in the
report  was obtained  through  intensive  interaction with  industry
representatives beginning in  the 1970s.  Over  this  period  a large
number of companies and trade organizations cooperated with Rand by
providing basic data, current estimates, and projections. Many of these
organizations  are  cited  within  the  report:  Others  wish to  remain
anonymous. We thank them all.
  Rand colleagues Arthur Alexander and Richard Salter painstakingly
reviewed earlier drafts, David Rubenson and Toshiya Hayashi collected
information on refrigeration applications,  and Jan Acton helped to
hasten review  and production of the report under stringent deadlines.
John Hoffman and Stephen Seidel of the U.S. Environmental Protec-
tion Agency helped to frame  the analysis and contributed numerous
specific suggestions.  In addition, we received valuable comments from
the Alliance for Responsible CFC Policy, John Wells, and other partic-
ipants  at the  EPA-sponsored workshop "Protecting the Ozone Layer:
Workshop  on Demand  and  Control  Technologies."  Mary  Vaiana
assisted in preparing the presentation  of the material to that workshop,
Patricia Bedrosian ably edited the final draft, and  Janet D'Amore, Chai
Fosterling,  Nancy Lees, and Alyce Shigg assisted  in preparation of the
manuscript.
  Especially in a research area as contentious as this,  none of the indi-
viduals and organizations that assisted us can be  presumed to agree
with all our conclusions.  As always, the authors  alone are responsible
for any judgments or remaining errors of fact.
                                IX

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                      CONTENTS


PREFACE	 iii

SUMMARY  	  v

ACKNOWLEDGMENTS 	 ix

FIGURES	xiii

TABLES	 xv
Section
   I.  INTRODUCTION	  1
         Current Applications  	  4
         Summary of Projected Use  	  7
         Organization of the Report  	 11

  II.  METHODOLOGY	 12
         Characterization of the Uncertainty About Projected
            Chemical Use  	 12
         Projected Growth in GNP	 14

  III.  AEROSOL PROPELLANTS	 17

  IV.  RIGID FOAM	 22
         Rigid Urethane Foam	 23
         Nonurethane Foam  	 26

  V.  FLEXIBLE FOAM  	 31
         Slabstock Foam	 31
         Molded Foam 	 34

  VI.  REFRIGERATION AND AIR CONDITIONING
           SYSTEMS 	 39
         Mobile Air Conditioning	 39
         Retail Store Refrigeration	 42
         Home Refrigerators and Freezers	 44
         Chillers  	 47

 VII.  MISCELLANEOUS USES OF CFC-11 AND CFC-12	54
         Sterilants  	 54
         Liquid Food Freezing  	 54
         Other Miscellaneous Applications	55
                            XI

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Xll
VIII.  SOLVENTS 	 57
        CFC-113	 58
        Methyl Chloroform  	 61
        Carbon Tetrachloride	 63

 IX.  FIRE EXTINGUISHANTS  	 68
        Historical U.S. Use  	 69
        Current and Future Reporting Country Use	 70

  X.  USE OF POTENTIAL OZONE DEPLETERS IN THE
          COMMUNIST COUNTRIES  	 74
        CFC-11 and CFC-12 Use	 74
        Solvent Use  	 76

 XL  CONCLUSIONS	 79
        United States and Global Projections  	79
        Directions for Future Work	 84

Appendix
  A.  ESTIMATES OF CURRENT CONSUMPTION OF
        CFC-11, CFC-12, METHYL CHLOROFORM, AND
        CARBON TETRACHLORIDE	 87
  B.  COMPARISON OF ESTIMATED TOTAL CFC-11
        AND CFC-12 USE WITH OTHER SOURCES	93
  C.  DERIVATION OF SUBJECTIVE CREDIBILITY
        INTERVALS 	101

REFERENCES  	105

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                         FIGURES
 1.1.   Estimated CMA Reporting Country and U.S. Use of
      CFC-11, by Product	   5
 1.2.   Estimated CMA Reporting Country and U.S. Use of
      CFC-12, by Product	   6
 3.1.   Estimated Historical and Projected U.S. Use of CFC-11
      and CFC-12 in Aerosols  	  19
 4.1.   Estimated Historical and Projected U.S. Use of CFC-11
      and CFC-12 in Rigid Foam	  29
 4.2.   Estimated Historical and Projected Reporting Country
      Use of CFC-11 and CFC-12 in Rigid Foam  	30
 5.1.   Estimated Historical and Projected U.S. Use of CFC-11
      in Flexible Foam	  37
 5.2.   Estimated Historical and Projected Reporting Country
      Use of CFC-11 in Flexible Foam  	38
 6.1.   Estimated Historical and Projected U.S. Use of CFC-11
      and CFC-12 in Refrigeration and Air Conditioning	52
 6.2.   Estimated Current and Projected Reporting Country
      Use of CFC-11 and CFC-12 in Refrigeration and Air
      Conditioning	  53
 8.1.   Estimated Historical and Projected U.S. Use of
      CFC-113, Methyl Chloroform, and Carbon
      Tetrachloride  	  66
 8.2.   Estimated Current and Projected Reporting Country
      Use of CFC-113, Methyl Chloroform, and Carbon
      Tetrachloride  	  67
 9.1.   Estimated Historical and Projected U.S. and Reporting
      Country Use of Halon 1301 and Halon 1211   	  73
10.1.   Estimated Historical and Projected Use of CFC-11 and
      CFC-12 in the Communist Countries  	  77
11.1.   Estimated Historical and Projected Use of CFC-11 and
      CFC-12 in the United States	  81
11.2.   Estimated Historical and Projected Use of CFC-11 and
      CFC-12 in the Reporting Countries   	82
                              Xlll

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                         TABLES
S.I.  Estimated Current and Projected World Use of
     Potential Ozone-Depleting Substances 	   v
1.1.  Estimated 1985 World Use of Potential Ozone-Depleting
     Substances	   2
1.2.  Estimated Current and Projected World Use of Potential
     Ozone Depleters  	   8
1.3.  Estimated Current and Projected World Use of CFC-11  . .   9
1.4.  Estimated Current and Projected World Use of CFC-12  . .  10
2.1.  Projected Base GNP Growth Rates  	  15
3.1.  Estimated Historical Use of CFC-11 and CFC-12
     in Aerosols	  18
3.2.  Estimated Current and Projected Use of CFC-11 and
     CFC-12 in Aerosols  	  20
4.1.  Estimated Historical U.S. Production of Rigid Urethane
      Foam  	  23
4.2.  Estimated Historical U.S. Use of CFC-11 in Rigid
     Urethane Foam	  24
4.3.  Estimated Historical Reporting Country Use of CFC-11
     in Rigid Urethane Foam	  24
4.4.  Estimated Current and Projected U.S. Use of CFC-11
     in Rigid Urethane Foam	  25
4.5.  Estimated Current and Projected Reporting Country
     Use of CFC-11 in Rigid Urethane Foam  	  26
4.6.  Estimated Historical U.S. Production of Nonurethane
     Foam and Use of CFC-12 	  27
4.7.  Estimated Current and Projected U.S. Use of CFC-12
     in Nonurethane Foam  	  28
4.8.  Estimated Current and Projected Reporting Country
     Use of CFC-12 in Nonurethane Foam	28
5.1.  Estimated Historical U.S. Production of Slabstock
     Foam and Use of CFC-12	  32
5.2.  Estimated Current and Projected U.S. Use of CFC-11
     in Slabstock Foam	  33
5.3.  Estimated Historical Reporting Country Use of CFC-11
     in Slabstock Foam	  34
5.4.  Estimated Current and Projected Reporting Country
     Use of CFC-11 in Slabstock Foam	34
5.5.  Estimated Historical U.S. Production of Automotive
     Vehicles, Molded Foam and Use of CFC-11	35
                              XV

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XVI
  5.6.  Estimated Current and Projected Reporting Country
       Automotive Vehicle Production and Use of CFC-11
       in Molded Foam  	  36
  6.1.  Estimated Historical and Projected U.S. Vehicle Sales
       and Use of CFC-12 in Mobile Air Conditioning	41
  6.2.  Estimated Current and Projected Reporting Country Use
       of CFC-12 in Mobile Air Conditioning 	  41
  6.3.  Estimated Historical and Projected U.S. Use of CFC-12
       in Retail Food Refrigeration  	  43
  6.4.  Estimated Current and Projected Reporting Country
       Use of CFC-12 in Retail Food Refrigeration  	44
  6.5.  Estimated Historical and Projected U.S. Home Refrigerator
       and Freezer Sales and Use of CFC-12	  45
  6.6.  Estimated Historical World Production of Home
       Refrigerators	  46
  6.7.  Estimated Current and Projected Reporting Country
       Use of CFC-12 in Home Refrigerators and Freezers  	47
  6.8.  Estimated Historical and Projected U.S. Centrifugal
       Chiller Installations and Use of CFC-11 and CFC-12  ....  48
  6.9.  Estimated Current and Projected Reporting Country Use of
       CFC-11 and CFC-12 in Centrifugal Chillers	49
 6.10.  Estimated Historical and Projected U.S.
       Reciprocating Chiller Installations and Use of CFC-12  ...  50
 6.11.  Estimated Current and Projected World Use of CFC-12
       in Reciprocating Chillers  	  51
  7.1.  Estimated Current and Projected Use of CFC-12 in
       Liquid Food Freezing	  55
  7.2.  Estimated Current and Projected Use of CFC-11 and
        CFC-12 in Other Miscellaneous Applications  	56
  8.1.  Estimated Historical and Projected U.S.
       Use of CFC-113	  59
  8.2.  Estimated Current and Projected Reporting Country Use
       of CFC-113	  60
  8.3.  Estimated Historical and Projected U.S. Use of Methyl
       Chloroform	  62
  8.4.  Estimated Current and Projected Reporting Country
       Use of Methyl Chloroform  	  62
  8.5.  Estimated Historical U.S. Use of Carbon
       Tetrachloride 	  64
  8.6.  Estimated Current and Projected Reporting Country
       Use of Carbon Tetrachloride	  64
  9.1.  Estimated Historical U.S. Use of Halon 1301	69

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                                                           XV11
 9.2.  Estimated Current and Projected Reporting Country
      Use of Halon 1301	  71
 9.3.  Estimated Current and Projected Reporting Country
      Use of Halon 1211	  71
10.1.  Estimated Historical Soviet Union and Projected
      Communist Country Use of CFC-11 and CFC-12	75
10.2.  Estimated Current and Projected Communist Country
      Use of CFC-113, Methyl Chloroform, and Carbon
      Tetrachloride  	  78
11.1.  Estimated Current and Projected U.S. Use of Potential
      Ozone-Depleting Substances	  80
11.2.  Estimated Current and Projected World Use of Potential
      Ozone-Depleting Substances	  80
 A.I.  Regression Estimates of Reporting Country CFC-11
      and CFC-12 Production  	  89
 A.2.  Reported and Predicted Reporting Country CFC-11 and
      CFC-12  Production  	  89
 A.3.  Regression Estimates of U.S.  CFC-11 and CFC-12
      Production	  91
 A.4.  Reported and Predicted U.S. CFC-11 and CFC-12
      Production	  91
 A.5.  Regression Estimates of U.S.  Methyl Chloroform and
      Carbon Tetrachloride Production	  92
 A.6.  Reported and Predicted U.S. Methyl Chloroform and
      Carbon Tetrachloride Production	  92
 B.I.  Comparison of Estimated 1985 CFC-11 Use	94
 B.2.  Comparison of Estimated 1985 CFC-12 Use	  95
 B.3.  Comparison of Rand Estimates of 1976 and 1985
      U.S. Nonaerosol CFC-11 and  CFC-12 Use	96
 B.4.  Comparison of Rand and DuPont Estimates of 1976
      U.S. Nonaerosol CFC-11 and  CFC-12 Use	98
 B.5.  Estimated Shortfall in Rand 1976 Estimates of U.S.
      CFC-11  and CFC-12 Use Compared with DuPont
      Estimates	  99

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                     I.  INTRODUCTION
   Release of several chlorofluorocarbons (CFCs) and related chemicals
to the atmosphere may reduce the concentration of ozone in the strato-
sphere.   Almost all emissions of these chemicals  result from  human
activities. Depletion of stratospheric ozone would increase the amount
of ultraviolet  radiation that  penetrates to the earth's surface, poten-
tially causing  increases in human  skin cancers and adverse effects on
plants,  animals, and marine  life.  In addition, when these substances
are released to the atmosphere  they may reduce the radiant cooling of
the earth, thereby creating a  "greenhouse effect," possibly warming the
earth's  surface and changing its climate.1
   Potential ozone-depleting  chemicals are used  in a  wide range  of
products. They are used to manufacture  foam cushioning and insula-
tion products,  as  the  refrigerant in refrigeration  and air conditioning
systems,  as  solvents  to clean  electronic and other  components  in
manufacturing  processes,   and   as   aerosol  propellants  and  fire
extinguishants.  This  report  describes the major world uses of  these
chemicals, estimates the current quantities used in each product area,
and projects future use to 2000.
   Estimates of  current  use and  projected future  use are reported
separately for  the  United States,  the  other non-communist countries,
and the communist countries.  This distinction is  relevant because we
have much better information on  U.S. than on foreign use  of most of
these chemicals, and  better  information  on non-communist than on
communist use.  Nearly all  of the production  of  CFC-11 and CFC-12
outside the communist countries is by companies that report their pro-
duction to the  Chemical Manufacturers Association (CMA); production
in the  communist countries  is  not reported.  Consequently, we divide
the world into  three regions for analysis:  the United States, the "other
reporting countries,"  and the  "communist countries"  (including  the
Soviet Union, Eastern Europe,  China, and the other communist Asian
nations). The non-communist  countries are jointly called the "report-
ing countries."2
   !For more information on the atmospheric processes and possible adverse conse-
quences see Ramanthan et al. (1985) or National Academy of Sciences (1976, 1979, 1982,
1984).
   2We treat annual production and use of the chemicals within regions as equivalent,
since inventories and net regional imports and exports are generally small. As described
in Appendix A, however, the difference between production and use in a single nation,
the United States for example, may  be significant.  Systematic data on imports and

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   The chemicals discussed in this report are limited to those believed
to pose the  greatest threat to stratospheric ozone, if such  a threat
exists, as indicated by  computer models  that  simulate atmospheric
chemistry. They  include  CFC-11, CFC-12, CFC-113, methyl chloro-
form, Halon  1211, Halon 1301, and carbon tetrachloride. Current con-
sumption  estimates for  the three world  regions are  summarized  in
Table 1.1.
   Carbon tetrachloride  and methyl chloroform  are produced  in the
greatest quantities but are  not considered the most important potential
ozone depleters.  Carbon tetrachloride is used primarily  as a chemical
intermediate  in the production of CFC-11 and CFC-12, so the quanti-
ties  that  may be  emitted are  only a fraction of total production
estimated here.3 Although  most methyl chloroform is used as a solvent
and  eventually released  to the atmosphere, it is relatively unstable  in
the atmosphere and  consequently more likely to decompose  without
reaching the  stratosphere.
   CFC-11 and CFC-12  are considered  the most important potential
ozone depleters because of their high production  levels and  relative
depletion  potency.  CFC-113 use is significantly smaller, but CFC-113
is thought to be almost as effective a  potential depleter as the two
other CFCs.

                             Table  1.1

              ESTIMATED  1985 WORLD USE OF POTENTIAL
                   OZONE-DEPLETING SUBSTANCES
                          (In thousands of mta)
              Chemical
               Other
       United Reporting  Communist
World  States Countries  Countries
CFC-11
CFC-12
CFC-113
Methyl chloroform
Carbon tetrachloride
Halon 1301
Halon 1211
341.5
443.7
163.2
544.6
1,029.0
10.8
10.8
75.0
135.0
73.2
270.0
280.0
5.4
2.7
225.0
230.0
85.0
187.6
590.0
5.4
8.1
41.5
78.7
5.0
87.0
159.0
0.0
0.0
            "Metric tons.
exports of each chemical needed to estimate the size of the difference are apparently not
publicly available, however.
   See Quinn et al. (1986) for a more explicit analysis of possible chemical emissions.

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   The Halons are produced in only small quantities, about  11,000 mt
each worldwide. However, they contain bromine, which may be a much
more effective ozone depleter per atom than the chlorine contained in
the other  substances.  Although the  Halons  may  not be  important
potential  ozone depleters at present,  their use is  expected to grow
rapidly and they may become more important in the  future.
   As shown by Table 1.1,  the United States  currently accounts for
about one-quarter to  one-half of world use of these potential  ozone
depleters.  The U.S. share of specific applications of CFC-11  and CFC-
12 is generally similar, except for use in aerosols where, because of a
U.S. ban  on CFCs in "nonessential" aerosol applications, the United
States accounts for only about 5 percent of world use.  Use in the com-
munist countries is estimated to be less than 20 percent of  the  global
totals. Because of the limited data available  on communist use,  the
text focuses on use in the CMA reporting countries.  Estimates of com-
munist use are derived in Sec. X.
   An important feature of  these chemicals is their  chemical stability:
They do not  readily react  with others. This stability  contributes to
their safety and usefulness in a variety  of applications but also to their
potential threat to stratospheric ozone.  Because of  this stability most
of these chemicals are believed to survive in the atmosphere 50 to  100
years or  longer, so their concentrations in  the  lower atmosphere may
remain high for many years after release. Only a small fraction  of the
molecules of these chemicals in the lower atmosphere is transported to
the stratosphere; there it is decomposed by ultraviolet radiation and
the  freed  halogen  atoms  may  catalytically  react with the  ozone
molecules. Consequently, if depletion occurs it may persist for decades,
even if emissions are terminated.  The  radiative effect of these chemi-
cals as greenhouse gases would also be persistent.
   Differences in the time pattern of chemical emissions between prod-
ucts may  be important.  In  some applications, such as aerosol propel-
lants, the chemicals are released directly to the atmosphere as the aero-
sol product is used.   In other uses,  such  as home refrigerators,  the
chemical is contained in a hermetically sealed system and not emitted,
except for  minor leakage, until the product is disposed of. If disposed
of before the seals are broken it is theoretically possible to recover the
chemical and so prevent emission, although it may not be practical.  In
cases like this the chemical constitutes a bank that may be released
sometime in the future, or possibly never released.
   Other  chemicals may also affect the concentration of stratospheric
ozone. Most  of those that are suspected ozone depleters are  simple
organic molecules containing either chlorine or  bromine. Other  gases,
including  methane  and oxides  of nitrogen,  may increase or decrease

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stratospheric ozone concentrations, depending on the concentrations of
other perturbants.  Carbon dioxide emissions are believed to generally
increase  ozone concentrations.  These gases are  being examined in
other research efforts funded by the Environmental Protection Agency
(EPA) and other agencies.  However, none of the other potential ozone
depleters is thought to be  as likely to pose a threat as the chemicals
discussed  here.  The other chemicals may  be  less important  either
because they are produced in smaller quantities or because they are less
likely to reach the stratosphere.  Perhaps the most widely used of these
less important chemicals is CFC-22, which  is extensively used as the
refrigerant in air conditioners and other refrigeration equipment.
CURRENT APPLICATIONS

  The seven chemicals we discuss are used in the  following applica-
tions:  aerosol dispensers, rigid foam insulation and related products,
flexible cushioning foams, refrigeration and air conditioning systems,
solvents, fire extinguishants, and other products.
  CFC-11  and CFC-12 are used in diverse  applications.  In the CMA
reporting countries, CFC-11 is used almost  entirely  as an aerosol pro-
pellant and as  a  blowing agent in producing rigid and flexible foams.
As shown by Fig. 1.1, these three uses account for an estimated 90 per-
cent of reporting country use.  Most of the remainder represents the
difference between the sum of our estimates of CFC-11 use in each
product area  and total use, based on  total  production as reported by
CMA (1985) for the last several years (see Appendix A for details).
  In  the  United States,  CFC use  in  "nonessential aerosols"  was
banned by  the EPA effective in 1979 (the ban was announced in 1977).
As a result, aerosols account for only about 5 percent of U.S. CFC-11
use, whereas  rigid foams account for  about  half. The manufacture  of
flexible foam accounts for about one-fifth, similar to its share of world
use.  The unallocated  uses, about  18 percent, represent the difference
between  the applications for which we estimate current use and 1985
domestic use  estimated from  U.S.  International Trade Commission
(ITC)  production data (see Appendix A). We believe that part of the
unallocated use of CFC-11  is in refrigeration and air conditioning (see
Appendix B).  In addition, it includes storage, packaging, and transport
losses that  may account for about 2 percent  of use (see Wolf, 1980).
  Reporting  country and U.S. use of CFC-12 are shown in Fig. 1.2.
An estimated 32 percent of CFC-12 use in the reporting countries is  as
an aerosol  propellant, whereas 27 percent is used in the refrigeration
applications we analyze, including mobile air conditioning,  retail food

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                  CMA Reporting Countries
                       (300,000 mt)
                                     United States
                                      (75,000 mt)
                  Unallocated
                     (8%)
       Chillers (3%
 Flexible molded
      (4%)
 Flexible
slabstock
  (15%)
                        Rigid foam
                          (39%)
Aerosol
 (31%)
                       Unallocated
                         (18%)
             Chillers (6%)

                Flexible
                molded
                  (5%)
                                                                 Flexible
                                                                 slabstock
                                                                  (15%)
                                           Aerosol
                                             (5%)
                                                                                                           Rigid foam
                                                                                                             (51%)
              Fig. 1.1—Estimated CMA reporting country and U.S.  use of CFC-11, by product

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                                                                                                                               cr>
                     CMA Reporting Countries
                           (365,000 mt)
                                        United States
                                        (135,000 mt)
          Unallocated
             (22%)
Miscellaneous
    (7%)
   Home
refrigerators
   (3%)

 Chillers (1%)-
   Retail food
 refrigeration (3%)
                      Mobile
                  air conditioning
                      (20%)
                                                Aerosol
                                                 (32%)
Rigid
foam
(12%)
                      Unallocated
                         (31%)
  Miscellaneous
     (10%
Home refrigerators
      (2%)
                                                                                             Aerosol
                                                                                              (4%)
                        Chillers (1%)  Retail
                                     food
                                  refrigeration
                                     (4%)
                                             Rigid
                                             foam
                                             (11%)
    Mobile
air conditioning
    (37%)
               Fig.  1.2—Estimated CMA reporting country and U.S. use of CFC-12, by product

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refrigeration, chillers (large commercial and industrial air conditioning
systems),  and home refrigerators  and freezers.  The unallocated uses
total 22 percent.
   In the  United States, aerosols account for only about 4 percent of
use, about the same share as of CFC-11.  The refrigeration applications
account for 44 percent, of which mobile air conditioning is by far the
largest  component.  The unallocated uses are about 31  percent of
estimated total domestic use.  As discussed in Appendix B, we suspect
that a large part of the unexplained use of CFC-12 is in food refrigera-
tion applications, both in  the  United  States  and  abroad.   Again,
storage, packaging, and transport  losses may account  for about 2 per-
cent of total use.
   The other chemicals are concentrated in fewer applications.  Methyl
chloroform  and  CFC-113 are used  almost  exclusively as  solvents.
CFC-113 is used largely in the electronics industry to  "deflux" printed
circuit boards and clean plastic parts  including semiconductors; methyl
chloroform is a general purpose solvent used in many types  of metal
and other cleaning applications.  A small amount of  CFC-113  is also
used in  specialty refrigeration applications.
   Carbon tetrachloride is produced in larger quantities than any of the
other chemicals  but  most  is  transformed into  CFC-11  or  CFC-12.
Additional carbon tetrachloride is used as a solvent, as a grain fumi-
gant,  and in the pharmaceutical industry, but  chemical producers in
the United States have agreed to stop using it as an active ingredient
in pesticides by 1986.
   Halon 1211 and Halon 1301 are relatively new  and are produced in
small but growing quantities.  They  are used as  fire extinguishants,
Halon  1301 primarily  in  total flooding systems used  to  protect com-
puter installations and other expensive equipment, Halon 1211 pri-
marily in hand-held extinguishers.
SUMMARY OF PROJECTED USE

   Table 1.2 summarizes current and projected annual global use of the
seven potential ozone depleters we analyze. As described in Sec. II, our
projections include a base production level assuming continuation of
current and foreseeable trends and a range of uncertainty surrounding
the base projection.  They assume no change in  the perceived likeli-
hood of regulations on use or emissions  of these chemicals because of
the  threat of potential ozone depletion.  Thus,  they are meant to
characterize future use in the absence  of additional  regulations on
potential ozone depleters as such.  The projections do account for the

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                            Table 1.2

          ESTIMATED CURRENT AND PROJECTED WORLD USE
                 OF POTENTIAL OZONE DEPLETERS
                         (In thousands of mt)

                                         2000 Use

Chemical
CFC-11
CFC-12
CFC-113
Methyl chloroform
Carbon tetrachloride
Halon 1301
Halon 1211

1985
Use
341.5
443.7
163.2
544.6
1029.0
10.8
10.8

Base
Use
560
620
420
840
1550
20
20
Annual
Base Growth
Rate (%)
3.3
2.3
6.5
3.0
2.8
4.4
4.2

Range of
Uncertainty
-140 to +180
-160 to +210
-130 to +180
-220 to +290
-390 to +510
-8 to +12
-8 to +12
possibility of other regulations, such as the U.S. ban on land disposal
of chlorinated solvents and regulations affecting substitute chemicals.
  Table 1.2 characterizes the projections in terms of the projected base
level of use, the average annual growth rate necessary to achieve that
base level, and the range of uncertainty about the  future level of use.
Recall that the chemicals differ in the degree to which they may reduce
the concentration of stratospheric ozone because of differences in emis-
sion patterns and chemical reactions in the atmosphere.  Although car-
bon tetrachloride is produced in the largest quantities, because its dom-
inant use is  as a chemical intermediate only a  small fraction of current
production is released to the atmosphere (we estimate about 6 percent;
see Quinn et al., 1986).  Similarly, methyl chloroform, despite its  large
production volume, is not believed to be as important a potential ozone
depleter as the three CFCs, because much of it decomposes in the lower
atmosphere.  In contrast, the Halons  are thought to be very potent
ozone depleters and thus merit attention despite their low production
levels.
  The seven chemicals  may be divided into two groups on the basis of
their expected future growth rates.   As shown in Table 1.2, the baseline
projections for  CFC-11,  CFC-12, methyl chloroform, and carbon tetra-
chloride involve growth at an average annual  rate of about 3 percent.
In contrast, CFC-113 and the two Halons are projected  to grow much
more  rapidly:  Their base  projections  entail about 4  to  6 percent

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average growth until 2000.  This contrast reflects a fundamental differ-
ence between the two groups of chemicals:  The first,  slowly growing
group includes chemicals that have been produced for many years and
have found applications in a variety of uses.  In contrast,  the second
group is composed of "specialty" chemicals that are used in  a narrower
set of applications but are making rapid inroads in these markets.
   Table 1.2 indicates that absolute uncertainty about  future produc-
tion is  greatest  for  carbon  tetrachloride  and  methyl  chloroform,
because  of their  high production levels. Future CFC-12 production is
somewhat less certain than future CFC-11 production.  The range for
CFC-113 is  almost  as broad as for  CFC-11, in  part  because  the
expected growth  rate  is higher.  In contrast,  the ranges  for the Halons
are significantly smaller because of their low  production  levels.
   Tables 1.3  and 1.4 report the projected use of CFC-11 and CFC-12
in each application.4 CFC-11 is used primarily as an aerosol propellant

                              Table 1.3

      ESTIMATED CURRENT AND PROJECTED WORLD USE OF CFC-11
                           (In thousands of mt)

                                           2000 Use
Applications in
Reporting Countries
Aerosol
Foam production
Rigid
Slabstock
Molded
Refrigeration and
air conditioning
Centrifugal chillers
Miscellaneous and
unallocated uses
Communist countries
Total world use
1985
Use
93.7

115.8
45.0
12.0


9.9

23.6
41.5
341.5
Annual
Base Base Growth Range of
Use Rate (%) Uncertainty
95

260
74
12


11

39
100
560
0.1

5.5
3.4
0.3


0.9

3.4
6.0
3.3
-37

-67
-26
-4.2


-3.2

-9.8
-30
-140
to

to
to
to


to

to
to
to
+59

+89
+39
+6.2


+4.3

+13
+42
+180
  4The range of uncertainty for total use of the chemicals cannot be derived by adding
the ranges for each application. As explained in Sec. II the ranges represent subjective
80 percent credibility regions.  The region for total use derived by adding the regions for
each application would correspond to a much higher credibility level.  See Camm and

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10
                              Table 1.4

      ESTIMATED CURRENT AND PROJECTED WORLD USE OF CFC-12
                           (In thousands of mt)

                                           2000 Use
Applications in
Reporting Countries
Aerosol
Foam production
Rigid
Refrigeration and
air conditioning
Mobile air cond.
Retail food refrig.
Home refrigeration
Centrifugal chillers
Reciprocating chill.
Miscellaneous and
unallocated uses
Communist countries
Total world use
1985
Use
115.6

42.8


73.4
9.7
10.2
3.7
1.3

108.3
78.7
443.7
Annual
Base Base Growth Range of
Use Rate (%) Uncertainty
120

76


110
6.4
22
4.3
0.5

140
160
620
0.1

3.9


3.0
-2.7
5.2
1.0
-5.7

1.7
5.0
2.3
-46

-31


-34
-3.5
-7.6
-1.2
-0.3

-38
-53
-160
to

to


to
to
to
to
to

to
to
to
+72

+51


+48
+7.3
+ 11
+1.6
+0.5

+51
+75
+210
and as a blowing agent in foam manufacturing.  Growth trends in these
applications  are very  dissimilar, however.   Use  in aerosols in  the
reporting countries is projected to remain approximately constant.  In
contrast, use in rigid foams is projected  to grow rapidly, with a base
projected growth rate above 5 percent.  Largely because of this  higher
expected growth, the absolute  uncertainty about CFC-11 use in  rigid
foam is substantially larger than the uncertainty about aerosol use.
   Aerosol use of CFC-12 is also expected to remain about constant, as
shown in Table  1.4.   The next largest applications are mobile air condi-
tioning and rigid foam production.  Growth in these areas is expected
to be strong, although the corresponding  ranges of uncertainty include
nearly constant  use in each area.
Hammitt (1986) for more detail on our method for calculating the ranges. Because of
approximations in that method the projected total base use does not equal the sum of the
base uses in each application.

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                                                                11
ORGANIZATION OF THE REPORT
  Section II describes the methodology used to project future chemical
use in each product area and to characterize the uncertainty associated
with each projection.  The following sections describe the diverse prod-
ucts in  which the  chemicals  are used  in  more  detail  and report
estimated current U.S. and  other reporting country use and projected
use to 2000.
  The products are  described in roughly decreasing order  of  their
potential threat to stratospheric ozone,  as measured by the quantities
of potential ozone-depleting  chemicals used, adjusted for their approxi-
mate estimated ozone-depletion potency.  Within product  areas,  indi-
vidual  products are also discussed in decreasing order of importance.
Sections  III through VII describe  reporting country use of CFC-11 and
CFC-12 in aerosol products, in manufacturing rigid foams for insula-
tion and  other applications,  flexible foams for cushioning, as a refriger-
ant in  refrigeration and air conditioning systems, and in miscellaneous
uses.
  Section VIII describes solvent and other uses of CFC-113, methyl
chloroform,  and carbon tetrachloride  (which is used primarily  as a
chemical intermediate in CFC-11  and CFC-12 production).  Section IX
describes  fire extinguishant applications  of Halon 1301  and Halon
1211.  Section X estimates  current and future use of all seven of the
potential  ozone-depleting substances we  consider  in  the  communist
countries.  Section  XI summarizes the analyzed  product applications
and compares them with total use reported by the CMA and the U.S.
ITC.
  Supporting material  is included in three appendices.  Appendix A
documents our method for estimating 1985 total use of the chemicals
for  which reported production data are available.  Appendix B  com-
pares the sum of the estimates of current use in each major application
of  CFC-11 and CFC-12 to the  total  production  reported  by other
sources.  It then attempts to determine the source of the differences by
comparing the estimates in this report with other sources. Appendix C
elaborates on the method for characterizing the uncertainty about pro-
jected use described in Section II.

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                    II. METHODOLOGY
   The  descriptions  of product  use and manufacturing processes are
based on intensive interaction with industry that began in the 1970s.
Over this period a  large number  of industrial companies and trade
organizations cooperated with Rand by providing basic data,  current
estimates, and  projections.  More detailed descriptions  of nonaerosol
CFC use in the United States can be found in Palmer et al. (1980).
   To date, most of our information has come from U.S. manufacturers
and trade associations. Although we are actively pursuing information
outside  the United States, our current  data are necessarily more lim-
ited.
   Projections of future chemical use in each application are based on
analysis of historical trends, industry projections, and comments.  In
many cases we project product use to remain a constant share of the
U.S.  or other national or regional economy—that is, to grow at a rate
equal to the corresponding Gross National Product (GNP).
   As we obtain additional  information our estimates of current and
likely future  use  will inevitably  change.  In a  project of this nature
there can never be a "final word,"  only a most recent estimate.  This
report summarizes our information as of early 1986.
CHARACTERIZATION OF THE UNCERTAINTY ABOUT
PROJECTED CHEMICAL USE

   Projecting the outcome of future events is always a hazardous under-
taking.  In this report we project a range of possible chemical uses in a
number of applications.  For expositional clarity we characterize each
range by a base projection and a range of uncertainty for the year 2000.
The base projection is intended to  characterize the middle of the distri-
bution  of  credible future outcomes.   The  range of  uncertainty  is
described by two  numbers that indicate the approximate upper and
lower ends of what appears to us to be the range of reasonable out-
comes, relative to  the base projection.  More precisely, we think that
the probability that the  future outcome  will fall within the correspond-
ing range is 0.8:  Thus the ranges represent subjective 80 percent credi-
bility intervals.
   An alternative style for presenting our projections would be to report
the limits of the range  of uncertainty directly, without a central base
projection.  However, this style of exposition would  assign too much
                                12

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                                                                   13
legitimacy to the bounds of the range, which  are  inherently fuzzy. It
would  also make the procedure for calculating the projections  and the
assumptions used less transparent.
   Although we report a range of uncertainty for chemical use  only for
2000, projected use in earlier years should also be characterized by a
range.  In most situations the range should be smaller for years closer
to the  present.  If  required, we suggest that the appropriate ranges for
earlier years be calculated by assuming that  the annual growth rates
are  normally  distributed,  calculating  the corresponding means  and
standard  deviations implied by the range for 2000, and from these cal-
culating the desired credibility intervals.1
   The base projections that  characterize the center of the range of
projected use are based on current and anticipated trends in chemical
use in  each application. They assume no unanticipated shocks, such as
changes  in the perceived likelihood that  use will be regulated because
of concern about possible  ozone depletion,  or unexpected  changes in
relative prices. Moreover,  we do  not attempt to project  short-term
oscillations in  use associated with business cycles but  instead  try to
characterize the basic trends.
   The limits of the ranges  of reasonable uncertainty are derived from
explicit consideration of three levels of uncertainty:

     •  Uncertainty  about  the  level  of general  economic  activity,
       described by the GNP,
     •  Uncertainty about final product use conditional on GNP,  and
     •  Uncertainty about  the use of  the chemical per unit  of final
       product, conditional on  final  product use.  Chemical  use per
       unit of product may change because of changes  in the relative
       costs of alternative  manufacturing technologies  resulting from
       technological innovation,  regulation, or changes  in real input
       prices.

   We  assess ranges of reasonable uncertainty  for each of the three lev-
els of uncertainty and combine them to produce an overall range using
the  procedure  described in  Appendix C.2 The range of uncertainty
about  GNP growth is common to  all of the product applications.  It is
described in the following  subsection.  The other  ranges are based on
       Camm and Hammitt (1986).
   2We use log-normal distributions to approximate our subjective probability distribu-
tions corresponding to each level of uncertainty. Although the uae of log-normal distri-
butions imposes some restrictions on the character  of the  uncertainty  that can  be
represented, they provide close approximations to our subjective distributions in most
cases.  The assumption that chemical use is distributed log-normally is equivalent to the
assumption of normally distributed growth rates.

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14
our knowledge  of  specific product  areas and our beliefs about what
changes might reasonably occur within the next 15 years.
  Because part of the uncertainty about use in each application—that
due to uncertainty about general economic growth—is common to all
applications of a given chemical, derivation  of the range of uncertainty
for  total use of a chemical  requires accounting for this  correlation
among uses.  The reported  ranges  of  total CFC-11 and CFC-12 use
account for this correlation using the procedure described in  Camm
and Hammitt (1986).
  The chemical use projections do  not explicitly account for  uncer-
tainty about current use.  As noted in Sec. I, our "bottom  up" estimates
of use in each major application do not account for all of the CFC-11
and CFC-12 currently used.  There  may be other significant uses we
have not  analyzed, or our estimates for current use in some  of the
applications may be too low.  It would  be possible to develop a  subjec-
tive range of uncertainty for current use, both in applications  and in
total, and to incorporate this uncertainty with the uncertainty about
future growth.  However, we have not  yet taken this step.  If future
information reveals our estimates of current  use in a specific applica-
tion to  be too low we would recommend  revising the corresponding
range of projected use upward.
  Our ranges of uncertainty are reported in  the discussion of  each
product area.  Readers who find our  intervals inappropriate are  invited
to supply their own and see  how it affects  the  final range for  total
chemical use.
PROJECTED GROWTH IN GNP
   In many of the baseline projections final products are assumed to
remain a constant share of a nation's economy, that is, to grow at the
same rate  as  the GNP. The base GNP  growth  rates we assume are
reported in Table 2.1.   With one  exception, the rates are based  on
those prepared by Edmonds et al.  (1984) for the U.S. Department of
Energy.  These projections are a revision  of the rates used in  our ear-
lier work projecting long-term growth (reported in Quinn et al., 1986).
They are based on analysis of likely population and labor productivity
trends  and, compared  with other published projections,  are low to
moderate.3
   The one difference between our rates and the Edmonds et al. (1984)
projections is  for the United States.  Edmonds et al. (1984) project a
   3See Quinn et al. (1986), Appendix B.

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                                                                   15
                              Table 2.1

                PROJECTED BASE GNP GROWTH RATES
                          (In percent per year)

                          Region            1985-2000
                United States                     3.0
                Western Europe and Canada         2.8
                Japan, Australia, and New Zealand     4.0
                USSR and Eastern Europe           2.4
                Centrally Planned Asia              4.5
                Mideast                         6.6
                Africa                          3.7
                Latin America                     5.3
                South and East Asia               5.1
                Other reporting countries            3.5
                Communist countries               3.0
                World                          3.3
base growth rate of 2.7 percent per year. For the period 1985 to 1990
we  have  increased the  base  rate  to  3.5  percent,  consistent with
Congressional  Budget Office  (1985)  projections.  This estimate  is
slightly lower than the prominent alternative of 4.0 percent suggested
by the Council of Economic Advisors (1985).  After 1990 we adopt the
Edmonds et al. (1984) projection of 2.7 percent per year.  The resulting
average rate over the 15 year period is 3.0 percent.
  For most  product  areas  we do  not disaggregate use in  the CMA
reporting countries outside the United States. Rather we use an aggre-
gate growth  rate of  3.5  percent for other  reporting country  GNP
growth, which is the appropriate aggregate  of the regional rates  in
Table 2.1.
  As described above, we assessed  ranges of uncertainty around the
base GNP growth rates.   For the United States our  intervals include
growth  rates  1.5  percent  higher or lower than the base projections.
Thus, our intervals extend  from 1.5 to  4.5 percent per  year over the
period.  These intervals are based on the  observation that, since World
War II, U.S.  growth has  averaged between about  1.5  and 4.5 percent
per year over periods of about a decade.   For  the other CMA reporting
countries we  use the  same  range of uncertainty  as  for  the United
States, plus or minus 1.5  percent from the base, or 2.0 to 5.0 percent
per year.  Although uncertainty about  growth in  some parts  of the
world is  greater  than for the United States,  variations in  different

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16
regions will tend to partially offset one another so the range of uncer-
tainty  about the growth of the total is less than the range for  an indi-
vidual  country.  For the communist countries we use a wider range,
plus or minus 2.0 percent (a range of 1.0 to 5.0 percent averaged over
the period). We  feel that a wider range is appropriate for these coun-
tries because we  have less information  about their likely growth and
because the communist countries constitute  a smaller region than the
other reporting countries, and hence variations within the region are
less likely to offset each other. The ranges of uncertainty implied by
these ranges of possible growth rates are between 0.80 and 1.25 times
the base projected GNP level in 2000 for both the United States and
the other reporting countries, and between 0.74 and 1.35 times  the base
projected level in the communist countries.

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             III.  AEROSOL PROPELLANTS
   CFC-ll and CFC-12 are used  extensively as propellants  in  a  wide
variety of aerosol products. Many of these are personal care products,
such as deodorant, perfume,  and hairspray;  others  include household
products such as insecticides and drain cleaners, and household and
industrial products, such  as  spray paints  and lubricants.  Substitute
propellants  include hydrocarbons and  carbon dioxide, and  in some
applications aerosol cans  can be replaced by  pump dispensers or other
nonpressurized applicators. CFCs are more expensive than the alterna-
tive  aerosol propellants but they are not flammable like hydrocarbon
propellants, and some of their attributes make them technically more
attractive in limited applications.
   Because the propellant  is emitted as  the aerosol is discharged emis-
sions are typically prompt.  Before 1975  aerosol use was the largest sin-
gle source of worldwide CFC emissions.
   Historical CFC use in aerosols is reported in Table 3.1 and Fig. 3.1.
In 1978 the EPA banned use of CFC propellants in  all aerosols except
a  limited  list  of  "essential  uses"  (including military applications).
Under the ban United States use fell about 95 percent from its  peak
(1973) level.1 Subsequently the  European Economic  Community nego-
tiated a 30 percent  reduction in use.  Current EEC use is about  45 per-
cent below use in the late  1970s, well below the target reduction, as the
voluntary reductions  have apparently stimulated increased substitution
of less expensive hydrocarbon and carbon dioxide propellants.
   United States use has remained constant at about 9500 mt since the
ban  and no significant change  is  expected.  We project constant use
with an uncertainty range of 78 to 128 percent of the projected value in
2000. This range is composed of uncertainty in the level of aerosol use,
conditional  on the GNP,  of  90 to 111 percent of the projected base
level, combined with the uncertainty  range for the U.S. GNP.
   Use in the European  Economic  Community has declined steadily
since the mid 1970s  as manufacturers  have substituted other  propel-
lants.   The  substitution  of pump dispensers  for aerosol cans is
apparently not occurring  to  the  extent it  did  in the United  States.
   !United States CFC use in aerosols fell substantially between 1973 and the announce-
ment of the ban in 1977. This decline is probably related to several factors including the
Arab oil embargo, anticipation of the regulation, and the discovery that additional aero-
sol products could be successfully marketed with non-CFC propellants.  (Some aerosols
were traditionally propelled without CFCs; for example, spray paint has usually employed
hydrocarbons.)
                                 17

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18
Fundamental uncertainty exists as to how much further CFC use will
decline there.  It is possible that all of the decline that will occur in the
absence of regulation has all ready occurred. Alternatively, reductions
in use could parallel those in the United States.  However, the level of
peak  use  is uncertain.  By analogy to the  United States, we assume
that the peak occurred in  1973  and  was 50 percent higher than  the
1976  level, that is, about  265,000 mt. If this estimate is  correct, 1983
use is about 37 percent of estimated peak (1973) use.
   We project EEC use to fall to about 50,000 mt or almost 20 percent
of the assumed peak by  2000.  As an  upper bound on  the  range of
uncertainty we use the current level of about 100,000 mt, since we do
not expect CFC use in aerosols to grow in the EEC.  The lower bound
is 25,000 mt or almost 10 percent of the assumed peak. This amount is
about twice the level of U.S. use (5 percent of peak use), which seems
reasonable assuming no further regulation in the EEC.
                             Table 3.1

    ESTIMATED HISTORICAL USE OF CFC-11 AND CFC-12 IN AEROSOLS
                               (In mt)
Year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
United
States8
156,400
161,400
185,000
212,700
198,600
162,700
138,600
79,500
40,000
9,500
9,500
9,500
9,500
9,500
9,500
EEC"
na
na
na
na
na
na
176,900
162,600
150,400
136,600
126,400
116,100
111,700
98,800
na
Japan0
na
na
na
na
14,400
14,000
15,500
14,000
13,300
12,900
13,000
12,500
12,000
11,800
11,800
Other
Reporting
Countriesd
na
na
na
na
na
na
101,200
94,700
103,500
95,600
94,200
83,500
75,300
91,900
na
Total
Reporting
Countries'
na
na
na
na
na
na
432,300
350,800
307,200
254,600
243,300
221,600
208,500
212,000
218,800
       NOTE:  na = not available.
       •Wolf (1980).
       bEuropean Fluorocarbon Technical Committee data as supplied by EEC.
       'Ministry of International Trade and Industry data as supplied by Japan
     Flon Gas Association (private communication, 1985).
       dTotal reporting countries less United States, EEC, Japan.
       'CMA (1985).

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    450
    400
   350
                                                                         NOTE: Earlier reporting country use not available
«?  300
E
8
   25°
    200
V)

16


I   150
    100
     50
          J	L
                                       Reporting Countries
                                       (total CFC-11 and CFC-12)
                                          U.S. (total CFC-11 and CFC-12)
                                            I    I   I    I   I	I	1  . I	1	1	1	1	1
                                                                                               J	1	L
      1970
1975
1980
1985

Year
                                                                         1990
                                                                    1995
                                                                    2000
          Fig. 3.1—Estimated historical and projected U.S. use of CFC-11 and CFC-12 in aerosols

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20
  Japanese use has declined slowly, in part because of substitution of a
blend of CFCs and hydrocarbons. Since Japanese law prohibits using
pure hydrocarbons as aerosol propellants (because of fire hazards) any
substitution to other propellants  is presumably to carbon dioxide; sub-
stitution from aerosols to pumps may also be occurring. As these alter-
natives are technically inferior in many uses, we use a base  projection
for  Japanese CFC use equal to current production of about  12,000 mt
with a range of uncertainty from three-quarters to one and one-third
times that amount.
  Further growth is likely in the  industrializing nations, particularly in
East Asia. These countries are undergoing rapid economic growth and
are not party to the  international agreements restricting CFC use in
aerosols.  Our base projection assumes modest growth of 2.5 percent,
one-half the expected rate of GNP  growth.  We believe  growth could
reasonably range from one-half to twice as  fast.
  The  base projections are summarized  in Table  3.2 and Fig. 3.1.
They assume that the proportions of aerosol production accounted for
by each CFC remain constant at  the current reporting country propor-
tions: about 45 percent CFC-11 and 55 percent CFC-12. Note that the
projected declines in the EEC almost exactly offset projected growth in
the other reporting countries: Baseline projected use initially declines
then rises as the developing countries  account for a larger share of the
total.  Combined with the anticipated constant U.S. use, the offsetting
trends in the EEC and other reporting countries  produce  a nearly con-
stant base  projection for  reporting country  aerosol  use.  As noted
                              Table 3.2

            ESTIMATED CURRENT AND PROJECTED USE OF
                   CFC-11 AND CFC-12 IN AEROSOLS
                               (In mt)

                              Other Reporting    All Reporting
                United States       Countries       Countries
          Year  CFC-11  CFC-12  CFC-11  CFC-12  CFC-11  CFC-12
1985
1990
1995
2000
3,800
3,800
3,800
3,800
5,700
5,700
5,700
5,700
89,900
88,100
88,500
90,800
109,900
107,700
108,200
111,000
93,700
91,900
92,300
94,600
115,600
113,400
113,900
116,700

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                                                                      21
above, the range of uncertainty for U.S. use is between 78 and 128 per-
cent of  projected base  use in 2000.  Outside  the United States  the
range is  from about 60 to 165 percent of projected base use in 2000.2
   2This calculation  assumes that use is correlated across regions, with a correlation
coefficient of 0.75.

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                      IV.  RIGID FOAM
  CFC-ll and CFC-12 have been used to produce rigid or "closed-cell"
foams since the early 1960s. These products are widely used for insula-
tion and packaging.
  CFC-ll and CFC-12 are used as blowing agents to form the holes or
cells when the foam is  manufactured.  In closed-cell foams the CFCs
remain  trapped  inside, diffusing  only slowly  to the  atmosphere.
Because of the low thermal conductivity of the CFCs,  these foams are
about twice  as effective insulators  as equally thick nonfoam alterna-
tives.  Foam  sheets or  boards are sometimes clad with  aluminum,
paper,  or asphalt sheathing to  slow the  diffusion of air into the foam
and thus slow the degradation of its insulating capacity.1
  There are two major types  of closed-cell  foams:  rigid urethane or
isocyanurate  foam, usually produced  using  CFC-ll, and  nonurethane
foam, usually produced with CFC-12.  Rigid uretharie foam accounts
for  the second largest share of world CFC-ll  use, after aerosols, and by
far  the largest share  of U.S.  CFC-ll use.  Rigid urethane foams are
better  insulators than the  nonurethane foams, and over 90 percent of
these foams  are  used  as  insulation  in residential,  commercial, and
industrial construction, in home and commercial refrigerators, and in
refrigerated  trucks and  railroad cars.  Insulating foam is  made into
sheets  or boards that are installed during construction, sprayed directly
onto tanks,  pipes, and  other structures, or  foamed in place, as inside
the walls of a refrigerator.  Noninsulation applications include flotation
devices, marine buoys and use  as a packaging material to  protect valu-
able and delicate objects during shipment.
  The  most  important CFC-consuming nonurethane foams—extruded
polystyrene  (PS)  sheet  and extruded  PS board—use smaller quantities
of CFC-12.  PS sheet products include  meat trays,  egg cartons,  plates,
and other food containers. Extruded  PS board was introduced by Dow
Chemical Company during World War II under the trade name Styro-
foam.  It is  used  primarily as  insulation and competes  directly with
rigid urethane foam in the residential and  commercial wall and roof
sheathing market.
   Insulating capacity may be degraded by changes in the amount and composition of
gas retained in the foam, which apparently depend on complicated diffusion and dissolu-
tion processes. See Mooz et al. (1982).
                                 22

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                                                                   23
RIGID URETHANE FOAM

   Rigid urethane foam is used primarily for insulation in construction,
refrigeration, and transportation applications.  Table 4.1 presents his-
torical U.S. foam use in these markets.
   We estimate that each kilogram  of foam  requires an  average  of
about 130 grams of CFC-11 to produce.2 From the quantities of CFC-11
required per unit  of foam  we  estimate CFC-11  use by  application,
reported in Table  4.2.  As shown, the construction market currently
accounts for about two-thirds of CFC-11 use, refrigeration for one-fifth,
and transportation for one-ninth. Estimated reporting country use of
CFC-11  in rigid urethane foams is  presented in Table 4.3.  United
States use accounts for about one-third of the total.
   The markets for rigid urethane insulating foam are closely related to
the construction industry and tend to follow similar cycles.  However,
growth in most insulation markets has been strong and is expected to
continue. Our base projections for U.S. use are reported in Table 4.4.
   In the United States and Western  Europe, growth in rigid foam use
in construction averaged 12 percent  annually  between 1976 and 1981
(before the major recession in the early 1980s; see Table 4.3), whereas
U.S.  growth has historically averaged 5 to 8 percent  (see Table 4.2).

                              Table 4.1

              ESTIMATED HISTORICAL U.S. PRODUCTION OF
                        RIGID URETHANE FOAM
                                 (In mt)
Year
1978
1979
1980
1981
1982
1983
1984

Construction
131,000
154,000
142,000
163,000
152,000
163,000
177,000
Insulation
Refrigeration
45,000
48,000
48,000
50,000
48,000
50,000
53,000

Transportation
21,000
22,000
18,000
22,000
16,000
21,000
32,000
Other
18,000
20,000
18,000
11,000
10,000
11,000
12,000
Total CFC-
Blown
215,000
244,000
226,000
246,000
226,000
245,000
274,000
         SOURCE:  Modern Plastics (various issues).
   Specifically, we estimate the following average quantities of CFC-11 to produce one
kilogram of foam for each application: 126 (construction), 140 (refrigeration), 136 (trans-
portation), and 137 (other applications).  See Palmer et al. (1980) Tables III.C.2, F.2, and
F.3.

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24
                              Table 4.2

  ESTIMATED HISTORICAL U.S. USE OF CFC-11 IN RIGID URETHANE FOAM
                                (In mt)
Year
1978
1979
1980
1981
1982
1983
1984
Construction
16,500
19,400
17,900
20,500
19,200
20,500
22,300
Refrigeration
6,300
6,700
6,700
7,000
6,700
7,000
7,400
Transportation
2,900
3,000
2,400
3,000
2,200
2,900
4,400
Other
2,500
2,700
2,500
1,500
1,400
1,500
1,600
Total
28,200
31,900
29,500
32,000
29,400
31,900
35,700
                              Table 4.3

           ESTIMATED HISTORICAL REPORTING COUNTRY USE
                  OF CFC-11 IN RIGID URETHANE FOAM
                                 (In mt)

Year
1976
1977
1978
1979
1980
1981
1982
1983
1984

United
States8
18,500
21,800
28,200
31,900
29,500
32,000
29,400
31,900
35,700

EEC"
20,100
21,500
27,300
29,000
33,400
35,200
na
na
na
Other
Reporting
Countries0
13,500
21,900
10,600
19,200
21,200
30,500
na
na
na
Total
Reporting
Countries'1
52,100
65,200
66,100
80,100
84,100
97,700
94,900
na
na
              NOTE:  na = not available.
              "From Table 4.2.
              bBased on industry sources.
              Calculated as total reporting countries less United States
           and EEC.
              dCMA reports.

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                                                                 25
                             Table 4.4

            ESTIMATED CURRENT AND PROJECTED U.S. USE
                 OF CFC-11 IN RIGID URETHANE FOAM
                               (In mt)
Year
1985
1990
1995
2000
Construction
24,100
35,400
45,200
57,600
Refrigeration
7,600
8,700
9,800
11,100
Transportation
4,800
7,800
9,900
12,700
Other
1,800
2,000
2,000
2,000
Total
38,300
53,900
66,900
83,400
The base projections for U.S. use in Table 4.4 assume that high growth
averaging 8 percent will persist  through  1990,  followed by 5 percent
average growth to the end of the century.
  The  refrigeration  market is  relatively mature and historic U.S.
growth  has been similar  to  the  GNP. The  base  projections  assume
growth slightly slower than the GNP, 2.7  percent to 1990 and 2.5 per-
cent thereafter.
  The transportation market accounts for only a small share  of  use
but is  growing most  rapidly, nearly doubling in the first half of  the
1980s.  The current 15 percent growth rate is unlikely to be sustained,
however.  Our  base projections  assume that  the rate will average  10
percent for the remainder of the decade and 5 percent over the next
decade.
  The noninsulation  rigid urethane markets declined significantly dur-
ing the early 1980s and never recovered to mid  1970s levels.  Here, we
assume that they recover only slightly further, leveling off at 200 mt of
CFC use by 1990.
  Table 4.5 presents base  projections for reporting country  use of
CFC-11 in rigid foams.  Rigid  urethane foam use  in Western Europe
has historically been similar to  U.S. use and the projections assume
similar growth. Other reporting countries have apparently experienced
more  rapid growth (according to CMA reports), which is reasonable,
since they are undergoing more rapid economic development.  The base
projections  assume that  the entire rigid  urethane markets  in these
countries will grow at the same  rate as the rapidly growing construc-
tion markets in the United States and Europe, an average of 8 percent
through 1990 and 5 percent thereafter.
  To estimate the range  of uncertainty about the  base projections we
start with the uncertainty about  the size of final product markets con-
ditional on GNP.  Because  these are well established, at least in  the
developed  economies, we believe that uncertainty is similar  to  the

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26
                            Table 4.5

          ESTIMATED CURRENT AND PROJECTED REPORTING
          COUNTRY USE OF CFC-11 IN RIGID URETHANE FOAM
                              (In mt)


Year
1985
1990
1995
2000

United
States
38,300
53,900
66,900
83,400
Other
Reporting
Countries
77,500
111,100
139,600
175,900
Total
Reporting
Countries
115,800
165,000
206,500
259,300
uncertainty about general economic growth, between 0.8 and 1.25 times
the projected level.  Additional uncertainty concerns  the share of the
final product markets that will be served by CFC-11, since there exist a
number of other insulating products, such as fiberglass, extruded poly-
styrene board, and particle board, that are competitive in some applica-
tions.  In contrast, the use of CFC-11-blown foam  seems secure in
applications where the foam is sprayed or  poured in place.  Conse-
quently, we doubt that rigid urethane foams will lose more than 20 per-
cent, or gain more than 25 percent,  of their current share. Combining
these ranges produces an  overall range of uncertainty of 73 to 137 per-
cent of projected base use.
NONURETHANE FOAM

   The major  nonurethane products are extruded polystyrene board,
used for  commercial and residential insulation, and extruded polysty-
rene sheet, used in egg cartons  and food service trays. Jointly, they
account for about two-thirds of the CFC-12 used in nonurethane foam
products.  Table 4.6 presents historical U.S. production of these foams
and estimated CFC-12 use. CFC-12 use per unit of nonurethane foam
is about  95 grams per kilogram  of foam, smaller than CFC-11 use in
rigid urethanes.
   CFC-12 is the primary blowing agent for extruded polystyrene sheet,
but use declined during the late  1970s and early 1980s. Palmer  et al.
(1980) estimate CFC-12 use in 1976 assuming that 64 percent of poly-
styrene sheet  is CFC-blown  (the remainder  uses pentane) and that

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                                                                27
                            Table 4.6

            ESTIMATED HISTORICAL U.S. PRODUCTION OF
              NONURETHANE FOAM AND USE OF CFC-12
                              (In mt)

                   Extruded PS Board    Extruded PS Sheet
             Year   Foam     CFC-12      Foam    CFC-12
1976
1977
1978
1979
1980
1981
1982
1983
1984
na
na
na
31,000
27,000
32,000
30,000
34,000
39,000
1,900
2,300
2,500
2,900
2,600
3,000
2,900
3,200
3,700
na
na
na
151,000
147,000
140,000
146,000
153,000
184,000
5,900
7,300
7,800
7,600
7,400
7,000
6,600
6,500
7,200
               SOURCES:  Foam production from Modern Plas-
             tics (various issues).  CFC-12 use before  1979 from
             Palmer et al. (1980), after 1979 calculated from foam
             production (see text).
               NOTE: na = not available.
CFC-blown  foam  contains  7.8  percent CFC-12 by weight.   During
recent years, however, a mixed blowing agent combining CFC-12 and
carbon dioxide has reduced the CFC requirement by about 25 percent.
By 1984, we calculate CFC-12 use in polystyrene sheet assuming that
two-thirds of the foam uses 5.85 percent CFC-12 by weight.
   Other nonurethane  foams including expanded  polystyrene  foam
(used for drinking cups) and the polyolefins are manufactured in large
quantities but require only small amounts  of CFC blowing agents.  In
the absence of direct data on CFC  use in these products we  assume
that use grows at the same rate as in the extruded polystyrene foams.
   Table 4.7 provides a  base projection for U.S. use of CFC-12  in rigid
foams.  For extruded PS board, we assume growth comparable to that
of rigid polyurethane insulation with which it competes. The base pro-
jections for use in polystyrene  sheet and in the other  nonurethane
category grow with GNP.
   Table 4.8 presents  base projections for reporting country use of
CFC-12 in  nonurethane foam.  Our base  projections have the  same
growth rates outside the United States  as within.  Since about half of
CFC-12 use in nonurethane foams is for extruded  polystyrene sheet,
which faces a variety of competing products  such  as cardboard egg

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28
                            Table 4.7

           ESTIMATED CURRENT AND PROJECTED U.S. USE
                 OF CFC-12 IN NONURETHANE FOAM
                              (In mt)
Extruded Polystyrene
Year
1985
1990
1995
2000
Board
4,000
5,900
7,500
9,600
Sheet
7,500
8,900
10,200
11,600
Total
11,500
14,800
17,700
21,200
Other
Nonure-
thanes
3,400
4,000
4,600
5,300
Total
Nonure-
thanes
14,900
18,800
22,300
26,500
cartons and food serving trays, and because some of these products can
also be made with pentane, we believe that there is significant uncer-
tainty  about  CFC-12 use conditional on the size of  these packaging
markets.   We  suggest a range  of  uncertainty  for  CFC-12 use  in
nonurethane  foam from 60 percent of the  projected level, if CFC-12-
blown  polystyrene sheet were to lose 80 percent of its market, to 167
percent of the projected level if it were to displace many of its competi-
tors.  Combining these with  the range of uncertainty about  GNP
growth produces a range of uncertainty of 57 to 172 percent of the base
projections.
  Figures 4.1 and 4.2  summarize historical and base  projected use  of
CFC-11 and  CFC-12 in rigid  foams, in  the  United States and all
reporting countries, respectively. Note that the rigid urethanes account
for  the majority of CFC use in rigid foam.

                            Table  4.8

          ESTIMATED CURRENT AND  PROJECTED REPORTING
           COUNTRY USE OF CFC-12 IN NONURETHANE FOAM
                              (In mt)


Year
1985
1990
1995
2000

United
States
14,900
18,800
22,300
26,500
Other
Reporting
Countries
27,900
35,200
41,800
49,600
Total
Reporting
Countries
42,800
54,000
64,100
76,100

-------
                                           Annual use (thousands of mt)
oo
r*
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i—i.
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           -i O
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-------
   400
           NOTE: Historical CFC-12 use not available
    1976
1980
1996
                                                                                                     2000
                                                                                                                  CO
                                                                                                                  o
Fig. 4.2—Estimated historical and projected reporting country use of CFC-11 and CFC-12 in rigid foam

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                   V.  FLEXIBLE FOAM
  CFC-ll is widely used to produce flexible foams, which first came
into use in the 1950s.  Because these foams are resilient, durable, and
relatively inexpensive they are now widely used in  furniture, bedding,
carpet underlay, automobile seats and dashboards, and packaging appli-
cations.
  There are two major processes for producing flexible foams.  Most
foam is manufactured in the form of slabstock, which is a piece of foam
typically about six feet wide, four feet high,  and from six to 200 feet
long.  Final  shapes are cut from this large slab.  The second process
molds foam  into its final shape, which  is often rounded or has other
features that would make it difficult or  costly to carve from slabstock.
Molded foam is used almost exclusively  for automobile seats and seat-
backs.
  The important characteristics of flexible foam are imparted by blow-
ing agents that form the  holes or cells in the foam and give it flexibil-
ity.  All flexible  foams  use  carbon dioxide  as the primary  blowing
agent. To produce softer (less dense) foams requires  augmenting the
carbon  dioxide with  an  auxiliary  blowing agent,  either CFC-ll  or
methylene chloride.  Since the carbon dioxide is produced by  reacting
water with TDI (toluene diisocyanate), foams produced without  aux-
iliary blowing agents are called water-blown.
  Flexible foams are often called "open-cell," since their cells are open
to the atmosphere. As a  result, CFC emissions are prompt: The blow-
ing agent escapes from the foam within a matter of hours or days after
its manufacture.
SLABSTOCK FOAM
  Table 5.1 presents estimated U.S. production of slabstock foam and
CFC-ll used.  Foam production is reported  in  Mobay (1982-1985).
CFC-ll use is based on estimated use of 50 grams per kilogram of
CFC-blown  slabstock foam.  CFC-ll use  peaked in the  late 1970s,
declined through  1982, and is currently increasing.  The decline was
primarily due  to reduced foam production during the recession, but it
also reflects reduced use of CFC-ll  per unit of foam because of substi-
tution to the less expensive methylene chloride.  Currently, methylene
chloride and CFC-ll each account for about half of the auxiliary blow-
                                31

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32
                             Table 5.1


                     ESTIMATED HISTORICAL U.S.
                     PRODUCTION OF SLABSTOCK
                      FOAM AND USE OF CFC-12
                               (In mt)
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
Foam
380,000
439,000
472,000
473,000
425,000
409,000
369,000
414,000
448,000
CFC-11
11,400
12,900
13,600
13,300
11,700
11,000
9,700
10,600
11,200
ing agent  used.1 Further  substitution to methylene chloride is  not
expected because the cost savings will not offset the necessary invest-
ment in learning to produce sufficiently high quality foam.  Future use
of methylene chloride may even decline because of concerns about its
potential carcinogenicity and possible  regulation.  A new alternative
blowing process has been recently patented.  According to its Belgian
developers, the new process is less expensive, can be used to produce
all  densities of foam,  and uses  no auxiliary blowing agent  (CMR,
February 28, 1983).  If these claims prove correct, adoption of this new
process could lead to substantial reductions in CFC-11 use.
   Industry sources expect slabstock foam production to  grow at the
same rate as the GNP (Mobay, 1985).  Table 5.2 reports our base pro-
jections for U.S. production of slabstock foam and CFC-11 use, assum-
ing that CFC-11 use per unit of foam remains at its current level.  We
suggest that these projections are  subject to the following range of
uncertainty.  First, the  uncertainty concerning GNP growth  implies
that total use could be about  20 percent smaller or 25 percent greater
than  the base projection by 2000. We treat  the uncertainty about the
growth of  the  final product markets, conditional on a given level of
GNP, as negligible.  The level of CFC use,  conditional on the size of
the final product markets, is  subject to substantial uncertainty, how-
ever.  Considerable substitution away from CFC-11 to either methylene
        CFC-11 use averages 25 grams per kilogram of slabstock foam.

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                                                                  33
                             Table 5.2

                      ESTIMATED CURRENT AND
                       PROJECTED U.S. USE OF
                     CFC-11 IN SLABSTOCK FOAM
                               (In mt)

Year
1985
1990
1995
2000
Slabstock
Foam
459,400
545,600
623,400
712,200
CFC-11
Used
11,500
13,700
15,700
17,900
chloride or possibly to the alternative blowing method is possible.  As a
lower bound, we postulate that CFC-11 could lose one-half its share by
2000.  Conversely,  if  the costs of using  methylene chloride increase
substantially because of regulation, its share could be taken by CFC-11,
potentially doubling  CFC-11  use.  Combining  these ranges of uncer-
tainty produces a range  of uncertainty in  2000 of from 0.48 to 2.07
times the projected base level.
   Estimated reporting country use  of CFC-11 in slabstock foam is
reported in  Table  5.3.2  We  estimate  non-U.S.  use by subtracting
estimated U.S.  use derived above.  Assuming that  non-U.S.  use of
CFC-11 in slabstock foam will also grow with the GNP  of the respec-
tive  countries,  we project a future base level as shown in Table 5.4.
The  range of uncertainty  is similar to that for the United States, albeit
somewhat smaller.   Uncertainty about GNP growth implies that total
use could be 20  percent  smaller, or 25 percent larger,  than the pro-
jected baseline.  We believe that total slabstock foam markets, condi-
tional on GNP, could reasonably range between 80 and 125 percent of
the projected level.  Finally,  since methylene  chloride use is smaller
overseas than in the United States and concerns about its possible car-
cinogenicity are perhaps greater, the share of foam blown by CFC-11 is
likely to remain steadier than in the United  States:  We use an interval
from 0.83  to  1.20.  The  resulting range  for other reporting country
CFC-11 use in slabstock  foam falls  between 0.69  and 1.44 times the
base projection.
   2CMA details reporting country use of CFC-11 in all flexible foams. We estimate use
in molded foam by multiplying world vehicle production by the estimated quantity of
CFC-11 used per vehicle and attribute the remainder to slabstock production.

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34
                            Table 5.3

           ESTIMATED HISTORICAL REPORTING COUNTRY
                 USE OF CFC-11 IN SLABSTOCK FOAM
                             (In mt)
Year
1976
1977
1978
1979
1980
1981
1982
1983
United
States
11,400
12,900
13,600
13,300
11,700
11,000
9,700
10,600
Other
Reporting
Countries
20,500
26,000
25,500
22,800
26,900
26,500
22,900
31,300
Total
Reporting
Countries
31,900
28,900
39,100
36,100
38,600
37,500
32,600
41,600
                            Table 5.4

               ESTIMATED CURRENT AND PROJECTED
                 REPORTING COUNTRY USE OF CFC-11
                       IN SLABSTOCK FOAM
                              (In mt)


Year
1985
1990
1995
2000

United
States
11,500
13,700
15,700
17,900
Other
Reporting
Countries
33,500
39,800
47,300
56,100
Total
Reporting
Countries
45,000
53,500
63,000
74,000
MOLDED FOAM

   Molded foam is used almost entirely for seats and seatbacks in auto-
motive vehicles and its production is intimately related to total vehicle
production.  Table 5.5 reports  estimated historical U.S. use of CFC-11
in molded foams, molded foam production, and total automobile pro-
duction.  Manufacturers report that average use of CFC-11 per unit of
foam has been declining as they have  changed product  formulations,
substituted  methylene  chloride, adopted the  high resiliency process

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                                                                  35
                             Table 5.5

      ESTIMATED HISTORICAL U.S. PRODUCTION OF AUTOMOTIVE
             VEHICLES, MOLDED FOAM AND USE OF CFC-11
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
CFC-11
(mt)
3,900
4,100
4,300
4,300
3,000
2,800
2,500
3,000
3,200
Molded Foam
(mt)
156,000
164,000
178,000
177,000
131,000
126,000
118,000
145,000
162,000
Automotive
Vehicles
(thousands)
11,500
12,700
12,800
11,400
8,000
8,000
6,900
9,500
10,900
CFC-11 per
Vehicle
(grams)
340
322
333
373
376
347
360
320
297
         SOURCE: Vehicles, Automotive News, April 24, 1985.


(which requires no auxiliary blowing agent), and switched to foam den-
sities that can be produced using carbon  dioxide  alone.3 CFC-11 use
currently averages about  300  grams per vehicle.  We combine this fig-
ure with projected growth in  vehicle production to project CFC-11 use
in molded foam.
   Relying on industry sources, our base projections for vehicle sales in
the United States (total import and domestic sales) grow at 1.9 percent
per year, and sales in foreign  markets grow at 2.9 percent.  (CFC use is
allocated to the region  in which  the  car is  produced though not neces-
sarily sold.) To estimate CFC use outside the United States we assume
that foreign automobiles also  average 300 grams of CFC-11 per vehicle.
Table 5.6 summarizes  base projections for reporting country vehicle
production and CFC-11 use.
   Note that although the base projection for vehicle production grows
at 2.9 and 1.9 percent, the base projection for CFC-11  use  grows at
only 0.5 percent outside  the  United  States, and falls 0.4 percent per
year within the United  States. This  occurs because of the fundamental
uncertainty about future CFC-11 use in molded foam. We believe that
there is  little chance that CFC-11 use per vehicle will increase; how-
ever, substantial decreases are possible. Increases are unlikely because
   3Molded foams have always used less auxiliary blowing agent than slabstock foam.
Currently, we estimate that molded foams require an average of 20 grams per kilogram.
The average level of CFC-11 use per vehicle is more erratic than CFC-11 use per unit of
foam because of the changing average quantities of foam used per vehicle.

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36
                             Table 5.6

           ESTIMATED CURRENT AND PROJECTED REPORTING
             COUNTRY AUTOMOTIVE VEHICLE PRODUCTION
                 AND USE OF CFC-11 IN MOLDED FOAM
            United States
Other Reporting
   Countries
Total Reporting
  Countries
         Vehicles    CFC-11    Vehicles    CFC-11    Vehicles    CFC-11
   Year  (thousands) Used (mt)  (thousands)  Used (mt)  (thousands) Used (mt)
1985
1990
1995
2000
11,100
12,200
13,400
14,700
3,330
3,260
3,190
3,120
29,000
33,400
38,300
44,100
8,700
8,910
9,130
9,360
40,100
45,600
51,800
58,800
12,030
12,170
12,320
12,480
methylene chloride is  used much less frequently  for molded than for
slabstock  foam, so that substitution to CFC-11 would not be as large if
methylene chloride were to be regulated.  However, according to indus-
try sources it would be possible to  reduce CFC-11 use drastically by
switching to other, unspecified, processes for manufacturing automobile
seats.  Because of the possibility of substituting to methylene chloride,
high resiliency or water-blown foam,  CFC-11 use per vehicle  could
decline by half by 2000.  Consequently we project a baseline average
CFC-11 use per vehicle in 2000 to be only 212 grams, with a range of
uncertainty falling between 150 and the current level of 300 grams.
   Conditional on GNP, molded foam production could vary by a factor
of about 10 percent, depending on future trends in automobile sizes in
the United States and abroad.  Combining these ranges with the range
for GNP  growth  we  obtain an uncertainty range for  CFC-11 use in
molded foams in the United States and in other reporting countries of
65 to 153  percent of the base projections.
   Figures 5.1 and 5.2  summarize  historical and projected use of CFC-
11  in  flexible  foams  in  the United States  and  reporting countries.
Slabstock foam accounts for the majority of reporting country use.

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     40
en
"O

ca

13
O
CD
03


C
     35
     30
    25
20
15
     10
                                           Molded
                           I	 I	I
                                                           I    I    I
                                                                           I    I    I
                                                                                           I    I    I
     1976
                 1980
1984
1988

Year
1992
1996
2000
             Fig. 5.1—Estimated historical and projected U.S. use of CFC-11 in flexible foam

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03
to

o
0)
CO



75

c
120




110




100




 90




 80




 70




 60





 50




 40





 30




 20





 10
                                                                                                                       CO

                                                                                                                       00
            NOTE: Historical molded foam use not available
            i    i
      1976
                  1980
                                             Molded
                                                                  i	i
1984
1988


Year
1992
1996
2000
       Fig. 5.2—Estimated historical and projected reporting country use of CFC-11 in flexible foam

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 VI. REFRIGERATION AND AIR CONDITIONING
                          SYSTEMS
  CFC-ll and CFC-12 are used as refrigerants in a variety of systems.1
The largest quantities  are  used in home refrigerators  and freezers,
retail store refrigeration systems,  chillers (used for  cooling buildings)
and mobile (automotive) air conditioners.  Except for mobile air condi-
tioners, all of these  markets are well developed  in the United States
and Western Europe and little growth is expected there. Growth in the
developing countries  may be stronger.
  The refrigeration cycle consists of compression of the refrigerant fol-
lowed by cooling until it condenses to  liquid form,  and expansion to
allow evaporation of the liquid.  During evaporation the refrigerant
absorbs heat  from  the  refrigeration unit  and  then  returns  to the
compressor to repeat the cycle.   Since the  refrigerant  remains  in a
sealed system throughout the cycle, the CFC is not emitted until the
unit is disposed  of (except for quantities that leak from the system or
are emitted during servicing).
MOBILE AIR CONDITIONING

  Air conditioning in automobiles and other vehicles began as a luxury
item in the 1940s and has become commonplace in the United States
but remains a  rarity in  other countries.  Mobile air conditioners use
CFC-12 exclusively.  A CFC-22  system was used in the past but has
disappeared, presumably because  of the higher cost  and weight that
result from the higher pressures required.  As with other refrigeration
systems, emissions are generally low until disposal, although significant
emissions occur at servicing and when systems are damaged in automo-
bile accidents.
  Use of CFC-12 in mobile air conditioners depends on three factors:
the number of  new vehicles, the fraction that are air conditioned, and
the average amount of refrigerant used per  system.   The fraction of
new cars and trucks sold in the United States with air conditioning has
increased rapidly, from about 6 percent in 1960 to about 60 percent in
the 1970s.  Since then that number has remained stable at the current
   !When describing refrigerants the CFC prefix is often replaced by the letter R (for
refrigerant) or F (for Freon, a DuPont trademark).  Thus CFC-12 is frequently called
R-12 or F-12.
                                39

-------
40
level of 68 percent.2 The average refrigerant charge in domestic auto-
mobiles declined from about 1.7 kilograms (3.8 pounds)  to  1.3  kilo-
grams   (2.75  pounds)  between  1974  and  1985  as  systems  were
redesigned to  reduce leakage  and  weight and  smaller  automobiles
became more common. Further declines are not expected  unless vehi-
cles  become  smaller.  Charges  in imported  automobiles  are  smaller,
perhaps 0.9 kilograms  (2.0 pounds).
   Table 6.1  presents  historical and projected  baseline United States
vehicle sales  (total domestic and imported) and estimated CFC-12 used
in mobile air conditioning.  Note the decrease in CFC-12 use for 1978
through  1982 because of the  decline  in initial charge.   Annual use
includes the  initial charge  for new  units, manufacturing and installa-
tion  losses (about 10 percent of initial charge), replacement of routine
leakage (30 percent  of the  initial charge is assumed to be  lost every 5
years on  average),  other servicing  losses (10 percent of  stocks),  and
replacement  of accident-caused losses  (2.5 percent of stocks).  The
model for estimating use is  described in Palmer et al. (1980). The base
projections assume that United States vehicle  sales will  grow at 1.9
percent annually through  2000, as  industry sources  suggest,  and that
both the share of new vehicles that  are air conditioned and the average
charges will remain constant.
   Mobile air conditioning is much less  common outside the  United
States.  We estimate that about 20 percent of non-U.S. vehicles are air
conditioned (65 percent in  Japan, 34 percent in Canada, one-half per-
cent in the EEC, and negligible numbers elsewhere).3 Assuming that
average charges and losses are  the  same  as for imports to the United
States (0.9 kilograms average charge), annual use in the other reporting
countries is estimated as 23,000 mt.
   Relying on industry sources  we project the  number of  new  foreign
vehicles sold to grow at 2.9 percent annually.  We further  assume that
the share of  new vehicles that are air conditioned will grow to 30 per-
cent by 2000, a 50 percent increase from the estimated current level.
Combining these factors leads  to a baseline projection of 5.7 percent
annual growth as reflected in Table  6.2.
   Uncertainty about future domestic use  of CFC-12 in mobile air con-
ditioning  is based on uncertainty about total vehicle sales, the share
that are  air conditioned,  and  average charge.   We suggest  that the
   2This is the percentage of all new automotive vehicles, including both automobiles
and trucks, that are air conditioned.  The fraction of automobiles is higher, about 82 per-
cent of those produced domestically.
   3The Japanese share is reported  in Nihon Reito Kucho Kogyo Kai (1985), the EEC
share is from  confidential industry  sources, and the Canadian share is assumed to be
one-half the United States share because of the colder climate there.

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                                                                41
                            Table 6.1

               ESTIMATED HISTORICAL AND PROJECTED
                U.S. VEHICLE SALES AND USE OF CFC-12
                   IN MOBILE AIR CONDITIONING
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1990
1995
2000
Vehicles Sold
(millions)
13.28
14.84
15.43
14.13
11.46
10.80
10.54
12.31
14.48
14.76
16.21
17.81
19.57
CFC-12 Use
(mt)
44,890
50,780
52,800
50,910
47,570
47,860
47,670
48,650
50,350
50,400
54,800
59,900
65,400
                 SOURCE:  Historical vehicle sales, Automotive
               News, April 24, 1985.
                            Table 6.2

               ESTIMATED CURRENT AND PROJECTED
                 REPORTING COUNTRY USE OF CFC-12
                   IN MOBILE AIR CONDITIONING
                              (In mt)


Year
1985
1990
1995
2000

United
States
50,400
54,800
59,900
65,400
Other
Reporting
Countries
23,000
30,300
40,000
52,800
Total
Reporting
Countries
73,400
85,100
99,900
118,200
uncertainty  about vehicle  sales is  equivalent  to  that  about general
economic growth. The share of new vehicles with air conditioners has
remained at about two-thirds over the last decade, despite substantial

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42
changes in the size of automobiles.  We suggest a range of uncertainty
of plus or minus  10 percent of the current share.  Finally,  further
design changes affecting the average charge are not expected, but if the
average size of vehicles changes average charge could vary by perhaps
30 percent.  Combining these uncertainties yields an overall range of
uncertainty of 0.70 to 1.43 times the base projection.
   Outside the United States, the uncertainty about the share of new
vehicles with air conditioning is greater.  Accordingly, we suggest a
range of use conditional on GNP of 0.8 to 1.25 times the base projec-
tion, or an overall range of 0.67 to 1.50 times the base projection.
RETAIL STORE REFRIGERATION

   Retail food store refrigeration systems  are  used to refrigerate the
food and beverages in display cases and to store meat, produce, dairy
products,  frozen food, and ice cream in walk-in coolers.  Systems are
designed differently depending on whether they are for medium tem-
peratures  (storing dairy products) or low temperatures (storing frozen
foods).
   System design and choice  of  refrigerant are influenced by  energy
use, since refrigeration equipment  accounts for as much as half of a
typical  store's energy use.  CFC-12 is  usually used for medium tem-
perature systems, whereas most low temperature systems use CFC-502,
a blend of nearly equal parts of CFC-22 and CFC-115.  Some stores use
CFC-502 for medium temperature systems  as well, because of the con-
venience of handling only one refrigerant.   However, CFC-502 is sub-
stantially more expensive than CFC-12.
   CFC-22 was once  employed in both low and medium temperature
systems.  Currently it is used only rarely,  since it  generates excessive
heat in the compressor.
   The  average refrigerant charge increased during  the mid 1970s as a
number of energy saving features were adopted that required additional
refrigerant.   This trend will probably  continue to  some extent until
about  1990.  Eventually, the use of low pressure flooding  systems in
large supermarkets is expected to be  implemented extensively. One
industry source  estimates that this will lead to a 10 percent reduction
in average system charge.  Another trend  that may reduce refrigerant
use is  a decline in  leakage and servicing emissions as  older equipment
is replaced by newer designs.
   Table 6.3 presents historical United States data on the number of
retail food stores and their use  of CFC-12, and projections.  CFC-12
use  is  estimated using the model  described  in Palmer et al.  (1980),

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                                                                 43
which  simulates refrigerant use  in  four sizes of stores.  Annual  use
includes refrigerant used for charging new units (between about 60 and
1,100 kilograms, depending on size of store), in testing new units dur-
ing manufacture (about  2 percent of initial charge), and  in replacing
losses that occur during installation  (5 to 8 percent depending on store
size), leakage, and servicing (about 10 percent of refrigerant in use).
   The values in Table 6.3 show a decline in the total number of stores,
but a slight increase in refrigerant use over the period.  This reflects a
trend toward larger supermarkets and away from small grocery stores
that is expected to  continue in the future.  The effect of this trend is
partially offset by expected further substitution to CFC-502 in medium
temperature systems and lower leakage and servicing losses as newer
units with better integrity replace old units.
   The base projections for reporting country CFC-12 use  are given in
Table 6.4.  Industry sources indicate that foreign systems are  similar to
those in the United States and that use in  the other reporting coun-
tries is currently about equal  to  United States use. Future  growth is
expected to be  at the  same  rate  as  GNP, 3.5 percent  annually, some-
what more rapid than in  the United States
   Uncertainty  about CFC-12  use in retail  food stores can be divided
into uncertainty about the number of such  stores and about the aver-
age  charges  and types  of refrigerants used.  Uncertainty about  the
number of stores, conditional on the level of general economic activity,
is  small, plus or minus 10 percent.  The average charge is highly sensi-
tive to shifts between refrigerants. In recent years there has been some

                             Table 6.3

                     ESTIMATED HISTORICAL AND
                        PROJECTED U.S. USE OF
                        CFC-12 IN RETAIL FOOD
                          REFRIGERATION
Year
1976
1980
1985
1990
1995
2000
Number
of Stores
183,700
174,570
164,950
155,330
145,710
136,090
CFC-12
(mt)
4,820
4,830
4,850
4,620
4,910
5,200

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 44
                             Table 6.4

                ESTIMATED CURRENT AND PROJECTED
                 REPORTING COUNTRY USE OF CFC-12
                  IN RETAIL FOOD REFRIGERATION
                              (In mt)


Year
1985
1990
1995
2000

United
States
4,850
4,620
4,910
5,200
Other
Reporting
Countries
4,850
4,620
5,130
5,670
Total
Reporting
Countries
9,700
9,240
10,040
10,870
movement toward  use  of CFC-502 in medium temperature systems
because of the convenience of handling only the one refrigerant.  CFC-
502  could completely replace CFC-12 in  new  medium temperature
installations  by 2000. If it did CFC-12  use  would be reduced  by  as
much as 75 percent by 2000.4 Alternatively, if the average  refrigerant
charge per store continues  to increase after  1990,  use  of  CFC-12  in
2000 could be higher by perhaps 20 percent.  Combining these  uncer-
tainties we suggest a range for CFC-12 use of  0.25 to 1.33 times the
base projections in 2000.
HOME REFRIGERATORS AND FREEZERS

   In the early part of this century refrigerants such as methyl chloride,
ammonia,  and sulfur  dioxide were  employed in  home  refrigeration
equipment.  Since these chemicals are toxic, and some are also flam-
mable  or explosive, they are  not considered safe enough for home use.
CFC-12 has none of these drawbacks and has been used in all home
refrigerating equipment in the United States since at least 1946.
   Home refrigerators  currently use either a rotary  or reciprocating
compressor. The reciprocating-compressor machines require only one-
third to one-half as much refrigerant.  Historically, the average  charge
in a domestic  refrigerator was 280 grams (10 ounces)  and the average
   4Leakage and servicing use represent about half of refrigerant use.  Older units using
CFC-12 would still require CFC-12 for servicing. If half the medium temperature units
in service used CFC-502 by then, CFC-12 use would still account for one-fourth the pro-
jected use.

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                                                                  45
charge in a freezer was 430 grams (15 ounces). Today, refrigerators use
an average  of about 210 grams  (7.5 ounces) of  refrigerant, whereas
freezers require about 280 grams (10 ounces).5 Although refrigerators
outside the United States are typically smaller, we assume that initial
charges are  the same as in  current  U.S. practice,  about three-quarters
the historic U.S. level.  We assume that home freezer use outside the
United States is negligible.
   CFC-12 is used in home appliances for charging new units, in testing
and  rework at manufacturing, and  in replacing leakage and  servicing
losses.  The models  used to calculate  historical  and  future use are
described in Palmer et al. (1980).
   Table 6.5 reports historical and projected baseline  U.S. sales of
home  appliances and estimated use of CFC-12.  CFC-12 use declined
between 1976 and  1984 because of the  increased  use of  reciprocating
compressors in refrigerators, which require a smaller initial charge, and
because the  growth  in  freezers declined.  Since  the domestic  home
refrigerator  market is well saturated, we project future  growth slightly
below  the expected growth of GNP, 3 percent to 1990 and 2.5 percent
to 2000.  Freezer  sales were strong in the early 1970s  but have since
declined. We assume only 1 percent growth to 2000.

                             Table 6.5

                ESTIMATED HISTORICAL AND PROJECTED
                U.S. HOME REFRIGERATOR AND FREEZER
                       SALES AND USE OF CFC-12
Year
1976
1980
1984
1985
1990
1995
2000
Number of
Refrigerators
(thousands)
5,090
5,570
6,200
6,390
7,410
8,380
9,480
Number of
Freezers
(thousands)
1,740
1,670
1,340
1,360
1,430
1,500
1,570
CFC-12
(mt)
2,920
2,370
2,400
2,440
2,660
2,900
3,190
                  SOURCES:  Palmer et al. (1980), Mooz et al.
               (1982).
   Home refrigerators typically incorporate three to six times more CFC-11 blowing
agent in the insulating foam in their walls than CFC-12 refrigerant in their cooling sys-
tems.

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46
  Both reciprocating  and rotary compressors  are  competitive  in the
home appliance market. However, if their market shares were to shift
significantly  it  could  substantially affect  CFC-12  use.  At present,
about 25 percent of domestic refrigerators and 30  percent  of freezers
contain rotary compressors.  If  the share  of appliances using  rotary
compressors were to halve or double,  average initial charges could fall
25 percent or increase  by one-third by 2000.  Combined with the uncer-
tainty  over the total  number of home refrigerators and freezers pro-
duced (equivalent to the uncertainty about GNP) the range of uncer-
tainty  is from  0.7 to 1.43  times  the projected base for  CFC-12 use  in
2000.
  Table 6.6 reports estimated home  refrigerator production by world
region.  As a  baseline projection we assume that West European use
will halt its historical  decline and remain constant  at 11,000 mt annu-
ally  to  2000.  For the other reporting countries  we  set baseline pro-
jected growth at the same rate as from  1972 to  1981, 6.2  percent per
year. 6
  Table 6.7 reports our base projection  for reporting country CFC-12
use  in  home  appliances.  Uncertainty about use outside  the  United
States is greater, because of the  greater uncertainty about the average
charge  and how it may change.  We suggest a range  of 0.67 to 1.50

                             Table 6.6

             ESTIMATED HISTORICAL WORLD PRODUCTION
                      OF HOME REFRIGERATORS
                             (In thousands)
Region
Western Europe
North America (excl. U.S.)
South America
Asia (excl. USSR)
Africa
Oceana
Eastern Europe (excl. USSR)
USSR
Total
1972
12,110
830
1,330
4,550
330
450
2,510
5,030
27,100
Average growth
1981 rate (%)
10,990
1,350
2,800
7,710
510
460
3,340
5,930
33,100
-1.1
5.6
8.6
6.0
5.0
0.0
3.2
1.8
2.2
             SOURCE:  United Nations Statistical Office (1981).
   6Recall that we do not project use in the communist countries in this section; the data
 on communist countries in Table 6.6 is included for reference.

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                                                                  47
times the base projection in 2000 to account for the uncertainty about
average charge.  Combined with  uncertainty  about GNP growth  this
produces a range of uncertainty of 0.63 to 1.59 times projected use.
CHILLERS
   Chillers are air conditioning systems used in  large commercial and
industrial buildings.  The cooling system consists of a central unit that
chills a secondary refrigerant, typically water or brine, which is circu-
lated to cooling coils throughout the building.  Chillers may use either
centrifugal or reciprocating compressors. The centrifugal units use pri-
marily CFC-11 or CFC-12 and  have capacities ranging from 75 to
10,000 tons.7 The reciprocating units use  CFC-22 and CFC-12 and are
of smaller capacity, usually no more than 150 tons.
   Estimates of historical and projected baseline  CFC-11 and CFC-12
use are developed using a model described in Palmer et al. (1980).  Use
includes  the CFC used for  charging new units, for testing at manufac-
ture (about 5 percent of initial charge, falling over time), for replacing
losses during shipping and installation (4 percent of initial charge), and
for replacing leakage and servicing losses (about 7.5 and 10 percent of
banked refrigerant, respectively; estimated servicing losses decline over
time).

                              Table 6.7

                 ESTIMATED CURRENT AND PROJECTED
                 REPORTING COUNTRY USE OF CFC-12 IN
                 HOME REFRIGERATORS AND FREEZERS
                                (In mt)


Year
1985
1990
1995
2000

United
States
2,440
2,660
2,900
3,190
Other
Reporting
Countries
7,790
10,520
14,220
19,200
Total
Reporting
Countries
10,230
13,180
17,120
22,390
   'Refrigerating system capacities are traditionally rated in tons, where one ton is the
amount of heat required to melt one ton of ice in 24 hours or 200 Btu per minute. A
commercial or industrial building generally requires about one ton of cooling capacity for
every 300 square feet of floor area.

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48
Centrifugal Chillers

  The choice of refrigerant in a centrifugal chiller is also a matter of
size.  CFC-11 is used in about 80 percent of the  units, but these are
primarily small units (less than 500 tons), requiring an estimated 350
kilogram average charge.  CFC-12 is used in  about 10 percent of the
units, with an average charge estimated as 950 kilograms. The largest
units  (over 1,000 tons) are usually charged with CFC-22, CFC-114, or
CFC-500—a blend containing 74 percent CFC-12.  Average charges are
declining  slowly  as  manufacturers  make evolutionary advances  in
chiller design and reduce leakage.
  Table 6.8 presents historical estimates of domestically installed cen-
trifugal  chillers and attendant CFC-11  and CFC-12 use and our base
projection for future use. The number of chillers grew steadily between
1976 and 1981 and then declined slightly, perhaps because of the reces-
sion.  CFC  use  over the period  increased by only about  10 percent
because of a decrease in servicing losses from an estimated 16 percent
of stocks in 1976 to about 10 percent in 1985.  Note the slower growth
in CFC  use  after 1985 because of projected further decreases in servic-
ing  losses, to 5 percent of stocks by 2000.

                             Table 6.8

             ESTIMATED HISTORICAL AND PROJECTED U.S.
                CENTRIFUGAL CHILLER INSTALLATIONS
                    AND USE OF CFC-11 AND CFC-12
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1990
1995
2000
Centrifugal
Chillers
1,930
1,910
2,280
2,350
3,090
3,580
3,210
3,470
3,420
3,580
4,490
5,260
5,750
SOURCES: Chillers,
CFC-11
(mt)
3,910
3,900
4,010
4,020
4,260
4,440
4,330
4,400
4,360
4,380
4,840
4,950
5,400
1976-1980,
CFC-12
(mt)
1,460
1,430
1,480
1,480
1,590
1,670
1,620
1,650
1,640
1,650
1,800
1,830
2,000
Mooz et al.
             (1982); 1981-1984, industry sources.

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                                                                   49
   One trend that may reduce future use of CFC-11 in centrifugal chill-
ers is the increasing use of one or more reciprocating chillers,  most of
which use CFC-22,  instead of a single centrifugal unit.  This trend is
expected  to continue  as larger reciprocating units are manufactured.
The use of multiple reciprocating chillers  in place of a single centrifu-
gal unit provides greater system reliability  and allows continued cooling
while one unit is being serviced.  If this trend were to continue, use of
CFC-11 might be reduced by one-third by the year 2000.8
   We  estimate  current reporting  country  use relying  on industry
sources who  suggest  that  the United  States  currently  accounts for
about 45 percent of  CFC-11  and CFC-12 use  in centrifugal  chillers.
Table  6.9 reports projected reporting country  use.  We  assume that
chiller sales for new construction grow at  the rate of GNP both in the
United States and abroad.
   Uncertainty concerning  future  use of  CFCs in  centrifugal chillers
centers on possible substitution to reciprocating chillers.  We suggest
that uncertainty about the total demand for cooling systems is compar-
able to uncertainty  over GNP growth, whereas the quantities of CFC-
11  and CFC-12 used  in centrifugal chillers could decline by one-third
by 2000 if reciprocating chillers take a significant share of the centrifu-
gal market.  These  uncertainties combine  to  a  range of 63 to 125 per-
cent of the base projections.


                              Table 6.9

           ESTIMATED CURRENT AND PROJECTED REPORTING
                  COUNTRY USE OF CFC-11  AND CFC-12
                      IN CENTRIFUGAL CHILLERS
                                (In mt)

                               Other Reporting   Total Reporting

Year
1985
1990
1995
2000
United
CFC-11
4,380
4,840
4,950
5,400
States
CFC-12
1,650
1,800
1,830
2,000
Countries
CFC-11
5,520
6,090
6,510
7,420
CFC-12
2,080
2,270
2,410
2,750
Countries
CFC-11
9,900
10,930
11,460
. 12,820
CFC-12
3,730
4,070
4,240
4,750
   8If reciprocating chillers take half the market we project for centrifugal units, the
 stock of centrifugal chillers would be 20 percent smaller than projected.  Since replace-
 ment of leakage and servicing losses account for 68 percent of CFC-11 use in 2000, use
 would be only about two-thirds the projected level.

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50
Reciprocating Chillers

  Smaller cooling systems, of less than about 150 tons capacity, typi-
cally employ reciprocating chillers.  Although the systems were origin-
ally designed to  use CFC-12, CFC-22 designs have been replacing the
older units since the 1960s; today only about 2 percent of new units use
CFC-12.  The CFC-22 systems have about a 60 percent greater capacity
than CFC-12 systems for the same physical size.
  Table  6.10 presents  estimated historic U.S.  sales of reciprocating
chillers and associated CFC-12 use and the base projection for future
use.  Note that in spite of the growth in the number of chillers, CFC-12
use declined precipitously as an increasing share of chillers used  CFC-
22.  This decline is projected to continue  as older units that use  CFC-
12 are  replaced by  new CFC-22 using units.
  Table 6.11 reports the base projection for reporting country CFC-12
use in  reciprocating chillers.  Estimated current  use is based on indus-
try sources indicating that reporting country use of CFC-12  in recipro-
cating  chillers is currently 3.6 times as large as U.S. use.  We believe
that growth  in new reciprocating chillers outside the United States will
be somewhat more rapid, 5 percent annually, because  most other  coun-
tries have concentrated on reciprocating instead of centrifugal chillers
because of the lower production capital costs.
  Uncertainty over total demand for chillers is comparable to uncer-
tainty  over GNP growth. Moreover, the level of CFC-12 use in chillers

                            Table 6.10

                    ESTIMATED HISTORICAL AND
                   PROJECTED U.S. RECIPROCATING
                    CHILLER INSTALLATIONS AND
                           USE OF CFC-12
Year
1976
1977
1978
1979
1980
1985
1990
1995
2000
Reciprocating
Chillers
5,020
6,970
6,300
6,850
8,020
9,300
10,350
11,100
12,700
CFC-12
(mt)
890
830
750
670
600
280
130
90
90
                      SOURCE:  1976-1980, Mooz et al.
                   (1982).

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                                                                51
                            Table 6.11

               ESTIMATED CURRENT AND PROJECTED
                      WORLD USE OF CFC-12 IN
                     RECIPROCATING CHILLERS
                              (In mt)


Year
1985
1990
1995
2000

United
States
280
130
90
90
Other
Reporting
Countries
1,000
510
400
450
Total
Reporting
Countries
1,280
640
490
540
could vary widely.  If all new chillers used CFC-22, use of CFC-12
could decline to about half the base projection by 2000.  Alternatively,
if centrifugal chillers continue to be replaced by reciprocating units and
significant substitution  of CFC-22 does not  occur, CFC-12 use could
conceivably double. Combining these uncertainties produces a range of
possible use in 2000 of 48 to 207 percent of the base projections.
  Figures. 6.1 and 6.2 summarize the projected baseline use of CFC-11
and  CFC-12 in refrigeration  applications. Almost all of the use we
have  analyzed  is of CFC-12,  and the  United States  accounts for  the
majority of analyzed use because of widespread mobile air conditioning.

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    100
     90
     80
    70
S   60
T3

CO


o   50



0>
(A


|   40
    30
    20 -
    10 -
          J	L
     1976
1980
                                          CFC-11
         J	1	1	I	I	I    I
1984
1988


Year
                                                                        J	I    I
1992
                                                                                   1996
               Fig. 6.1—Estimated historical and projected U.S. use of CFC-11 and CFC-12

                                   in refrigeration and air conditioning
                                                                                                                 Ol
                                                                                                                 10
                                                                              2000

-------
tf>
~a
c
(0
en

o
0)
tfi
"55
c
c
      20 -
       1985
1990
                                                                    1995
                                                              2000
                                                     Year
          Fig. 6.2—Estimated current and projected reporting country use of CFC-11 and CFC-12

                                  in refrigeration and air conditioning
                                                                                                               Ol
                                                                                                               CO

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   VII.  MISCELLANEOUS USES OF CFC-11 AND
                           CFC-12
  There are a variety of other applications that use small amounts of
CFC-11 and CFC-12. Although the amount of CFC used in each speci-
alty application alone is small, taken together such uses represent a
significant  fraction  of CFC use.   In  what follows, we  estimate  the
present and future use of CFC-11 and CFC-12 in miscellaneous appli-
cations.  We do not attempt to construct ranges of  uncertainty for
these minor uses and present only point estimates for future years.
STERILANTS
   CFC-12 is used as a diluent for ethylene oxide in hospital and indus-
trial sterilants.  In earlier work (Palmer et al., 1980; Mooz et al., 1982),
Rand estimated U.S. use of CFC-12 in sterilants at 5,900 mt in  1976
and  6,800 mt in 1980.  During that four  year period the growth aver-
aged 3.6 percent annually.  Assuming the same  rate of growth for the
next five years would place 1985 use at about 8,000 mt.
   Industry sources indicate that  use  of the ethylene oxide/CFC-12
blend will not increase in the future. Indeed, ethylene oxide, an animal
carcinogen, may eventually be banned in sterilant applications.  Accor-
dingly, we assume no future growth. We  arbitrarily assume  that CFC-
12 use in sterilants outside the United States  accounts for an addi-
tional 8,000 mt and that this use will not grow.
LIQUID FOOD FREEZING
   CFC-12  is  used in a  liquid food freezing  process  developed  by
DuPont. 1976 U.S. use was estimated at about 2,720 mt,  with  large
future growth  anticipated (Palmer et al., 1980).  By 1980, the expected
growth had not occurred  and future growth was estimated at much
lower levels (Mooz et al., 1982).
   Using this  information  we estimate an  average annual growth of 1
percent since  1976, placing 1985 use at  2,970  mt.  Use in the other
reporting countries is  also  small: We estimate that it is about equal to
U.S. use.
                             %
   Table 7.1 presents  estimated CFC-12 use  in liquid food freezing for
the United States  and other reporting countries. The  projections were
                                54

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                                                                55
                            Table 7.1

            ESTIMATED CURRENT AND PROJECTED USE OF
                  CFC-12 IN LIQUID FOOD FREEZING
                              (In mt)


Year
1985
1990
1995
2000

United
States
2,970
3,530
4,030
4,600
Other
Reporting
Countries
2,970
3,530
4,190
4,980
Total
Reporting
Countries
5,940
7,060
8,220
9,580
derived assuming future growth at the projected regional GNP growth
rates. Industry sources indicate that new LFF users are few and that
CFC-12 use for this purpose may actually decline in the future.
OTHER MISCELLANEOUS APPLICATIONS

  A variety of other applications use very small amounts of CFC-11
and  CFC-12.  They  include CFC-12  use  in  fire and  other  warning
devices,  boat  horns,  dehumidifiers,  pressurized blowers and drain
cleaners, and trucking refrigeration, and CFC-11 use in coal cleaning.
Total U.S. use in these applications was estimated at 450 mt  of CFC-
11 and 1,430 mt of CFC-12 in 1976 (Palmer et al., 1980).  In Table 7.2
we provide estimates of current and future  U.S. use based on growth at
the GNP rate  for all  applications except coal cleaning.  Industry
sources indicate that this use has not grown and is unlikely to do so in
the future.  The table also presents estimated current and projected use
of CFC-12 in the other  reporting countries assuming that 1985 levels
mirror those in  the United States and that growth will occur at the
same  rate as the GNP.  We do not include CFC-11 since we are not
aware of its use for coal cleaning outside the United States.

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56
                            Table 7.2


       ESTIMATED CURRENT AND PROJECTED USE OF CFC-11 AND
           CFC-12 IN OTHER MISCELLANEOUS APPLICATIONS
                              (In mt)

                             Other Reporting    Total Reporting

Year
1985
1990
1995
2000
United
CFC-11
450
450
450
450
States
CFC-12
1,700
2,020
2,301
2,640
Countries
CFC-11 CFC-12
— 1,700
— 2,020
- 2,400
— 2,850
Countries
CFC-11
450
450
450
450
CFC-12
3,400
4,040
4,710
5,490

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                      VIII. SOLVENTS
   CFC-113  and  methyl chloroform  are  used primarily as solvents.
Carbon tetrachloride was formerly used as a solvent but,  at least in the
industrialized countries, this use has been curtailed. It is also used as a
grain fumigant, but that use  has been  discontinued  in  the  United
States.  The chemical's major use is as an  intermediate in  the produc-
tion of CFC-11 and CFC-12.
   The use of solvents  as "degreasers"  is an important cleaning step in
many manufacturing processes.  Projections of future solvent use are
especially uncertain because of the number of competing solvents and
the possibilities for substitution among them as one  or  more are sub-
jected to increasing regulation.  Neither CFC-113 nor methyl  chloro-
form has a dominant share of the overall solvent market, although each
has a strong position in certain submarkets. CFC-113 is used primarily
in the electronics industry, and methyl chloroform is  used  in a variety
of applications  from electronics to shipbuilding.
   Most solvent uses can be described as either "cold cleaning," where
the  part to be cleaned is dipped into a  tank  of solvent, or "vapor
degreasing," where  the solvent  is heated and the item to be cleaned is
suspended in the vapor above the tank.  In both types of cleaning the
solvent  displaces contaminants  and then evaporates. Another use  is
drying, where the solvent  is used to displace water. Solvent emissions
are prompt, although equipment to recover and recycle the solvent can
be used.
   Use of methyl chloroform and CFC-113  may be strongly affected by
government regulations.  One factor  that  may  discourage  the use of
these and  other solvents  is  the U.S. ban  on land disposal of waste
chlorinated solvent, which becomes effective in November  1986. Some
users may adopt more conservative practices or alternative cleaning
processes, or substitute other solvents  that have not been banned from
land disposal to avoid  much higher disposal costs. Alternatively, some
of the competing solvents, such as trichloroethylene, perchloroethylene
and methylene chloride, may be regulated  more stringently because of
concern  over  health   risks  to  workers  and  the general  population.
(These  solvents have  been  shown to cause chronic adverse  health
effects  in  animal  studies.)   Such  restrictions  could substantially
increase demand for CFC-113 and methyl chloroform.
                                57

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58
CFC-113

   CFC-113 is used largely in the electronics industry, to deflux printed
circuit boards and  other metal components and for  "critical cleaning"
of plastic or specialty components, such as semiconductors,  that are
produced in a contamination-controlled environment. CFC-113 is more
compatible with certain plastics than are  other solvents:  Without  it
many components could not be made of plastic.  Small quantities are
also used in  chemical processing, as a blowing agent for foam produc-
tion, as a specialty refrigerant, and  for dry cleaning.
   CFC-113 has several advantages  over potential alternatives. First, it
is a mild solvent, compatible with  virtually all materials.  Indeed, it  is
gentle enough to  dry clean  delicate suede  and  leather garments.
Second, its TLV1  in  the workplace  is  1,000  parts per million, the
highest value assigned.  This implies that costly methods of air circula-
tion and dilution can be avoided. Third, CFC-113 is  very stable,  one  of
the characteristics  that makes it a potential ozone  depleter.  Thus  it
can be used without stabilizing additives.
   In Table 8.1 we present estimates of  historical U.S. CFC-113 pro-
duction and projected baseline future use. Because the chemical  is pro-
duced by only two  domestic producers, annual production data are not
reported by the International Trade Commission.  We estimated his-
torical use  as follows:  The 1976 and 1977 values are  from Palmer et al.
(1980).  The  1978  estimate  was derived from a  Chemical Marketing
Reporter Chemical  Profile on fluorocarbons indicating that solvent use
amounted to 11 percent of total CFC use (CMR, 1978).  Since virtually
all solvent  use is CFC-113, we estimate 1978 use as 11  percent of 1978
CFC  production.  Total  CFC  production is estimated  from  the ITC
reports for CFC-11, CFC-12, and  CFC-22, and a Rand estimate for
CFC-114.2
   For 1979, we based our estimate on a Chemical Marketing Reporter
Chemical Profile on perchloroethylene, the precursor chemical used  to
produce CFC-113  and  CFC-114 (CMR,  1979).  The profile indicated
that 13 percent of the chemical was used in CFC  production.   After
subtracting  the  estimated amount used  to  produce  CFC-114 the
amount of CFC-113 produced  can  be estimated using  the appropriate
stochiometric equations (see Wolf,  1980).
   lrThe Threshold Limit Value is the maximum allowable time-weighted average con-
centration to which a worker may be exposed over an eight-hour working day, 40-hour
work week, as determined by the U.S. Occupational Safety and Health Administration
(OSHA). Generally, the more toxic the chemical, the lower the TLV.
    Total  CFC-113 use exceeds solvent use by the small amounts used as refrigerants
and in plastic foams.

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                                                                59
                            Table 8.1

                      ESTIMATED HISTORICAL
                       AND PROJECTED U.S.
                          USE OF CFC-113
                              (In mt)
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1990
1995
2000
CFC-113
31,300
36,740
39,010
49,900
57,150
57,150
57,150
57,150
68,040
73,200
105,600
134,800
172,000
  The 1984 production estimate is from industry sources.  The values
for 1980 through 1983 are more uncertain.  CFC-113 production during
that time may have been as high as 59,870 mt (EPA, 1981) or as low as
57,150 mt (industry sources).  We adopt the latter estimate and assume
that the market was flat for the period because of the recession.
  The estimates in Table 8.1 suggest that CFC-113 use more than
doubled between 1976  and 1984.  We expect future growth to  be high
as well.  In the absence of the ban on land disposal  of waste chlori-
nated solvents, CFC-113 use in defluxing and  critical cleaning (about
50 percent of current  use) would be expected to  grow at the rate of
other chemicals used in the  electronics industry,  13 percent over  the
next several years.3 As a base projection, we assume that defluxing and
critical cleaning use grow at only 10 percent between 1984 and 1990 to
account for the land disposal ban. We assume  that the other CFC-113
applications grow at a lower  rate, 5 percent through 1990. Combining
these markets  implies overall growth averaging 7.6 percent annually.
Because industry sources expect the electronics industry to continue to
grow more rapidly than GNP for an extended period,  we project base-
line CFC-113 use in all applications to grow at an average of 5 percent
annually between 1990 and 2000.
   3See Stinson (1983), CMR (1984), Mining Journal (1985), and Manufacturing Chemist
and Aerosol News (1985).

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60
   Industry sources suggest that 1984 CFC-113 use in the EEC was less
than  45,000  mt; we  assume 40,000 mt.  Japanese  production of all
CFCs is about 150,000 mt4 of which CFC-11 and CFC-12  account for
110,000 mt.5 Almost all of the remaining 40,000 mt should be CFC-113
and CFC-114; we  assume that  CFC-113  production  is  35,000  mt.
Finally,  we  assume  that production in the other reporting  countries
outside  the EEC and Japan is nominal, about 10,000  mt.  This leads to
an  estimated  85,000 mt  in the CMA  reporting countries  outside the
United States.
   Our base projections for reporting country CFC-113 production are
reported in Table  8.2. Outside the United States, we project baseline
growth  of 9.3  percent for the period 1984 through 1990.  This rate is
based on one-half the market (defluxing and critical  cleaning) growing
at 13 percent, as U.S. use would in the absence of the  land disposal
ban, and the other half at 5 percent.  After 1990, we assume an average
annual  rate of  6  percent  growth in the baseline,  about  70 percent
higher than the expected  GNP growth rate, to  account for  the  fast
growing electronics industry.
   United States CFC-113  use may be lower than our projected base
use if the impending ban on land disposal  affects CFC-113 use more
than we have estimated.   Two of the most  likely alternatives to land
disposal  are  reclamation and incineration.  Once the ban goes into
effect there may be  insufficient  reclamation  capacity to  handle  the
greatly increased demand.  Indeed, today only a handful of reclaimers
in the country can properly reclaim CFC-113. The fluorine in CFC-113

                            Table 8.2

                ESTIMATED CURRENT AND PROJECTED
                REPORTING COUNTRY USE OF CFC-113
                              (In mt)

Year
1985
1990
1995
2000

United
States
73,200
105,600
134,800
172,000
Other
Reporting
Countries
85,000
132,600
177,400
237,500
Total
Reporting
Countries
158,200
238,200
312,200
409,500
  4Ministry of International Trade and Industry data as supplied by Japan Flon Gas
Association (private communication, 1985).
  5Taya (1985).

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                                                                 61
apparently corrodes  the refractory  material lining incinerators,  and
industry sources report that incinerator owners charge dearly for fluori-
nated chemicals or refuse to  accept them altogether.  Consequently, it
is possible that substitution  and increased reclamation might  reduce
U.S. CFC-113 production by a third.  Alternatively, regulation of tri-
chloroethylene, perchloroethylene. and methylene  chloride use could
increase demand for  CFC-113 by half.  We believe  that  outside the
United States any regulations are likely to have a smaller effect, since
the existence  and stringency of regulations will  differ  across nations.
However,  future growth in solvent use is more  uncertain so  we  also
assume a range of plus one-half or minus one-third.
METHYL CHLOROFORM
   Although it  is not  a particularly  strong  potential ozone depleter,
methyl  chloroform  is  produced  in  large  quantities.  In  the  United
States, it is used primarily for vapor degreasing and cold cleaning of
electronic  and  other  parts,  although  small  amounts are  used  in
adhesives, aerosols,  and coatings.  Methyl chloroform is a general pur-
pose  solvent that has certain advantages over its  competitors.  Its
TLV, although  lower  than that  of  CFC-113,  is higher than  that of
other chlorinated solvents.  It is a stronger solvent than CFC-113 and
is consequently not compatible with all  materials.  However, because it
is stronger it can clean contaminants that  CFC-113 cannot remove. A
recently  marketed blend of methyl chloroform and alcohol has  made
some inroads into the electronics market.
   Table 8.3 reports U.S. methyl chloroform production between  1976
and 1984 and projected use. Note that production increased 16 percent
over the  period,  an average of about 1.9  percent annually.
   We estimate  1985  U.S.  use of methyl chloroform as  270,000  mt.
This estimate is based on the trend in  reported production since  1979
and is derived in Appendix A. Since  methyl chloroform is a widely
used general purpose solvent we would  expect use to grow  at the same
rate as the GNP in the absence of the land disposal ban. Because of
the ban we assume a slightly lower growth, 3  percent between 1986 and
1990 and  2 percent  through 2000  (compared with expected  GNP
growth of 3.5 and 2.7 percent, respectively).  Before the ban's imple-
mentation in 1986 we assume growth at the GNP rate.
   Industry sources indicate that 1980  U.S. production represented 59
percent of total world production  outside the communist countries. If
we assume this same relationship for  1985, we obtain the values shown
in Table 8.4.  We project baseline growth outside the United States at
the same rate as GNP, 3.5 percent annually.

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62
                           Table 8.3

                      ESTIMATED HISTORICAL
                       AND PROJECTED U.S.
                         USE OF METHYL
                          CHLOROFORM
                              (In mt)

Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1990
1995
2000
SOURCE:
(1976-1984).
Methyl
Chloroform
266,000
288,000
292,000
325,000
314,000
279,000
270,000
266,000
303,000
270,000
314,500
347,300
383,400
U.S. ITC

   Projected methyl chloroform use  is subject  to the same types  of
uncertainty as CFC-113 use. The land disposal ban may cause users to
reduce their use  of  methyl  chloroform (through  reclamation,  for

                            Table 8.4

          ESTIMATED CURRENT AND PROJECTED REPORTING
              COUNTRY USE OF METHYL CHLOROFORM
                             (In mt)


Year
1985
1990
1995
2000

United
States
270,000
314,500
347,300
383,400
Other
Reporting
Countries
187,600
222,800
264,600
314,300
Total
Reporting
Countries
457,600
537,300
611,900
697,700

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                                                                 63
example)  or  to  switch to other solvents or processes.  Alternatively,
regulation  of alternative chlorinated solvents,  including  methylene
chloride, trichloroethylene, and perchloroethylene,  could substantially
increase domestic use of methyl chloroform. Since methyl chloroform
is used in a wider range of applications than CFC-113, its use is less
sensitive to trends in particular industries and the range of uncertainty
should be smaller. We suggest a range of uncertainty of 80 to 125 per-
cent of the base projection, conditional on  GNP. Combined with the
uncertainty about GNP growth, the overall range of uncertainty is 0.73
to 1.37 times the base projection for the United  States and for the
other reporting countries.
CARBON TETRACHLORIDE
   Carbon tetrachloride is  an excellent solvent in  many applications.
At  one time,  it was  widely  used as a solvent in  the  United States.
Because of its acute and chronic toxicity, however, it is used only  in
small amounts for such purposes today.  Although  our information on
carbon tetrachloride use in the rest of the world is  limited, we suspect
that carbon tetrachloride is commonly employed as a general purpose
solvent in many developing nations.
   Carbon tetrachloride's major use in the United  States and most  of
the rest of the world is as an intermediate in the production of CFC-11
and CFC-12.  A second large use in this  country  has  been for  grain
fumigation.  Domestic producers  have voluntarily agreed to halt pro-
duction for this application  beginning in 1986, however.  Additional
small amounts are used in the pharmaceutical industry.
   Table  8.5 shows historical U.S. production  of carbon tetrachloride
and the fraction used to produce CFCs.  Note the sharp decline in 1982
and 1983  because  of the recession.  Demand for CFC-11 and CFC-12
was off strongly for that period, and because a high percentage of car-
bon tetrachloride  is devoted  to CFC manufacture, its total production
declined as well (CMR, 1983).
   Table 8.6 presents  estimated future carbon tetrachloride production
using the  base projections for United States and other reporting  coun-
try CFC-11  and CFC-12 production.  The estimates are based on the
stochiometric equations for CFC production. These imply that produc-
tion of one kilogram of CFC-11 requires 1.12 kilograms of carbon  tetra-
chloride and that  one kilogram of CFC-12  requires  1.27 kilograms (see
Wolf, 1980). We estimate that additional losses in the production pro-
cess amount to 2.7 percent  of total use in CFC production, whereas
other uses, not including grain fumigation, account for an estimated

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64
                             Table 8.5

                   ESTIMATED HISTORICAL U.S. USE
                     OF CARBON TETRACHLORIDE
                               (In mt)
Year
1976
1977
1978
1979
1980
1981
1982
1983
1984
Carbon
Tetrachloride
389,000
366,000
334,000
324,000
322,000
329,000
266,000
260,000
323,000
% Used To
Produce CFCs
—
—
95
—
—
95
—
83.6a
—
                     SOURCES: U.S. ITC  (1976-1984);
                   CMR (1978, 1981, 1983).
                     "The share allocated to CFC produc-
                   tion  decreased in 1983 because  a large
                   fraction of carbon tetrachloride  was
                   exported.
                             Table 8.6

           ESTIMATED CURRENT AND PROJECTED REPORTING
              COUNTRY USE OF CARBON TETRACHLORIDE
                               (In mt)


Year
1985
1990
1995
2000

United
States
280,000
323,200
373,100
430,700
Other
Reporting
Countries
590,000
668,500
757,300
857,700
Total
Reporting
Countries
870,000
991,700
1,130,400
1,288,400
additional 5.4 percent of total use. The resulting U.S. estimate, 277,000
mt,  almost exactly matches the 280,000  mt  estimate  derived from
reported production in recent years (see Appendix A). Since almost all
carbon tetrachloride is used for CFC production the uncertainty about
future production is  based on uncertainty  about future  production  of
CFC-11 and CFC-12. Specifically, the range is based on the average of

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                                                                 65
the ranges of total CFC-11 and CFC-12 production  and spans  the
interval from 0.76 to  1.32 times the projected base level in the United
States and from  0.73 to 1.37 times the base projection for  the  other
reporting countries.
   Historical  and projected consumption of CFC-113,  methyl chloro-
form, and  carbon  tetrachloride  are  summarized in Fig.  8.1  for  the
United States and in Fig.  8.2 for the CMA reporting countries.  Note
that U.S. use of methyl chloroform about equals that of carbon  tetra-
chloride, but carbon  tetrachloride use far exceeds estimated methyl
chloroform use in the reporting countries. This difference  is due in
part to the relatively  low U.S. use of CFC-11, compared with the other
reporting countries, and consequently lower carbon tetrachloride use.

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700
 0 I	i	i	i	I
 1976
                                                                                                         05
2000
            Fig.  8.1—Estimated  historical  and  projected  U.S. use  of  CFC-113,
                         methyl chloroform, and carbon tetrachloride

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CO
CO


O
0)
W
      1985
1990
1995
2000
                                                   Year
              Fig. 8.2—Estimated current and projected reporting country use of CFC-113,

                             methyl chloroform, and carbon tetrachloride

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              IX.  FIRE EXTINGUISHANTS
   Halons 1211 and 1301 were introduced for use as fire extinguishants
in the United States in the early 1970s. Although total  production is
presently  small relative to the other chemicals we consider, use is
expected to grow rapidly.  Moreover, since the Halons contain bromine
they may present a much greater threat to the  stratospheric ozone than
do similar chlorinated chemicals.
   Halon 1301 is used primarily in  total flooding systems that protect
valuable  equipment and materials in enclosed spaces. These  systems
release a preset quantity of the gas from a pressurized cylinder in the
event of a fire.  Although Halon 1301 is relatively expensive it leaves
no residue and does not damage valuable equipment.  Moreover, unlike
other extinguishants,  it can be released before workers are evacuated
from  the room,  thereby reducing fire damage.  It  is used primarily in
'computer rooms, telephone exchanges, pipeline compressor and pump-
ing stations,  airliners,  some libraries and museums, battle tanks, and
ship engine and boiler rooms. In the late 1970s more than 80 percent
was  used in  computer  rooms, telephone exchanges,  and other rooms
containing electronic  equipment (DuPont, 1978).  Halon 1301 is also
being introduced into the hand-held extinguisher market  for home and
commercial use, and small quantities are  used as a specialty refriger-
ant.
   Halon 1211 is used primarily in hand-held fire extinguishers.  It is
also used in U.S. Air Force rapid intervention crash trucks.
   Nearly the entire quantity of Halons produced in a year is banked in
total  flooding systems  or other  fire extinguishers.  Emissions  occur
when the system is activated during a fire  and from system testing, fill-
ing and servicing,  leakage, and accidental discharges. Losses through
accidental discharge are  likely to  be more significant for hand-held
extinguishers than for the total flooding systems.  Since the Halons are
so expensive  it is likely that the amounts stored in total flooding sys-
tems  will often  be recovered and re-used  when the  system is disman-
tled, so much of the bank may never be released to the atmosphere.
                                68

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                                                                69
HISTORICAL U.S. USE
  Table 9.1 presents estimated historical U.S. use of Halon 1301.  We
have little  information  on past use of Halon 1211, but suspect it is
similar. Approximately 95 percent of annual Halon 1301 use is attri-
buted to total flooding systems with the remaining 5  percent going to
hand-held extinguishers, specialty refrigeration, and other uses.
  The historical use estimates assume the  introduction of 2,600 new
systems each year beginning in 1972 and reaching a total of 13,000 sys-
tems in 1978. Subsequent growth was rapid: an estimated 30 percent
annually during 1978 and 1979, falling to 25 percent in 1980 and 1981,
to 15 percent in 1982 and 1983, and recovering  to 20 percent in 1984
with the end of the recession.  The estimates are consistent with esti-
mates by industry sources that U.S. use in 1977 was between  1,100 and
1,400 mt and that use in recent years was 3,400 to 4,500 mt.
  Although there is considerable uncertainty about the average system
charge, industry sources indicate  that it was quite high  in  the early
years and has since fallen.  Accordingly, we adopt an average system
charge of 340 kilograms (750 pounds) for all  new  systems through 1983,
falling to 318 kilograms in 1984.

                             Table 9.1

                       ESTIMATED HISTORICAL
                             U.S. USE OF
                             HALON 1301
                               (In mt)
Year
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Use
1,200
1,200
1,200
1,200
1,200
1,600
2,100
2,600
3,200
3,700
4,300
4,800

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70
   The estimated use figures in Table 9.1 include: the Halon 1301 used
to charge new units; use for testing, estimated at 19 percent of the ini-
tial charge; replacement of filling and servicing losses, estimated at 1
percent of the  initial charge; replacement of leakage, estimated at  0.1
percent of the bank;  replacement of Halon 1301 at  system failure,
estimated at 1 percent of the bank; and discharge during fire, estimated
at 1 percent of the bank.
   Halon  1301  use for system testing may increase substantially from
its current estimated  use  of 19  percent of initial  charge.  Currently,
three-quarters of new  systems are tested, three-quarters of these using
CFC-12, but installers are beginning to test with the Halon more fre-
quently for two reasons.  First, although it had been believed that an
82 percent charge of  CFC-12 mimics a 100 percent charge of Halon
1301, recently  it  has become apparent that the hydraulics  of the two
chemicals differ as they move through the pipes of the flooding system.
Second, and more important,  CFC-12 at high  concentrations has an
anesthetic effect. To properly  test a flooding system a gas concentra-
tion of 5  percent must be held in the room for 10 minutes.  Because
service  workers  have complained of headaches  from CFC-12-filled
rooms, some are moving toward Halon 1301 in spite of its much higher
price.
CURRENT AND FUTURE REPORTING COUNTRY USE

   In the United States, growth in new systems has remained high, an
estimated 20 percent between 1984 and 1985.  For the base projection
we assume that rapid growth will continue at rates averaging 15 per-
cent through 1988. By then, many existing computers will be protected
by total flooding systems and growth is projected to decline to an aver-
age of 7 percent annually until 2000.   In the base projection, the aver-
age system charge is also projected to decrease, from 320 kilograms in
1984 to 180  kilograms by 2000, as the systems are placed in progres-
sively smaller installations (partly as a result of increasing miniaturiza-
tion of computers and other electronic equipment).  Combining these
effects and the  implied testing, servicing, and loss projections implies
annual U.S. production of 10,200 mt by 2000.
   Table 9.2  shows the U.S. baseline projections together with our esti-
mates of reporting  country Halon  1301  use.  Relying on  industry
sources, we  use  a  base projection for  total  reporting country use twice
that in the United States.
   These estimates and projections are subject to  considerable uncer-
tainty.  Halon total  flooding systems are  a substantial improvement

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                                                                71
                            Table 9.2

                ESTIMATED CURRENT AND PROJECTED
               REPORTING COUNTRY USE OF HALON 1301
                               (In mt)


Year
1985
1990
1995
2000

United
States
5,400
6,700
8,300
10,200
Other
Reporting
Countries
5,400
6,700
8,300
10,200
Total
Reporting
Countries
10,800
13,300
16,500
20,400
over earlier fire-protection systems and it is difficult to estimate how
widely they will be used.  The average charge is subject to significant
uncertainty depending on the types of future installations.  Increased
use of the Halon for testing could lead to substantially greater chemical
use. To account for  these factors we suggest a range of uncertainty
between 0.6 and 1.67  times the base levels, for both the United States
and abroad.
   Estimated current  use  of  Halon 1211, and its  base projection, are
shown in  Table 9.3. Halon 1211 is used primarily in hand-held extin-
guishers.  According to industry sources worldwide use is about equal
to that of Halon 1301, but the  United States accounts for only one-
quarter of the total.  For our  base projection we assume that future use

                             Table 9.3

                ESTIMATED CURRENT AND PROJECTED
               REPORTING COUNTRY USE OF HALON 1211
                               (In mt)


Year
1985
1990
1995
2000

United
States
2,700
3,300
4,100
5,100
Other
Reporting
Countries
8,100
10,000
12,400
15,300
Total
Reporting
Countries
10,800
13,300
16,500
20,400

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72
will grow at the same rate as Halon 1301 and suggest a range of uncer-
tainty between 0.6 and 1.67 times the base projected use.
   United States  use and reporting country use of Halons  1211 and
1301  are summarized in  Fig. 9.1.  The projected  baseline growth  is
strong but the range of uncertainty includes the possibility  of almost
no growth.

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CO
"O
c
CO
co
13
o
CD
CO
13

"ro
3
c:
c
          NOTE  Historical reporting country Halon 1301 and 1211 and U S Halon 1211 use not available
Reporting Country

Halon 1301,
Halon 1211
                                     U.S. Halon 1301
                                              U.S. Halon 1211
      1976
                                                                         2000
                  Fig. 9.1—Estimated historical and projected U.S. and reporting country use

                                          of Halon 1301 and  Halon 1211
                                                                                        CO

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 X. USE OF POTENTIAL OZONE DEPLETERS IN
            THE  COMMUNIST COUNTRIES
  Available data on use of potential ozone-depleting substances in the
communist countries are extremely limited.  The only published esti-
mates  are  for Soviet Union  use  of  CFC-11  and CFC-12 from  1968
through 1975.  However, we believe that the Soviet Union accounts for
the majority of use  in these countries.  Our approach  to estimating
base projections  for  CFC-11  and  CFC-12 is to estimate total use  by
extrapolating from these historical data.  Since we have little informa-
tion on the pattern of CFC uses, we do  not  explicitly estimate  com-
munist country use by application.
  The estimates of current solvent use are similarly uncertain.  Car-
bon tetrachloride use is based on estimated CFC-11 and CFC-12 use.
The methyl chloroform estimate assumes that communist country use
relative to GNP is the same as the corresponding ratio in the reporting
countries, whereas the CFC-113 estimate is based on industry sources
who suggest that communist  use  of this  solvent is quite small.  Since
we  have no information that Halon 1301 and 1211 are even used in the
communist countries, and because their use in the reporting countries
is so small, we assume that use in the communist countries is negligi-
ble.
  Our lack of information on potential ozone-depleter use in the com-
munist countries is too  great to treat the structure of uncertainty in
detail.  Our uncertainty ranges are based  on our ranges for use of each
chemical in the CMA reporting countries excluding the United States.
To  reflect our greater uncertainty about  use  in  the communist coun-
tries, the  uncertainty ranges are  constructed so that  the variance of
use, conditional on the level of the GNP,  is 1.25 times greater  than the
corresponding variance  for  the  non-U.S.  reporting  countries.  As
described in Sec. II, our uncertainty range for communist country GNP
is also  wider than for the reporting countries.
CFC-11 AND CFC-12 USE

   Table 10.1 presents estimated CFC-11 and CFC-12 production in the
Soviet Union from 1968  through 1975 and  base  projections  for the
communist countries  from 1985  to  2000.  The production  estimates
were originally published in a Soviet journal (Borisenkov and Kazakov,
                                74

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                                                                75
1980) and are reprinted in  the  CMA  reports.  Reported  growth was
very strong:  27 and 18  percent average annual growth rates for CFC-
11 and CFC-12, respectively. Such high rates are unlikely to have been
sustained in later years.  For the period 1975 to 1985 we assume that
use grew at rates 10 percent less than the historical rates, 17 and 8 per-
cent per year, respectively.  In addition, we assume that total commun-
ist country use is 15 percent greater than use in the Soviet Union (the
same assumption as CMA used in their 1983 report).  These assump-
tions lead to estimated 1985  communist  country use of 41,500 and
78,700 mt of CFC-11 and CFC-12. These estimates are  roughly con-
sistent with estimates by other sources but are clearly more uncertain
than our estimates for other regions.
   Beyond 1985 we project CFC-11 to grow at an average rate of 6 per-
cent through the end of the century and CFC-12 at an average rate of 5
percent. These rates are 2.0 and 1.67 times the base projected GNP
growth  rate  (3.0 percent). Such high rates are justified by the level of
development of  the communist economies,  a level  at which uses of
CFC-containing products are likely to grow rapidly, and by the histori-
cally strong growth. We suspect that  CFC-11  will grow  more  rapidly

                            Table 10.1

                ESTIMATED HISTORICAL SOVIET UNION
                AND PROJECTED COMMUNIST COUNTRY
                      USE OF CFC-11 AND CFC-12
                               (In mt)
Year
CFC-11
CFC-12
Soviet Union
1968
1969
1970
1971
1972
1973
1974
1975
1,400
2,200
2,500
2,900
3,700
4,100
6,200
7,500
9,800
12,200
13,500
16,200
18,500
20,100
25,900
31,700
Communist Countries
1985
1990
1995
2000
41,500
55,500
74,200
99,400
78,700
100,400
128,200
163,600

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76
than  CFC-12 because the estimated 1985 use  of CFC-12 is so much
higher than  that  of CFC-11 (compared with  the  pattern in other
regions) and because our analysis of specific applications suggests that
CFC-11 use will grow more  rapidly than CFC-12 use in other world
regions. Estimated historical and projected use is depicted in Fig. 10.1.
SOLVENT USE

   Table 10.2 reports our estimates of current and projected solvent use
in the communist countries.  Because  we have no information to the
contrary, and because CMA reporting  country use of Halon  1301  and
Halon 1211 is small, we assume that communist country use of these
chemicals is negligible.
   Current use of CFC-113 in the communist countries is believed to be
modest at  best,  although some is  likely to be used  in manufacturing
military and scientific electronic equipment.  We estimate a nominal
5,000 mt.  The baseline projection  is based on projected growth in the
non-U.S reporting countries: The  difference  between  the  baseline
CFC-113 and GNP growth  rates is the same as for these countries.
Thus the baseline projection for the communist countries  is 6.6 percent
for the next 15  years, 3.6  percent higher than the projected GNP
growth rate.  The range of uncertainty is similarly based on the range
for the non-U.S. reporting countries. Combined with uncertainty about
the level of the GNP, the range is from 0.62 to 1.62 times the  base pro-
jection.
   Since methyl chloroform is a popular general purpose solvent in the
reporting countries, we suspect it is also widely used  in the communist
countries.  We  estimate current  use by assuming  that  the  ratio of
methyl chloroform use to GNP is the same as for the reporting coun-
tries.  Thus communist use is estimated as 16 percent of world use, or
87,000 mt.  In the  reporting countries other than the United States,
methyl chloroform is projected  to grow at the same  rate as the  GNP.
We adopt the same assumption for the communist countries, implying
a baseline projected rate of 3  percent annually.  The  corresponding
range  of uncertainty is from  0.68 to 1.47 times the base projection in
2000.
   The estimated current and projected use of carbon tetrachloride is
based  on the CFC-11 and CFC-12 estimates, using the same assump-
tions  about  other  uses  as   for the  reporting  countries. Estimated
current use is 162,700 mt, with a projected baseline growth rate  of 5.2
percent.  The range of uncertainty is between 0.68 and 1.47 times the
projected base level.

-------
»*—
o
V)

O

*^




§
c
                                                                                    1996
2000
   Fig. 10.1—Estimated historical and projected use of CFC-11 and CFC-12 in the communist countries

-------
78
                          Table 10.2

         ESTIMATED CURRENT AND PROJECTED COMMUNIST
          COUNTRY USE OF CFC-113, METHYL CHLOROFORM,
                  AND CARBON TETRACHLORIDE
                            (In mt)

Year
1985
1990
1995
2000

CFC-113
5,000
6,900
9,500
13,000
Methyl
Chloroform
87,000
100,900
116,900
135,500
Carbon
Tetrachloride
159,000
205,900
267,000
346,400

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                    XI.  CONCLUSIONS
  We  are  now in  a  position to aggregate all of the details  of the
preceding sections into  global projections.  This report examines the
current and likely future  global production levels of the seven most
important potential ozone depleters—CFC-11, CFC-12, CFC-113, car-
bon tetrachloride, methyl chloroform, Halon 1211, and Halon 1301.  It
starts by looking at the products in which these chemicals are used in
the United States and the other CMA reporting countries. It asks how
demand for these products and hence derived demand for the chemicals
themselves is likely to change over the next 15 years. It then posits
similar, but much less detailed and confident, demand trends for the
communist countries.  This  product-based or  "bottom-up" approach
cannot capture the full demand for CFC-11 and  CFC-12; hence the
report  examines the magnitude of the uses not accounted for  by the
method and develops  a  way to project  these unallocated  uses into the
future.  By aggregating projections  of demand for each chemical in the
United States, other reporting countries, and communist countries,  as
well as projections of the  likely shortfalls for CFC-11 and CFC-12, we
can develop global projections for each chemical.  This section reports
those global projections and suggests some directions for future work.
UNITED STATES AND GLOBAL PROJECTIONS
   Tables 11.1  and 11.2 summarize estimated current and projected
U.S. and total world use of the seven potential ozone depleters we have
analyzed. The tables present the range of projected use  in 2000 and
the average annual growth rates from 1985 to 2000 implied by these
limits. In addition, Fig. 11.1  and Fig. 11.2 illustrate the estimated his-
torical and projected use of CFC-11 and CFC-12 in the United States
and CMA  reporting countries.  (Figures illustrating use of the other
chemicals are in preceding sections.)  Much of the evident decline in
CFC-11 and CFC-12 use in the late 1970s was due to the  discontinua-
tion of CFC use in many aerosol products in the  United States and
elsewhere.  As discussed in Sec.  II, the bounds of the ranges of uncer-
tainty reported in the  tables  and figures are meant to capture a  "rea-
sonable range" of outcomes for each chemical.  The reader should keep
in mind that this is not an exact concept.
   The projections  for total  CFC-11  and CFC-12 use are aggregated
from the projections  for  the specific  applications  we  analyze.  In
                                79

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80
                         Table 11.1

          ESTIMATED CURRENT AND PROJECTED U.S. USE OF
            POTENTIAL OZONE-DEPLETING SUBSTANCES
Use (thousands of mt)


Chemical
CFC-11
CFC-12
CFC-113
Methyl chloroform
Carbon tetrachloride
Halon 1301
Halon 1211


1985
75.0
135.0
73.2
270.0
280.0
5.4
2.7

Projected in 2000
Lower Upper
110 190
140 240
120 270
300 560
350 600
7 18
3 9
Average Annual
Growth
Lower
2.6
0.4
3.6
0.7
1.5
1.4
1.4
Rate (%)
Upper
6.3
4.0
9.1
5.0
5.2
8.3
8.3
                         Table 11.2

         ESTIMATED CURRENT AND PROJECTED WORLD USE OF
             POTENTIAL OZONE-DEPLETING SUBSTANCES



Chemical
CFC-11
CFC-12
CFC-113
Methyl chloroform
Carbon tetrachloride
Halon 1301
Halon 1211
Use


1985
341.5
443.7
163.2
544.6
1029.0
10.8
10.8
(thousands of mt)

Projected
Lower
420
460
290
630
1200
13
12

in 2000
Upper
730
830
610
1100
2100
33
32

Average

Annual
Growth Rate (%)
Lower
1.4
0.3
3.9
0.9
0.8
1.1
0.9
Upper
5.2
4.3
9.2
5.0
4.8
7.6
7.6

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T3

(0
W

O
0)
CO
15
C
      1972
1976
1980
1984          1988

       Year
1992
1996
2000
                                                                                                              00
       Fig. 11.1—Estimated historical and projected use of CFC-11 and CFC-12 in the United States

-------
    800
    700
    600
•R   500
TJ

co
in


1
400
§

75
§   300
    200
    100
      1972
                     I	,
                                      CFC-11
                                           I
                                                    _L
                            I
                                               J	I
               1976
1980
1984         1988


       Year
1992
1996
                                                                                                               00
                                                                                                               to
                                                                                                   2000
    Fig. 11.2—Estimated historical and projected use of CFC-11 and CFC-12 in the reporting countries

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                                                                83
addition, we project the unallocated uses to also grow at a rate equal to
the average of the analyzed applications. As discussed in Appendix B,
the unallocated uses are likely to include substantial amounts of CFC-
12  used in refrigeration  applications,  and for  CFC-11,  unspecified
refrigeration and  miscellaneous uses.  In addition, the unallocated uses
include any new  products that may be introduced over  the next 15
years.
   The U.S. and  global projections are quite  similar.  In part this  is
because the United States accounts  for such a large  share of global
demand and in part because our approach often infers  demand outside
the United States using information about U.S. demand.  As is often
true with chemicals,  demand for those  that  are  used in the largest
quantities tends to grow more slowly than demand for smaller "speci-
alty" chemicals.  Of the seven chemicals, CFC-12 and methyl chloro-
form are projected to grow at the lowest rates,  averaging between about
0  and  4 or 5  percent annually over the  next 15 years.   CFC-11  is
expected to grow slightly more rapidly, but with a comparably wide
range  of uncertainty.  The projected growth rates for carbon tetra-
chloride are similar to those of CFC-11 and CFC-12 because the major
use of this chemical is in producing the two CFCs.  The other chemi-
cals are produced in smaller quantities and are expected to grow more
rapidly, at rates of about 4 to 9 percent for CFC-113 and 1 to 8 percent
for the Halons. Nonetheless, these  growth rates are not large enough
relative to those for the chemicals used in  greater quantities to change
the relative importance to  potential ozone depletion of these seven
chemicals much over the next 15 years.
   Keep in mind  that the  quantities shown in Tables 11.1 and 11.2 are
not the quantities  relevant to potential ozone depletion.  This is true
for two reasons.  First, these  are levels of use,  not of emissions: Deple-
tion becomes  a  possibility only  when these  chemicals  are emitted.
Most carbon tetrachloride is  never emitted because it is converted into
other  chemicals.   Halons are rarely emitted and  large  amounts  of
CFC-11 and CFC-12 are not  emitted until  years after they are initially
used.  Second,  emissions of equal quantities of different chemicals pose
varying levels  of potential threat to stratospheric ozone.   Despite its
high  level of  use, for example,  methyl  chloroform  is estimated  to
present  only  a modest  threat to stratospheric ozone.  CFC-11 and
CFC-12 are currently the  most important potential ozone depleters and
will probably continue to be for the next 15 years.
   The ranges  of uncertainty reported  in  Table 11.1  for CFC-11 and
CFC-12  require  aggregating  the ranges for each application of these
chemicals.  Similarly,  the ranges for all of the chemicals  reported  in

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84
Table 11.2 require aggregation across world regions. These ranges were
calculated using a method described in Camm and Hammitt (1986).i
DIRECTIONS FOR FUTURE WORK
   The research reported here suggests several potential directions for
future work. The first focuses on the areas where our understanding of
demand for potential ozone depleters is least  complete.  Demand out-
side the United States, particularly in communist countries, is an obvi-
ous  candidate.  Work is under way in this area, but progress is slow.
Formal data systems outside the United States are not nearly as good
as those within.  Producers of these  chemicals do not face the same
reporting requirements outside  the United  States  as they do  within.
And  the growing  policy  importance of information about  potential
ozone depleters  'can  create  incentives for governments  outside  the
United States, which might be asked to restrict the use or production
of these substances in the future, to make data collection more difficult
than it might otherwise be. Hence, although additional information in
this area would be  beneficial, its collection is also proving to be costly.
   It would also be useful to know more about the product areas or
applications of CFC-11 and  CFC-12  not  explicitly captured  by the
"bottom-up" approach used here, in the United States and elsewhere.
As Appendix B suggests, these are likely to fall primarily in the refrig-
eration area.  If they do, this is important information for policymakers
because refrigeration applications of CFCs are  more difficult to displace
than other uses. Whatever accounts for the shortfalls, better informa-
tion about them would obviously improve our ability to project global
and U.S. demand for CFC-11 and CFC-12.
   Finally, it would be valuable to give greater formal attention to the
sources  of uncertainty  underlying these  projections. As explained in
Appendix C, the current formulation uses the concept of a subjective
probability  distribution to  combine information  on  different sources of
uncertainty.  The  details of the method are  explained in  Camm and
Hammitt (1986).  At present, we assume that the levels of chemical use
in  each application, conditional  on  the  level  of general  economic
   1Briefly, we assume that the growth rates for each chemical are normally distributed
 and composed of one term corresponding to general economic growth and a second term
 describing growth conditional on the level of GNP.  The term corresponding to GNP
 growth is common  to all applications within a  region,  whereas the second term is
 independent of the first and independent across applications.  We assume that the
 second term for the unallocated applications of CFC-11 and CFC-12 is distributed like
 the average of the terms for the analyzed applications.  To aggregate across regions we
 assume that both' GNP and chemical use relative to GNP are correlated across regions,
 both with correlation coefficients of 0.75.

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                                                                 85
activity, are independent of one another. However, there are clearly
applications where use is positively or negatively correlated. For exam-
ple, if some of the more toxic solvents that compete with CFC-113 and
methyl chloroform were subjected to stricter regulation, both CFC-113
and  methyl chloroform use  could be expected to  increase.  Alterna-
tively, if substitution of reciprocating chillers for centrifugal units were
to occur at a more rapid pace than we project, CFC use in reciprocating
chillers would increase and use in centrifugal units would decline.  We
have not been  able to take these correlations into account as yet, in
part because we have too little information to estimate the size of the
effects.
   In summary, we conclude that demand for potential ozone depleters
as a class  is likely to grow at a modest rate  over  the next  15 years.
Some chemicals will  grow faster than others  but the relative mix of
these chemicals in the world economy should not change markedly over
this  period. For specific chemicals, possibilities clearly exist  for much
more rapid growth or for almost no growth at all.  Further work could
allow us to refine our understanding of these basic trends.

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                          Appendix A

  ESTIMATES  OF CURRENT CONSUMPTION OF
 CFC-11, CFC-12, METHYL CHLOROFORM, AND
               CARBON TETRACHLORIDE
  The estimates of current chemical consumption reported in the text
are  intended to serve two purposes. First, we wish to present an accu-
rate overview of current  use of each  of the seven  potential  ozone
depleters we analyze.  Second, since we base our projections of future
use on these estimates, we want estimates that fairly  characterize use
in the mid 1980s.  We wish to avoid basing our projections on the level
of consumption  in any single year because, if that year is atypical, the
difference between consumption in that year and a more representative
estimate would be propagated in the projections for all  future years and
even inflated because of the projection methodology.1
  In  addition, although our analysis focuses on  consumption of the
potential ozone depleters, available data measure production.2 For total
use of CFC-11 and  CFC-12 in the reporting countries we  believe the
difference is not significant, because trade in these chemicals between
the reporting  and communist countries  is probably negligible.  In con-
trast, U.S. use may  differ  significantly from U.S.  production, reported
by  the U.S. ITC, because of substantial imports  and exports.  More-
over, for both reporting country and U.S. estimates, inventory adjust-
ments across  years  and other factors, although probably small, could
affect the annual totals.
  To accurately characterize the level  of reporting country and U.S.
use of the potential ozone depleters whose production is reported, we
have developed  estimates using not one year but the last several years
of reported production.  These estimates are  based  on simple  linear
regression  models describing reported annual production as a function
of time,  for 1979 through 1984 or  1985 if available.  Our  estimate of
   'If two otherwise identical projections use different base levels, projected levels in all
future years will differ by the same factor as the base year levels. Because future use is
expected to be greater than current use, the absolute difference will expand over time.
   2Published total production estimates are available for  CFC-11 and CFC-12 in the
reporting countries and, in the United States,  for  CFC-11,  CFC-12, methyl chloroform,
and carbon tetrachloride. For the other chemicals and regions our estimates of total con-
sumption are derived in the main text.
                                 87

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88
1985 consumption is  simply  the  level of production  predicted by the
corresponding estimated regression equation. We  do  not use pre-1979
data because production of CFC-11,  CFC-12, and  carbon tetrachloride
declined sharply in earlier years, largely as a result of the ban on most
aerosol applications  in the  United  States and other countries. The
production trends show a definite shift beginning in 1979.
  This method for estimating current consumption is implicitly based
on two assumptions.   First, it  assumes that annual  production, after
adjusting  for business cycle  and other fluctuations,  has increased or
decreased by the same absolute amount over the period 1979 to 1985.
As will be shown below, except for  a few anomalous years, this is a
good approximation.   Second, the method assumes that consumption is
on average equal to production. For  the reporting  countries as a whole
this approximation is accurate,  but for the United  States the difference
between production and consumption may be wider.  However, because
there is apparently no source of systematic, publicly available informa-
tion on imports and exports of these  chemicals, we are unable to adjust
for either the average level of net imports  or for changes in  net imports
over time.
REPORTING COUNTRY CONSUMPTION OF CFC-11 AND
CFC-12

   Table A.I reports the estimated regression  equations for reporting
country production of CFC-11 and CFC-12.  Because the 1985 CMA
data are not yet available,  we base our estimates on the 1979 through
1984 reports.  The regression estimates imply that reporting country
production has grown an  average of about 3,000 mt  annually  since
1979.  Table  A.2  reports  the  actual  reported  production and the
amount predicted by  the  estimated  regression equation.  As shown
there, the regression predictions are quite accurate for both CFCs and
all years except 1982 and  1984.  Production in 1982 was significantly
smaller than predicted by  the regression equation, whereas 1984  pro-
duction was significantly larger.3 Whether 1984 marks the beginning of
a  period of substantial growth or simply  an aberration  will not be
known for several years.  For the present, we estimate 1985 production
and  consumption by extrapolating along the estimated regression line
to obtain 300,000 mt of CFC-11 and 365,000 mt of CFC-12.4
   3We judge the differences to be practically significant. They are not statistically sig-
nificant by conventional criteria.
   4We have rounded the estimates to the nearest 5,000 mt.

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                                                                89
                            Table A.I

         REGRESSION ESTIMATES OF REPORTING COUNTRY
                  CFC-11 AND CFC-12 PRODUCTION
CFC-11
Independent
Variable
Constant
Year
Estimated
Coefficient
-5690
3.02
t-statistic
-0.91
0.95
CFC-12
Estimated
Coefficient
-6240
3.33
t-statistic
-0.73
0.77
       Dependent variable: reported annual production in thousands of mt
       R-squared:           0.185                 0.129
       RMSE:             13.2                  18.1
       Sample size:           6                    6
                            Table A.2

         REPORTED AND PREDICTED REPORTING COUNTRY
                  CFC-11 AND CFC-12 PRODUCTION
                        (In thousands of mt)

                    CFC-11                  CFC-12
             Reported   Predic-  Differ-   Reported   Predic-  Differ-
       Year  Production   tion   ence   Production   tion    ence
1979
1980
1981
1982
1983
1984
1985
289.5
289.6
286.9
271.4
291.8
312.4
na
282.7
285.7
288.8
291.8
294.8
297.8
300.8
+6.8
+3.9
-1.9
-20.4
-3.0
+14.6
—
357.2
350.2
351.3
328.0
355.3
382.1
na
345.7
349.0
352.4
355.7
359.0
362.3
365.6
+11.5
+1.2
-1.1
-27.7
-3.7
+19.8
—
         NOTE:  na = not available.

UNITED STATES CONSUMPTION OF CFC-11, CFC-12,
METHYL CHLOROFORM, AND CARBON TETRA-
CHLORIDE
  The ITC reports U.S. production of CFC-11, CFC-12, methyl chloro-
form, and carbon tetrachloride.  However, because the United States
imports and exports substantial quantities of these chemicals, domestic
consumption need not correspond to production. Moreover, there have

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90
been major shifts in international chemical trade  over the last several
years with the United States importing more and exporting less than
before.5 However, because systematic import and export data for these
chemicals are apparently not publicly available, we are unable to adjust
for this shift.  As a result, our estimate of 1985 production may be a
downward-biased  estimate of current consumption.  However, such a
bias would not have a substantial effect on projected world consump-
tion of CFC-11, CFC-12, or carbon tetrachloride, since its only effect is
to incorrectly distribute  total consumption between the United States
and other reporting countries.  Since  the projected growth rates  for
these two  regions do not differ widely, the  effect on projected  world
consumption would not be large.  Our estimates of methyl chloroform
consumption in the non-U.S.  reporting and communist  countries are
based on  estimated U.S.  use, however.  If the U.S.  estimate is biased,
the estimate of the world total may also be biased.
   Table A.3 reports the  estimated regression equations  for U.S. pro-
duction of CFC-11 and CFC-12. As shown, average annual production
has increased only about 500 mt per year over the  post 1979 period.  As
described above, we believe that U.S. use  has grown more rapidly than
production because of increased imports  and declining exports.  The
low R-squared values do not indicate that the regression models do not
accurately summarize the production data. The values are low because
the general trend  is essentially flat, so  a linear function of time cannot
explain much of the variation in annual production.
   As shown in Table A.4, the values predicted by the regression equa-
tion are  quite close to  the  reported production levels.  As  for the
reporting  country totals, reported  1982  production  is  significantly
below  the model  prediction and reported 1984 production is signifi-
cantly above the  prediction.   After  rounding,  our estimates for 1985
consumption of CFC-11 and CFC-12 are 75,000 and 135,000 mt, respec-
tively, about 1,000 and 7,000 mt larger than the reported 1985 produc-
tion levels.
   The  regression estimates for methyl chloroform and  carbon  tetra-
chloride are  reported  in Table  A.5.  Annual U.S. production has
declined on  average over recent years, about  7,000 mt  per year.  As
shown  in  Table  A.6, reported 1982  production is lower than that
predicted by the regression equation, whereas reported 1984 production
   5Much of this shift is presumably attributable to the recent strength of the U.S. dol-
lar. For at least some chemicals the shift has been dramatic. For example, using data
from the Chemical Marketing Reporter profiles on trichloroethylene (January 27,  1986)
and perchloroethylene (February 3, 1986), we calculate that the  increase in  net imports
(imports minus exports) of these chemicals between 1980 and 1985 was about 40 and 27
percent of the 1985 U.S. consumption of these chemicals, respectively.

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                                                               91
                       Table A.3

         REGRESSION ESTIMATES OF U.S. CFC-11
                AND CFC-12 PRODUCTION
CFC-11
Independent
Variable
Constant
Year
Estimated
Coefficient
-1190
0.636
t-statistic
-0.49
0.52
CFC-12
Estimated
Coefficient
-474
0.307
t-statistic
-0.10
0.12
Dependent variable:  reported annual production in thousands of mt
R-squared:            0.052                   0.003
RMSE:                6.4                    13.0
Sample size:            7                       7
                       Table A.4

         REPORTED AND PREDICTED U.S. CFC-11
                AND CFC-12 PRODUCTION

                    (In thousands of mt)

               CFC-11                    CFC-12
       Reported   Predic-  Differ-   Reported   Predic-  Differ-
Year  Production   tion     ence   Production    tion    ence
1979
1980
1981
1982
1983
1984
75.8
71.7
73.9
63.5
73.0
83.9
71.8
72.4
73.0
73.7
74.3
74.9
+4.0
-0.7
+0.9
-10.2
-1.3
+9.0
133.4
133.8
147.4
117.0
134.3
152.9
134.3
134.6
134.9
135.2
135.6
135.9
-0.9
-0.8
+12.5
-18.2
-1.3
+17.0
1985     73.9      75.6    -1.7     127.9     136.2     -8.3

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92
                             Table A.5

         REGRESSION ESTIMATES OF U.S. METHYL CHLOROFORM
             AND CARBON TETRACHLORIDE PRODUCTION
                     Methyl Chloroform
 Carbon Tetrachloride
         Independent  Estimated             Estimated
          Variable    Coefficient   t-statistic   Coefficient   t-statistic
Constant
Year
R-squared:
RMSE:
Sample size:
14,400
-7.13
0.400
21.1
7
1.82
-1.79



13,800
-6.80
0.233
29.2
7
1.26
-1.23



                             Table A.6

         REPORTED AND PREDICTED U.S. METHYL CHLOROFORM
             AND CARBON TETRACHLORIDE PRODUCTION

                          (In thousands of mt)
                 Methyl Chloroform
Carbon Tetrachloride
Reported
Year Production
1979
1980
1981
1982
1983
1984
1985
325.0
314.0
279.0
270.0
265.8
306.2
268.1
Predic-
tion
311.1
304.0
296.9
289.7
282.6
275.5
268.4
Differ-
ence
+13.9
+10.0
-17.9
-19.7
-16.8
+30.7
-0.3
Reported
Production
324.0
322.0
330.0
266.0
259.9
323.4
283.0
Predic-
tion
321.6
314.8
308.0
301.2
294.4
287.6
280.8
Differ-
ence
+2.4
+7.2
+22.0
-35.2
-34.5
+35.8
+2.2
is higher, the same pattern as for the CFCs in both the United States
and the  reporting countries as a whole.  However, reported U.S. pro-
duction of  methyl chloroform and carbon tetrachloride has fluctuated
more  (in absolute level)  than reported CFC production, as shown by
the larger  differences between the  reported and predicted production
levels. After rounding, we estimate  1985 U.S. consumption of methyl
chloroform and carbon tetrachloride as 270,000 and 280,000 mt, almost
identical to the reported production levels.

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                         Appendix B

  COMPARISON OF ESTIMATED TOTAL CFC-11
     AND CFC-12 USE WITH OTHER SOURCES
  Our estimates of total  CFC-11  and CFC-12 use  are constructed
"from the bottom up." That is, we estimate use in each application
considered, usually by combining estimates of total final product pro-
duced and CFC use per unit of product. Our estimate of total use is
simply the  sum of the estimates for each application.  In this section
we  compare our estimates to  total reporting country production of
CFC-11 and CFC-12 reported by the Chemical Manufacturers Associa-
tion (CMA, 1984) and total U.S. production reported by the U.S. Inter-
national Trade Commission (U.S. ITC,  1984). Our estimates are sub-
stantially lower than the CMA  and  ITC totals. Estimated CFC-11 use
is about 18 percent lower for the United States and 8 percent lower for
the reporting countries.  For CFC-12, our U.S. estimate is 31 percent
lower and the reporting country estimate is  about 23 percent too small.
To  understand the source  of these  discrepancies we also  compare our
current estimates to those in earlier Rand  work (Palmer et  al., 1980)
and to those published by DuPont (1978).
  Our estimates for the other chemicals  are based on published or
industry-supplied estimates of  total use that we  allocated to various
applications.  These "top-down" estimates  necessarily  agree with the
published totals.1
COMPARISON OF ESTIMATED CFC-11 USE
  Table B.I summarizes estimated current use of CFC-11 by applica-
tion and compares it to ITC and CMA reported total use in the United
States  and reporting countries.  The  CMA estimates in each applica-
tion are for 1984, when reported production totaled 312,400 mt. The
ITC and CMA totals are based on annual production since 1979 and
are  derived in Appendix  A.  The Rand U.S. estimate  is 18 percent
lower than the adjusted ITC figure, whereas the reporting country esti-
mate is 8 percent smaller than the adjusted CMA number.
   'Note that estimated carbon tetrachloride use depends largely on reported CFC pro-
duction levels and does not fall into either category.
                               93

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94
                            Table B.I

             COMPARISON OF ESTIMATED 1985 CFC-11 USE

                              (In mt)

                                         Total Reporting
                            United States      Countries
Application
Aerosol
Foam production
Closed cell
Open cell
Refrigeration and
air conditioning
Miscellaneous
Total
"Estimated 1985
Rand
3,800
38,300
14,800
4,400
450
61,750
use is
ITC
na
na
na
na
na
75,000"
derived in
Rand
93,700
115,800
57,000
9,900
450
276,850
Appendi}
CMA
97,500
110,600
63,300
23,900
17,000
300,000"
c A. The
            CMA reported applications total 312,300 mt.
  The ITC does  not provide estimates of use by product area.  Com-
parison of the Rand and CMA estimates reveals the Rand numbers to
be comparable in  aerosols and foam production but substantially lower
in the refrigeration  and miscellaneous categories, 14,000 and 17,000 mt
lower, respectively.  This suggests that there may be significant use in
other applications we  have not explicitly considered,  including some
refrigeration and air conditioning applications. The difference between
the adjusted  CMA  total and the Rand reporting  country estimate is
23,000  mt.  Comparison of the Rand U.S. and ITC estimates suggests
that 13,000 mt, about  half of the unallocated uses, are in the United
States.
COMPARISON OF ESTIMATED CFC-12 USE

  Estimated CFC-12 use is presented in Table  B.2 together with the
ITC and CMA estimates. Again, the ITC and CMA totals are based on
recent production trends and are derived in Appendix A. The report-
ing country estimate is 23 percent smaller than the adjusted CMA fig-
ure, whereas the U.S. estimate is about 31 percent lower  than the
adjusted ITC  estimate.  Comparison of specific product areas again

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                                                                   95
reveals the Rand estimate to be much smaller than the CMA estimate
for refrigeration categories:  We estimate only 98,000  mt in the report-
ing countries  in comparison to 188,000 mt reported by CMA, a differ-
ence of 90,000 mt or 48 percent.
   The Rand  aerosol estimate of 115,600 mt is slightly lower than the
CMA figure  of 121,300.  The Rand foam production estimate is also
somewhat lower than the CMA estimate, 42,800 versus 49,200 mt,2 but
the miscellaneous use estimates are very close.
   The  difference  between  the  adjusted CMA  total  and  the  Rand
reporting country  estimate  is 83,000 mt. The  difference in the U.S.
estimates is 42,000 mt, again about half the difference in  the reporting
country estimates.

                              Table B.2

              COMPARISON OF ESTIMATED 1985 CFC-12 USE
                                (In mt)
United States
Application
Aerosol
Blowing agent
Closed cell
Open cell
Total
Refrigeration and
air conditioning
Mobile air conditioning
Retail food
Centrifugal chillers
Reciprocating chillers
Home appliances
Total
Miscellaneous
Total
Rand
5,700

14,900
—
14,900


50,400
4,800
1,600
300
2,400
59,500
12,700
92,800
ITC
na

na
—



na
na
na
na
na
—
na
135,000°
Total Reporting
Countries
Rand
115,600

42,800
—
42,800


73,400
9,700
3,700
1,300
10,200
98,300
25,400
282,100
CMA
121,300

30,700
18,500
49,200


na
na
na
na
na
187,500
24,100
365,000"
            "Estimated 1985 use  is derived in Appendix A.  The CMA
          reported applications total 382,100 mt.
   2Note the difference in classification of foam production. Rand attributes all CFC-12
use to closed-cell foams and CMA attributes part to open-cell foams.

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96
COMPARISON WITH EARLIER RAND WORK
  In Table B.3  we compare the Rand 1985 U.S. CFC-11 and CFC-12
nonaerosol use  estimates with the  1976 estimates of Palmer et al.
(1980).  Between 1976 and 1985 these applications grew  at estimated
average annual  rates of 5.3 percent for CFC-11  and 2.3 percent for
CFC-12.
  Most of the CFC-11 growth is attributable to insulating (closed-cell)
foams. In flexible  (open-cell) foam  applications  CFC-11  use  declined
slightly reflecting  an  increase in  the use  of  methylene chloride.
Estimated use of CFC-11 in chillers  increased slightly and the amount
going to other applications remained approximately constant.
  In the  United States most  CFC-12 is used in refrigeration and air
conditioning  applications.  Between 1976 and 1985 estimated use in
each of these decreased or remained constant, except for mobile air
conditioning  where the increased  number of air  conditioned vehicles
more than offset the declining average charge.  Estimated use in  chill-
ers  declined  slightly, reflecting lower leakage and servicing  rates in
reciprocating chillers.  Estimated retail food  use  remained approxima-
tely  constant,  whereas CFC-12  use  in  home  appliances  declined

                             Table B.3

          COMPARISON OF RAND ESTIMATES OF 1976 AND 1985
               U.S. NONAEROSOL CFC-11 AND CFC-12 USE
(In mt)
CFC-11
Application
Blowing agent
Closed Icell
Open cell
Refrigeration and
air conditioning
Mobile air conditioning
Retail food
Chillers"
Home appliances
Miscellaneous
Total
1976

16,783
15,422


—
—
3,674
—
450
36,329
1985

38,300
14,800


—
—
4,400
—
450
57,950
CFC-12
1976

10,433
—


40,733
4,822
2,227
2,841
10,049
71,105
1985

14,900
—


50,400
4,800
1,900
2,400
12,700
87,100
             SOURCE: 1976 estimates from Palmer et al. (1980).
             "Centrifugal and reciprocating chillers combined.

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                                                                97
somewhat because of a reduction in the average initial charge.  In con-
trast, CFC-12 use in closed-cell foam (polystyrene sheet and board) and
other uses increased substantially.
  The estimates  for CFC-11 and  CFC-12  use  in 1976  are 8,600 and
14,600  mt smaller than production reported by  the U.S. ITC.  In con-
trast, the current estimates are 13,250 and  42,200 mt short, indicating
a growth in unidentified uses, especially  of CFC-12.3 In the next sec-
tion we attempt to identify other product areas  where the CFCs might
be used.
COMPARISON WITH DUPONT ESTIMATES

  Table B.4 compares 1976 CFC-11 and CFC-12 use as estimated by
Rand (Palmer et al., 1980) and by DuPont (1978).  The DuPont esti-
mates for each product area include all  CFCs used  for that purpose,
making  comparison of use by chemical difficult.  For example, the total
for food processing and handling includes use of  CFC-12, CFC-22, and
CFC-502.  However, by  making some simple  assumptions we can
obtain some insight into the composition of our unallocated uses. Our
estimates of the likely uses included in our unallocated sector are sum-
marized in Table B.5.
  The  Rand and  DuPont estimates  of CFC use  as a  foam blowing
agent are similar.  In  flexible foams, Rand's estimate of CFC-11 use
exceeds  DuPont's by about 3,000 mt. In rigid foams,  the comparison is
complicated by the use of both CFC-11 and CFC-12. The Rand total
of CFC-11 and CFC-12, 27,200 mt, is about 1,000 mt smaller than the
DuPont total for rigid  polyurethane and polystyrene  foams, 28,350 mt.
However, DuPont reports an additional 2,000 mt of CFCs used in other
foam, most of which is probably CFC-11 and CFC-12.  Thus DuPont
estimates greater use  in  rigid foam  and smaller use in  flexible foam
than Rand, but the total foam blowing estimates are very close.
  The major differences  are in the refrigeration and air conditioning
categories, especially in air conditioning and in food processing and
handling. The estimates for air conditioning,  including mobile air con-
ditioning and chillers,  differ by about 18,200 mt (after combining the
Rand CFC-11 and  CFC-12 estimates).  As indicated in note b to Table
B.4, we  have all ready  subtracted Rand estimates of  the  CFC-500 and
some  of the CFC-22   included in the DuPont  figure.   Most  of the
  3Part of the difference between the estimates of unallocated uses in 1976 and 1985 is
attributable  to differences  in accounting procedures:  Palmer et al. (1980)  explicitly
accounted for exports, intermediate use, and storage,  packaging, and transport losses
from the unallocated uses.

-------
98
                                 Table B.4

            COMPARISON OF RAND AND DUPONT ESTIMATES OF
               U.S. 1976 NONAEROSOL CFC-11 AND CFC-12 USE

                                    (In mt)
                                    Rand
                        DuPont
              Application
CFC-11   CFC-12  Quantity
            CFCs
         Blowing agent
           Flexible foams
           Rigid foams
 15,422     —
12,202
11
Polyurethane
Polystyrene
Other

Total

Refrigeration and
air conditioning
Air conditioning
Food processing
and handling
Refrigerators and
freezers
Small appliances
Industrial process
refrigeration
Miscellaneous
Miscellaneous uses
Liquid fast freezing
Sterilants
Other
Total




16,783 10,433



3,674 42,960"

— 4,822

— 2,841
— —

— —
— —

— 2,722
— 5,897
450 1,430
36,329 71,105
20,094
8,255
2,041

30,390



64,819°

33,112C

3,130
1,270

2,087
907

2,722
5,897
—
184,296
11, 12
12
11, 12,
113, 114, 115
11, 12,
113, 114, 115


11, 12, 22

12, 22, 502

12
12

12, 22
12

12
12
—
All CFCs
            SOURCES:  DuPont (1978), Palmer et al. (1980).
            'Includes CFC-12 in centrifugal  and reciprocating  chillers and
         mobile air conditioning.
            bDuPont estimate less estimated  635  mt of CFC-500 in chillers
         (Palmer  et al.,  1980, p. 147) and 1,361, 20,865, and 13,154 mt of
         CFC-22 used in in chillers, home, and supermarket air conditioning,
         respectively (Palmer et al., 1980, p. 35).
            °DuPont estimate less estimated 4,763  mt of CFC 502 and 680 mt
         of  CFC-22 used in  retail food applications (Palmer et  al., 1980, p.
         178).

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                                                               99
                            Table B.5

                ESTIMATED SHORTFALL IN RAND 1976
                ESTIMATES OF U.S. CFC-11 AND CFC-12
              USE COMPARED WITH DUPONT ESTIMATES

                              (In mt)

                                         Shortfall
Application
Air conditioning
Food processing and handling
Refrigerators and freezers
Small appliances
Miscellaneous
Industrial process refrigeration
Total
CFC-11
9,100
—
—
—
—
—
9,100
CFC-12
—
14,150
300
1,270
907
1,044
16,671
remaining difference is likely to be CFC-11 and CFC-22.  If we arbi-
trarily assume that half is CFC-11 the estimated Rand shortfall in this
category is 9,100 mt.
  In  food processing and handling, Rand analyzed only retail food
store  refrigeration systems.  As indicated  in note c of Table B.4, we
have subtracted Rand estimates of CFC-22 and  CFC-502 used in retail
food store applications from the  DuPont figure.  We  do not  know
whether this accounts for all the CFC-22 and CFC-502 included in this
category.  Even after this adjustment, the DuPont figure  exceeds the
Rand estimate by 28,300 mt.  If we arbitrarily assume that CFC-12
represents half of this difference (the same share as its share of retail
food store refrigeration applications), then Rand's estimate of CFC-12
use in food handling and processing is estimated as 14,150 mt too low.
  DuPont's estimate of CFC-12 use in home refrigerators and freezers
exceeds the Rand estimate by about 300 mt.  Dupont reports additional
CFC-12 use  of 1,270 mt of CFC-12 in small applicances and 907  mt in
miscellaneous  refrigeration applications, categories that  Rand did not
analyze.  DuPont also reports 2,087 mt of CFC-12 and CFC-22 used in
industrial process refrigeration.  If we  arbitrarily assume that half this
amount is CFC-12,  the  implied  Rand  shortfall is 1,044  mt  in this
category.
  Table  B.5 summarizes the differences as estimated above. To sum-
marize,  comparison  with  the DuPont estimates  suggests that  about
9,000 mt of  CFC-11  not accounted for by Rand is probably used in air
conditioning.  This  figure is very close to the  8,600  mt  difference

-------
100
between  the  Rand  estimate  and the ITC total.  In addition, some
17,000 mt of CFC-12 not accounted for by Rand may be used primarily
in food processing and handling.  Again, this estimate is close to the
14,500 mt difference between the Rand and ITC totals estimates.
SUMMARY OF COMPARISONS

  Rand estimates of CFC-11 and CFC-12 use in the United States and
reporting countries  are smaller than ITC and CMA  reported produc-
tion levels. The CFC-11 estimates are 13,000 mt lower for the United
States, and  23,000  mt lower for  the reporting countries.  Estimated
CFC-12 use  is 42,000 mt lower for the  United States  and 83,000 mt
lower in the reporting countries. Thus, about half the reporting coun-
try use of each CFC that we do not account for apparently  occurs in
the  United States.   In contrast,  estimated  total  CFC-11 use in the
United States is about 25 percent, and CFC-12 use about 37 percent, of
the estimated reporting country totals.
  Comparison of our estimates by application suggests that much of
the shortfall, particularly of CFC-12, is in refrigeration and air condi-
tioning  applications.  For the  reporting countries,  comparison  with
CMA estimates suggests that our estimates  fail to account for 17,000
mt of CFC-11 in miscellaneous applications and for 14,000 mt of CFC-
11 and 98,000 mt  of CFC-12  used as refrigerants.  Comparison with
estimates for the EEC and some other reporting countries recently fur-
nished by the European Fluorocarbon Technical Committee  (EFCTC,
1985) supports this conclusion.
  For the United States, Rand's current  estimates  are consistent with
its estimates for 1976 but the  current estimates account for  a  smaller
share of total U.S.  use (based on ITC production reports), suggesting
that  use  in  other applications  has  grown.  Comparison of the Rand
1976 U.S. data with DuPont estimates for the same year suggests that
the Rand estimates fail to account for about 9,000  mt of CFC-11 used
in air conditioning  and 17,000 mt of CFC-12 used primarily  in food
processing and handling refrigeration  applications.

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                           Appendix C

             DERIVATION OF SUBJECTIVE
                CREDIBILITY INTERVALS
   The ranges of uncertainty for projected chemical use and for each of
the three levels of uncertainty described in Sec. II can be interpreted as
subjective 80 percent credibility intervals.  When one must act in the
face of uncertainty about future outcomes that will affect the desirabil-
ity of the chosen action,  a long line of analytic work recommends the
use  of subjective probability distributions for the relevant outcome.1
We  choose to present 80 percent credibility  intervals, rather than the
more conventional 90 or 95 percent levels, because  experimental  evi-
dence shows that people are often poor at  thinking about small proba-
bilities.2  Using 80  percent  credibility  intervals  should enable  us to
assess the ranges, and readers to interpret them, more accurately.
   The subjective credibility intervals for chemical use are derived from
the intervals corresponding to each level of uncertainty.  The procedure
is exact  if the  subjective probability distributions  for each  level of
uncertainty are log-normal.  If not,  it at least provides a useful heuris-
tic for calculating the credibility intervals.
   To calculate the subjective  credibility interval for chemical use we
posit a random variable associated with each level of uncertainty that
is multiplied by the  base projected use.  These random variables are
assumed  to be log-normally  distributed with the median equal to one.
This assumption implies that the  probability that the outcome variable
is more than Z times  the  projected level is  equal to the probability that
it is less  than 1/Z times the projected level.  For example,  actual GNP
is as likely to be  more than  1.5 times the  projected level as it  is to be
less  than two-thirds of that  level.  For projecting future chemical pro-
       Raiffa (1968) for a very clear description of the principles and a historical over-
view.
   For an extensive reporting of the experimental evidence on common  difficulties in
evaluating probabilities see Kahneman, Slovic, and Tversky (1982). The work reported
there suggests that most people overestimate their ability to predict random variables,
especially when attempting to use high credibility-level intervals.  When assessing subjec-
tive 90 or  99 percent credibility regions, the random variable falls outside the region far
more often than the theoretical 10 or 1 percent of cases.
                                  101

-------
102
duction the  log-normal distribution provides a close approximation to
most of our subjective probability distributions.3
   The random variable describing the uncertainty about total chemical
use is the product of the random variables corresponding to each level
of uncertainty.  Since the random variables are  independent (by con-
struction) and  the  median of each factor is one, the base projections
reported  in the text constitute the median of  the subjective credibility
intervals. If, as we assume, each of the components is distributed log-
normally then  so is final chemical use.  Moreover, the parameters of
the  distribution of chemical  use  can be readily obtained  from the
parameters   of  the  distribution functions  of  the  component  random
variables, which can  in turn be derived from  the subjective credibility
intervals.  Hence, it is  a simple  procedure to calculate  a credibility
interval  for  chemical use from the subjective credibility  intervals for
each level of uncertainty.4
   If one is  unwilling to characterize his  subjective  uncertainty about
one  or  more of the random variables describing each level of uncer-
tainty as approximately  log-normal,  an  alternative  procedure  can be
used. However, it does not  provide an exact probability for the result-
ing  credibility  interval,  and the  bounds  on  that probability  may be
unhelpfully  wide.  The procedure  is  to calculate the range  of  possible
values for chemical use obtained by setting all  components at the limits
of their  respective  credibility  intervals.  For example,  assume  that we
believe an 80 percent credibility interval for GNP in 2000 ranges from
0.80  to 1.25 times the projected base value. Similarly, we believe that
the  80 percent credibility interval for final product use, conditional on
GNP, ranges between 0.67 and 1.50  times the projected use, and that
the  80  percent  credibility interval for use of chemical Y per  unit of
final product  ranges from 0.50 to 2.00 times the projected use.  The
alternative  credibility interval  for final use of chemical Y is from 0.27
(= 0.80  x 0.67  x 0.50) to 3.75 (=  1.25 x 1.50 x  2.00) times projected
use.  The probability that this interval  includes the  actual use is at
   3The ranges reported in the text are consistent with log-normal distributions in
almost all of the cases.  For a few minor CFC-11 and CFC-12 applications the ranges are
not geometrically symmetric about the base projections. To calculate the ranges for total
CFC-11 and CFC-12 use we adjust the base projections for these applications to obtain
the required symmetry.
   4If the distribution of X is log-normal  it can be characterized by two parameters:  fj.,
the expected value of the logarithm  of X, and a ,  the variance of the logarithm of X.
These parameters can be derived from the subjective credibility interval using a table of
the normal distribution function. The parameters of the distribution of chemical use are
simply the sum of the corresponding parameters of the distributions of each of its com-
ponents, and a credibility region for any chosen significance level can be derived with
reference to the tabulated normal distribution function.

-------
                                                                        103
least 0.51 (= 0.83) and no more than 0.99  (=!-(!- 0.8)3).5 In con-
trast,  if  these distributions  are  log-normal the  calculated  credibility
interval would include actual chemical  use with  probability 0.96, and
an  80 percent  credibility interval would range from 0.43 to 2.30 times
the base projected use.
   5In general, if the n  component credibility intervals have probability levels p,,  i =
1,2, . . . ,n, then the probability associated with the aggregate credibility limit will be at
least II Pj and at most 1 - II  (1 - p;) (assuming the component random variables  are
independent, as here).

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AW ANALYTJC  METHOD FOR CONSTRUCTING SCENARIOS  FROM A
   SUBJECTIVE JOINT POSSIBILITY DISTRIBUTION"
                         May   1986

-------
                           ACKNOWLEDGEMENTS

     This paper was written by Frank Camm  and  Jim  Hamrni U: oi
RAND corporation under contract with the U.S.  Eiivironmonta 1
Protection Agency.

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                                - Ill -
                               PREFACE
     This Note is one of a series of papers written at The Rand
Corporation on policy issues associated with chemicals that could
potentially deplete ozone in the stratosphere ("potential ozone
depleters").  Stratospheric ozone is important because the ozone layer
helps shield the earth from harmful ultraviolet radiation.  Increases in
ultraviolet radiation may threaten human health,  speed deterioration of
certain materials, reduce crop yields,  and have a wide range of
potentially important ecological effects.   Atmospheric models developed
and tested over the last decade suggest that global human emissions of
potential ozone depleters may lead to chemical reactions that reduce
stratospheric ozone, thereby increasing ultraviolet radiation with its
concomitant effects.  Substantial scientific uncertainty persists about
whether human emissions of these chemicals actually threaten the
stratospheric ozone layer and, if they do, whether lower ozone levels
actually threaten human health and other activities at the earth's
surface that concern policymakers.  Policymakers  must act in the face of
this uncertainty, however, and Rand's work is designed to help them act
with the best information available.
     To that end, The Rand Corporation is developing a series of reports
addressed to analysts and policymakers responsible for policy decisions
on emissions of potential ozone depleters in the United States and
elsewhere.  These documents report the results of research that includes
extensive literature reviews, interviews with knowledgeable officials
associated with the production and use of potential ozone depleters, and
formal chemical, cost, economic, and statistical  analyses.  The series
should also interest the much broader audience of analysts and
decisionmakers whose organizations would feel the effects of government
policies with respect to emissions of such chemicals.
     Published papers in the series include the following:

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                        - IV -

A. R. Palmer, W. E. Mooz, T. H. Quinn, and K. A. Wolf, Economic
Implications of Regulating Chlorofluorocarbon Emissions from
Nonaerosol Applications, R-2524-EPA, June 1980.
A. R. Palmer, W. E. Mooz, T. H. Quinn, and K. A. Wolf, Economic
Implications of Regulating Nonaerosol Chlorofluorocarbon
Emissions:  An Executive Briefing, R-2575-EPA, July 1980.
K. A. Wolf, Regulating Chlorofluorocarbon Emissions:  Effects
on Chemical Production, N-1483-EPA, August 1980.
A. R. Palmer and T. H. Quinn, Economic Impact Assessment of a
Chlorofluorocarbon Production Cap, N-1656-EPA, February 1981.
A. R. Palmer and T. H. Quinn, Allocating Chlorofluorocarbon
Permits:  Who Gains, Who Loses, and What Is the Cost?
R-2806-EPA, July 1981.
W. E. Mooz, S. H. Dole, D. L. Jaquette, W. H. Krase, P. F.
Morrison, S. L. Salem, R. G. Salter, and K. A. Wolf, Technical
Options for Reducing Chlorofluorocarbon Emissions, R-2879-EPA,
March 1982.
E. M. Sloss and T. P. Rose, Possible Health Effects of
Increased Exposure to Ultraviolet Radiation, N-2330-EPA, July
1985.
T. H. Quinn, K. A. Wolf, W. E. Mooz, J. K. Hammitt, T. W.
Chesnutt, and S. Sarma, Projected Use, Emissions, and Banks of
Potential Ozone-Depleting Substances, N-2282-EPA, January  1986.
F. Camm, T. H.  Quinn, A. Bamezai, J. K. Hammitt, M. Meltzer, W.
E. Mooz, and K. A. Wolf, Social Cost of Technical Control
Options to Reduce  the Use of Potential Ozone Depleters in  the
United States:  An Update,  N-2440-EPA, May 1986.
J. K. Hammitt,  K.  A. Wolf,  F.  Camm, W. E. Mooz, T. H. Quinn,
and  A. Bamezai, Product Uses and Market Trends  for Potential
Ozone-Depleting Substances:  1985-2000, R-3386-EPA, May  1986.
W. E. Mooz,  K.  A.  Wolf,  and F. Camm, Potential  Constraints on
Cumulative Global  Production of Chlorofluorocarbons,
R-3400-EPA,  May 1986.

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                                 - v -
     This Note was produced under Cooperative Agreement No.
CR811991-02-0 with the U.S. Environmental Protection Agency.

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                                -  v 11  -
                               SUMMARY
     Over the last 12 years,  photochemical models of the upper
atmosphere have suggested that chlorofluorocarbons (CFCs) and several
related chemicals may reduce  the concentration of stratospheric ozone.
Reducing the concentration of stratospheric ozone may increase the
quantities of ultraviolet radiation penetrating to the earth s surface,
which may harm human health,  reduce crop yields, accelerate the
degradation of certain materials, and have other important adverse
effects.  These chemicals, which we call "potential ozone depleters" or
PODs, are emitted to the atmosphere primarily through human activities.
As a result, changes in government policies could reduce emissions of
PODs, thereby reducing their  effects on ozone and reducing the potential
negative effects mentioned above.  This Note is one of a series of
publications being produced by The Rand Corporation to support the
development of better information on this policy issue.
     Many uncertainties are important to the issue of potential ozone
depletion and its possible effects.  It is not even certain that PODs
affect ozone or that changes  in ozone concentrations have any of the
negative effects mentioned above.  The Environmental Protection Agency
(EPA) has developed a large model that allows consideration of these
uncertainties and their importance in policy decisions.  It is
developing scenarios to capsulize in simple illustrations important
information about the range of outcomes possible with current
uncertainty.  For example, to represent uncertainty about future global
emissions of methane, the EPA uses both a high growth and a low growth
scenario.  As part of its effort, The Rand Corporation  is helping the
EPA characterize the uncertainties about market  and technological
factors that may affect the future global production of  seven PODs:
CFC-11, -12, -113, carbon tetrachloride, methyl  chloroform, and Halons
1201 and  1301.  This Note explains how we use information about the
uncertainties associated with each of these chemicals separately to
develop scenarios that illustrate these uncertainties jointly in a
useful way.

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                                - vin -

     It is important to view the uncertainties associated with these
chemicals jointly.  For example, suppose we developed high growth
scenarios for each chemical separately and then used them to construct a
high growth scenario for the seven chemicals together.  Unless the
production levels of these chemicals always moved together, one would be
highly unlikely to observe high growth levels for all of them
simultaneously.  Historically, they have not moved together.  Hence,
such an approach would yield a scenario so unlikely as to be irrelevant
to policy considerations.
     The high growth scenario chosen must be meaningful to policymakers
in the sense that it must represent some likely range of events with,
from their perspective, a "high" effect.  The policymaker's perspective
in this problem is focused primarily on ozone depletion (although
chemicals discussed here probably also have an effect on climatic
change, another concern to EPA).  Hence, a "high" growth scenario should
include production patterns for  those chemicals that, if ozone depletion
is a serious problem,  are likely to lead to high ozone depletion.
Similarly, a low  growth scenario should be associated with  a  low  level
of potential ozone depletion.   Simply put, this Note provides a way  to
define production scenarios for  the seven chemicals examined  here that
policymakers could reasonably associate with  a range of likely levels of
potential ozone depletion.
     The technique used here  starts with subjective probability
distributions  for each chemical.  These are based on  detailed Rand
analysis, reported elsewhere, of possible production  of these chemicals
during the period 1985-2040.  Uncertainty about  the growth  rate  for  each
chemical  is  characterized by  the probability  distribution  of  the  sum of
two  normal variates.   The  first captures uncertainty  about  general
economic  growth,  and  the  second captures uncertainty  about  the growth in
 intensity of use  of  each chemical  relative  to general  economic growth.
      The  technique  then  uses  these  growth  rates  to  calculate  a rough
proxy for the  general rate  of growth  of these PODs.   The  proxy is
 defined  by a "score function" that  weights  and sums  the  growth rates for
 the seven chemicals.   The weights  used reflect three  important factors
 that help determine how  likely a chemical  is  to  affect ozone

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                                 - ix -
concentration:   its annual rate of production,  the fraction of its
production ultimately emitted into the atmosphere, and its ozone-
depleting potential per gram in the atmosphere.   That is,  the score
function simply weights growth rates to reflect their relative potential
effects on ozone depletion.   Because of the way it is constructed,
uncertainty about the value of the score function is also captured by a
normal distribution.
     We define scenarios in terms of quantiles  of the distribution of
the score function.  For example, a "high" growth scenario is associated
with the 75th percentile of the distribution; a "low" growth scenario
corresponds to the 25th percentile.  Each of these corresponds to a set
of events likely to have a "high" or "low" effect relevant to the
policymaker.  For each scenario, we then pick growth rates for the seven
chemicals that, when weighted and summed, yield the value of the score
function for that scenario.   An infinite variety of individual growth
rates is consistent with any value of the score function; this is a
generic problem in scenario construction.  We use a simple convention to
pick growth rates that treats all sources of uncertainty equally.
     Table S.I illustrates the scenarios generated with this technique
by showing the production levels for the seven chemicals in selected
years under each of three scenarios.
     The specific technique developed here allows us to convolute all
uncertainties about POD growth rates analytically.  To do this, we
express all sources of uncertainty as normal distributions and use some
simple approximations.  The same general approach could be used with a
broader range of distributional assumptions and without the
approximations used here.  It would require a simulation technique like
Monte Carlo, which is substantially more costly and usually requires
other kinds of approximations.  The technique developed here illustrates
the application of a general approach and provides a specific method to
implement it.  Although the general approach would easily allow more
complex implementations, it is by no means clear that they would be
superior to the technique used here.
     The specific technique used here would allow greater subtlety in
the specification of the subjective probability distribution that
provides its inputs.  For example, the scenarios developed here assume

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                                 - x -
                               Table S.I
                SELECTED PRODUCTION LEVELS FOR SCENARIOS
                BASED ON QUANTILES OF THE SCORE FUNCTION
                      (In thousands of metric tons)
Scenarios/Quantiles of the
Chemical
CFC-11
CFC-12
Carbon
tetrachloride
CFC-113
Methyl
chloroform
Halon 1301
Halon 1211
Year
1985
2000
2040
1985
2000
2040
1985
2000
2040
1985
2000
2040
1985
2000
2040
1985
2000
2040
1985
2000
2040
"Low"
0.25
342
498
1017
444
555
1124
1029
1391
2827
163
367
700
545
752
1517
11
17
26
11
17
31
"Medium"
0.50
342
556
1435
444
622
1606
1029
1554
4014
163
422
1091
545
844
2179
11
20
44
11
20
53
Score Function
"High"
0.75
342
619
2022
444
696
2287
1029
1736
5686
163
485
1695
545
946
3123
11
24
76
11
24
91
that the intensities of use relative to general economic activity for
any two chemicals are unrelated.   As better empirical information
becomes available on the substitutability of different PODs in
consumption or their jointness in production, the technique presented

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                                 - xi -
here could easily accommodate it.   The intensities of use for
substitutes in consumption would be negatively correlated;  those for
chemicals produced jointly would be positively correlated.   Such
relationships can have significant effects on the joint distributions of
related chemicals and should ultimately be reflected in this kind of
analysis.
     The specific technique can also be used to develop scenarios that
incorporate a much broader range of factors than those presented here.
Scenarios that reflect additional factors may be important  because of
the correlations among economic variables.  For example, if global
economic growth is high, both the rate of production for PODs and the
activities like agriculture that may potentially be affected by ozone
depletion will grow faster.  Assuring that "high economic growth"
scenarios for PODs are matched with similar scenarios for the effects of
ozone depletion on crop yields will yield a larger — and more accurate--
measure of the benefit from limiting POD emissions than would be
calculated if such scenarios were not matched.  Developing scenarios
that are conditional on general economic growth would allow such
matching.  The technique presented here would allow us to develop such
conditional scenarios in the future.
     Understanding how all of the uncertainties associated with
stratospheric ozone depletion relate to one another is a complex task.
The EPA is approaching this task by breaking it into manageable pieces,
where complex information about uncertainties can be condensed into
scenarios that effectively illustrate the breadth of the uncertainty.
The technique developed here shows a way to assure that, even though
scenarios relevant to different sources of uncertainty are developed
separately, they can still be related to the primary issue relevant to
policymakers—ozone depletion—and hence to the goals of the analysis as
a whole.

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                                - xni -
                         ACKNOWLEDGMENTS
     John Hoffman and Stephen Seidel organized an informal workshop that
gave us an early opportunity to present the general approach used here
and get suggestions.  Suggestions from Michael Gibbs,  Michael Kavanaugh,
and Gary Yohe were especially helpful.  James Hodges read an earlier
draft and provided detailed comments that have significantly improved
the Note.  Jan Acton helped facilitate its production  and review under
tight deadlines.  Mary Vaiana helped prepare the presentation of
material in this Note to the Environmental Protection  Agency's March
1986 workshop, "Protecting the Ozone Layer."  Participants in that
workshop, particularly Toby Page, provided helpful feedback.   Alyce
Shigg oversaw production of the many drafts underlying this Note and
Patricia Bedrosian edited the final draft.  We thank them all and retain
responsibility for any errors that remain.

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                                 -  xv -
                              CONTENTS
PREFACE  	

SUMMARY  	   vii

ACKNOWLEDGMENTS  	  xiii

FIGURES AND TABLES 	  xvii
Section

I.   INTRODUCTION  	     1
II.  BACKGROUND:  THE NEED TO COMBINE DISTRIBUTIONS FOR POTENTIAL
           OZONE DEPLETERS  	     4

       Wanted:  A Subjective Probability Distribution for Ozone
             Depletion  	     5
       Scenarios Based on a Proxy for Stratospheric Ozone
             Depletion  	     9

III.   THE DISTRIBUTION OF THE SCORE FUNCTION  	    15

       Aggregating Chemical Use  	    16
       Deriving Scenarios for Individual Chemicals from the Score
             Function  	    18

IV.  SUBJECTIVE MARGINAL PROBABILITY DISTRIBUTIONS FOR POTENTIAL
           OZONE DEPLETERS  	    22

       Methodology   	    22
       Subjective Probability Distribution for the Pre-2000
             Period  	    25
       Subjective Probability Distribution for the Post-2000
             Period  	    27
       Marginal Distributions for Individual Chemical Production  .    31

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                                - xvi -
V.  PRODUCTION SCENARIOS BASED ON QUANTILES OF THE
          SCORE FUNCTION  	   33

       Choosing the Quantiles To Use for Scenario Development  ....   33
       Chemical Use Scenarios 	   35

VI.   CONCLUSIONS  	   39
APPENDIX 	   43

REFERENCES   	   51

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                                -  xvii -
                               FIGURES
2.1.   Schematic view of potential causes  and effects  of
      stratospheric ozone depletion  	     6
                                TABLES
S.I.  Selected Production Levels for Scenarios Based on Quantiles
      of the Score Function  	     x

4.1.  Parameters of the Subjective Joint Probability Distribution
      in the Pre-2000 Period  	    26

4.2.  Parameters of the Subjective Joint Probability Distribution
      in the Post-2000 Period  	    31

4.3.  Production Levels at Specified Quantiles of the Subjective
      Marginal Probability Distributions for Individual
      Chemicals 	    32

5.1.  Chemical Weights  	    34

5.2.  z-statistics and B Values for Distributions of the Score
      Function and Components  	    36

5.3.  Growth Rates for Scenarios Before and After 2000  	    37

5.4.  Selected Production Levels for Scenarios Based on Quantiles
      of the Score Function  	    38

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                          I.   INTRODUCTION
     Over the past 12 years photochemical  models of the atmosphere have
suggested that global human-caused emissions  of certain
chlorofluorocarbons (CFCs) and related chemicals may reduce the
concentration of stratospheric ozone.   We  refer to these chemicals as
potential ozone depleters or PODs.   A sufficient reduction in
stratospheric ozone could allow substantially greater amounts of
ultraviolet radiation to penetrate to the  earth's surface, potentially
causing a wide variety of detrimental effects.   These effects include
significant threats to human health, reductions in crop yields,
degradation of certain materials, and other important adverse ecological
consequences.1  Scientists studying the possibility of ozone depletion
have not reached a consensus on the likelihood that these adverse
effects will occur in the foreseeable future.  However, because the PODs
survive in the atmosphere for many decades after their release, current
emissions may affect stratospheric ozone concentrations well into the
next century.  Consequently, if the probability that the PODs will cause
serious adverse effects is sufficiently high, policies that reduce
current human emissions of these chemicals may be warranted.
     The U.S. Environmental Protection Agency (EPA) has undertaken a
major effort to study these potential effects,  to characterize
systematically the uncertainties about them,  and to examine the likely
effects of alternative policies to control the emissions of PODs.
Ultimately, this effort will help policymakers compare the social costs
of controlling POD emissions with the social  benefits.  The social costs
of controls are represented by the benefits that must be forgone if the
commercial use of these chemicals is restricted.  The social benefits
are amelioration of the kinds of adverse effects mentioned above, where
possible expressed in monetary terms.
          details, see National Academy of Sciences (1976, 1979, 1982,
1984) or Ramanthan et al. (1985).

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     The Rand Corporation is participating in this effort by, among
other things, studying the market and technological factors that affect
current and future human emissions of PODs.   We focus on the seven most
important of these:  CFC-11, -12, and -113,  carbon tetrachloride, methyl
chloroform, and Halon 1211 and 1301.  Rand has developed information on
the likely sources of uncertainty associated with production of these
seven PODs (Hammitt et al., 1986; Quinn et al., 1986).  Previous Rand
reports analyze the production of each chemical independently.  Given
EPA's approach to convoluting uncertainties, however, it is important to
analyze the combined effect of all these chemicals on potential ozone
depletion.  Thus, we must characterize the joint uncertainty about
production of the PODs.   This Note explains why that is true and
develops a simple methodology for doing so.
     Our method focuses on uncertainties about production over time.2
However, it is not production but ultimate emissions of the PODs that
are relevant to potential ozone depletion.  At present, we calculate the
time path of emissions for each chemical production trajectory using
deterministic algorithms similar to those used in prior Rand work
(Palmer et al., 1980) and by the Chemical Manufacturers Association
(CMA).   Hence, the method does not capture the effect of any
uncertainties about the relationship between production and emission of
the chemicals.3
     Section II provides additional background on EPA's policy analytic
approach to potential ozone depletion and Rand's role in that approach.
It explains the conceptual basis for integrating Rand's information on
uncertainties about future chemical production into EPA's approach.
Section III describes the specific analytic method we use to convolute
uncertainties about the production of individual PODs to derive the
probability distribution for the joint production of these chemicals.
Our subjective probability distributions for production of individual
     2We treat annual production and use as equivalent, since production
inventories over periods of several years are negligible.
     3The character and importance of these uncertainties is an
important topic for future analysis.

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                                 - 3 -
chemicals are reported in Sec. IV.  These are based on Rand's past work
on future production and emissions of PODs.   Section V presents
production scenarios based on the joint distribution derived from the
distributions for each chemical.   Conclusions and suggested directions
for future work are presented in Sec. VI, and the computer code used to
implement our method is documented in the Appendix.

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         BACKGROUND:   THE NEED  TO COMBINE DISTRIBUTIONS
                 FOR POTENTIAL OZONE  DEPLETERS
     Many uncertainties impinge on the question of the  costs  imposed
over the next century by continuing emissions  of PODs.   These range from
questions about the future emissions trajectories of PODs  and of  other
gases that influence ozone concentration,  to questions  about  the  effect
of a specified set of emission paths on actual ozone concentration, to
questions about the effects of greater ultraviolet radiation  on human
health, crop yields, and degradation of materials, and  of  other
consequences of policy interest.   Uncertainties about each of these
factors contribute to the uncertainty about  the magnitude  of  the
potential threat and the effects  of alternative global  strategies  for
controlling the emission of PODs.   Moreover, the presence  of  this
pervasive uncertainty is an important factor in choosing an appropriate
policy, since a more flexible policy may be  preferred even to
alternatives that would perform better in  a  more certain environment.
     The EPA has designed a strategy for comparing the  effects of
alternative policies in the face  of these  many sources  of  uncertainty.
The strategy first reduces the broad range of  possible  futures to  a
fairly small set of cases and then examines  the effects of alternative
policies in each case.  The cases  are constructed through  the following
method:

     •   Isolate the principal factors that  contribute  to  uncertainty.
     •   For each factor, select  a small number of scenarios  to
         represent the range of uncertainty  about it.
     •   Construct cases by taking all possible combinations  of the
         scenarios for the different factors.

     The Rand Corporation is analyzing uncertainties about the emissions
of seven PODs.  To incorporate its work into EPA's framework, Rand must
develop scenarios to reflect the  nature of uncertainty  about  future
emissions trajectories for these  PODs.   In this section, we ask what

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kinds of scenarios would be appropriate.  We  begin  by noting that  an
explicit probability distribution  for  ozone depletion would be
preferable to the current use of discrete scenarios if  costs allowed.
However, because of the extreme complexity of the computer simulation
models of the atmospheric chemistry involved,  computation costs prevent
the use of Monte Carlo analysis to generate a distribution function for
ozone depletion.  As an alternative, we suggest  an  analytic method to
develop scenarios that approximate the kind of information that would be
produced by the preferred focus on a subjective  probability distribution

for ozone depletion.1


WANTED:  A SUBJECTIVE PROBABILITY DISTRIBUTION
FOR OZONE  DEPLETION
     The extent of possible ozone  depletion lies at the heart of EPA's
policy concerns.2  Essentially, the concern is that certain human
activities may lead to ozone depletion, which may  in turn affect the
quality of human life.  Figure 2.1 summarizes, in  a very cursory
fashion, the EPA's view of the problem and the links that must be
understood.  To understand it, start at the top of  the  figure and  work
down.  Market and technological  factors and government  policies, ranging
from the ban on most uses of CFCs  as aerosol  propellants to workplace
safety standards, currently affect POD emissions.   The  EPA  is
     lThere are two main alternative interpretations of probability--
the frequency interpretation and the subjective interpretation.   In the
frequency interpretation, which is more widely understood,  "the
probability of event A" is understood to mean the relative  frequency of
occurrence of event A in some (invariably hypothetical) infinite
sequence of repetitions of the mechanism in question.  In the subjective
interpretation, "the probability of event A" is a representation of
one's belief about the likelihood of event A's occurring.  That  is, the
first presumes the existence of a stochastic process that can be
observed to get empirical information about the probability of an event,
whereas the second is a formal way of presenting a subjective judgment.
In this Note, all references to probability use the second
interpretation; we provide a formal method for developing the
implications of a set of subjective judgments about the state of the
world.  We thank James Hodges for emphasizing the importance of
distinguishing these interpretations to make our intentions and
discussion clearer.
     2The chemicals analyzed here may also affect general climatic
change, an issue that also concerns the EPA.

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 Market and
technological
   forces
Government
  policies
        Human emissions
            of PODs
              Emissions of other
             relevant trace gases,
                 some human
 Other
factors
                                      POTENTIAL
                                   STRATOSPHERIC
                                  OZONE DEPLETION
1
Effects on
human health

1
Effects on
materials

1
Effects on
crop yields

1
Other
ecological
effects
                   Fig. 2.1.—Schematic view of potential causes and effects
                             of stratospheric ozone depletion

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considering new government policies that could also affect emissions.
After release to the atmosphere, PODs and other trace gases diffuse and
react in a complex fashion that may be influenced by other factors such
as global temperatures and the amount of solar radiation.  One of the
potential results of these complex interactions is a reduction in the
concentration of stratospheric ozone.  The diffusion and chemical
reactions are simulated by computer models that produce time profiles of
estimated ozone concentrations at different altitudes and, in some
cases, latitudes.  These time profiles can in turn be transformed into
estimated time profiles of the various effects shown at the bottom of
the figure, using a variety of models.
     Each box has uncertainties associated with it.  As noted above, the
EPA plans to account for each of the identified uncertainties by
developing scenarios to represent alternative possible outcomes
corresponding to each box.  For example, it might choose three scenarios
to represent market and technological forces, eight to represent two
possibilities each for emissions of three "other" gases, four to
represent two parameterizations each of two models of the upper
atmosphere, and so on.  If these numbers of scenarios were used, the
analysis would generate 96 alternative possible time profiles for
stratospheric ozone.  Each of these cases would then be compounded with
scenarios that encapsulate information about uncertainties associated
with the effects of each time profile, to generate the full number of
cases to be analyzed for alternative policies.
     So many sources of uncertainty are important that even a simplistic
method of allowing each source to be represented by two or three
scenarios leads to an unwieldy number of cases to use in policy
analysis.  However, the structure of the problem lends itself to a
simplification that could potentially allow a much less simplistic
treatment of uncertainty.  Note that all of the information from the top
half of the figure funnels through a single time profile--that for the
extent of stratospheric ozone depletion--that is the only input required
to study the remaining sources of uncertainty.3  Thus, in theory, it is
     3This is a slight oversimplification.  Certain factors that affect
emissions in the top part of the figure may also be important to the

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                                 - 8 -
possible to develop a subjective probability distribution for the extent
of ozone depletion that summarizes all of the uncertainties in the boxes
that feed into the POTENTIAL STRATOSPHERIC OZONE DEPLETION box in Fig.
2.1 that are relevant to the analysis of the effects in the final row of
boxes.
     A probability distribution for the extent of ozone depletion could
be developed by first developing subjective probability distributions
for the uncertain quantities in each of the boxes that feed into the
POTENTIAL STRATOSPHERIC OZONE DEPLETION box and using Monte Carlo
analysis to convolute these distributions.  Actually, one would want a
set of such ozone-depletion distributions, each conditional on a
specified government policy.  These distributions would not only
summarize the extent of the known information about the factors that may
influence depletion but would also allow the assigning of probabilities
to particular ozone-depletion scenarios.  Thus, one could state that the
(subjectively assessed) probability that ozone depletion will fall
between two specified levels in a given year is x percent (conditional
on the corresponding government policy).
     The difficulty with this approach lies in representing the chemical
interactions in the atmosphere in a cost-effective way.  Current models
of the upper atmosphere are too complex and costly to use for more than
a limited number of cases.
     This difficulty does not eliminate the usefulness of using the
concept of a probability distribution for ozone depletion.  As we shall
see, it can provide a basis for developing emission scenarios used as
inputs to the atmospheric models.  Ideally, we should be able to
interpret cases easily in terms of this subjective probability
distribution.  For example, a "high" case should be developed from
scenarios for market and technological factors, other trace gases, and
other factors that together yield a "high" level of ozone depletion,
perhaps one consistent with the 75th percentile of the subjective

size of effects in the bottom half of the figure.  For example, the
level of general economic activity could affect the size of crops or
quantities of materials that might be harmed by ozone depletion.  These
kinds of dependencies can be integrated by making the distribution for
ozone depletion explicitly a function of general economic growth.

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                                 - 9 -
probability distribution for ozone depletion under current  government
policies.  Of course, we cannot accurately estimate the subjective
probability distribution without actually running the atmospheric
models, which we cannot do often enough to generate the distribution.
Nonetheless, if we must choose scenarios for the inputs to  the
atmospheric models, it makes sense to think about how to choose them in
light of what they are ultimately meant to do:   Provide the kind of
information that a subjective probability distribution for  ozone
depletion would provide if we could develop it  directly.

SCENARIOS  BASED ON A PROXY FOR STRATOSPHERIC
OZONE DEPLETION
     The scenarios developed here are intended  to approximate those  that
would be derived from a subjective probability  distribution for the
extent of ozone depletion, if one were to be developed.   We focus on
growth rates for each potential ozone depleter  so that a single random
variable—the growth rate—can describe a time  profile for  production.
We identify the main independent sources of uncertainty for the growth
rate of each chemical, designate them as "component" random variates,
and parameterize "component" distributions for  these variates.   The
available information on economic and technological factors that affect
growth in use of these chemicals is embodied in the distributions for
these component variates.   If the production growth rates of two
chemicals are related, they will both be dependent on at least  one
common component variate.
     To combine the distributions for the individual chemicals,  we
develop a "score function" that relates production growth rates of the
seven PODs to a scalar value that has some policy relevance.  Ideally,
the score function would be a monotone transformation of some relevant
measure of ozone depletion,  so that its subjective distribution could
easily be related to the distribution of ozone  depletion.   Because that
is not possible, we seek the best proxy that we can implement in a
simple way.   We derive the subjective probability distribution  for this
score function by convoluting the distributions for each of the
component variates underlying the POD production growth rates.

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                                 - 10 -
     We then define scenarios in terms of quantiles of the score
function.  For example, an "upper limit" growth scenario might use the
95th percentile of the distribution; a "high" growth scenario might use
the 75th percentile.  We then seek the quantile of the distributions for
the component random variates that, if chosen for all component variates
simultaneously, would yield the value of the score function for the
quantile used to define the scenario.  For example, using the 82nd
percentile for each component variate might yield values of growth rates
that, when placed in the score function, yield its value at the 95th
percentile of its distribution.ft  We then use the production growth
rates for each chemical that are consistent with these values of the
component variates to define the scenario in terms of the chemicals
themselves.  The resulting set of production paths for the seven
chemicals is a scenario that can be used to generate emissions inputs
for the atmospheric models.  Consider the key steps of this procedure in
turn.

Subjective Probability  Distributions for  Individual Chemicals
     Our approach begins as a standard Monte Carlo analysis would.  We
seek a set of independent probability distributions and then derive a
joint probability distribution for the seven chemicals based on these
independent distributions.  The joint distribution developed in this
Note, discussed in more detail in Sec. IV, is based on the assumption
that general economic growth is one source of uncertainty that affects
the production of all chemicals.  Otherwise, uncertainties about the
production of these chemicals are unrelated.  The approach, however,
could easily accommodate information on other interrelationships by
adding additional component variables to the analysis.
     *Note that the quantiles used for the component variates will
differ  from the quantile of the score function and will be closer to
their respective medians, unless all of the component variates are
perfectly correlated.

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                                 - 11 -
Score Function
     The score function is designed to do two things.   First, as a
practical matter, it provides a scalar value that summarizes the
information in the subjective joint probability distribution for the
individual chemicals.  This single value provides a simple way to relate
scenarios to one another.   Second, and equally important, the value is
designed to have policy significance.   Increased production of any of
the PODs will increase the value of the score function and should also
be associated with greater ozone depletion.   Hence, "high" growth
scenarios should be associated with high ozone depletion and "low"
growth scenarios with low ozone depletion.   This relationship between
the score function and the extent of ozone depletion is obviously not
perfect.  If it were, we would not need the atmospheric models.   But it
is designed to yield scenarios that can be interpreted roughly in terms
of the likely corresponding ozone depletion.5
     One way to think about the score function is as a simple tool that
policymakers can use to rank alternative sets of POD production levels.
A simple score function would be the sum of POD production in a given
year.  However, this function would be inadequate because of the widely
different effects that a unit of each POD may have on the ozone
concentration.  The score function we propose weights the production
levels of the chemicals, transforming them to a standard value so that a
unit of each is believed to have approximately the same effect on the
ozone.
     The EPA has proposed a similar approach to ozone depletion in the
past.6  Although our analysis does not use exactly the approach EPA
proposed, the use of a score function to order policy thinking about
chemicals that policymakers do not consider to be equally dangerous is
consistent with that approach.
     'Holding other factors, including the emissions of other gases,
constant.
     6See U.S.  EPA (1980).

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                                 - 12 -
     Specifically, of the many different score functions that might be
used, we use a simple weighted sum of the production growth rates for
individual chemicals.  The subjectively chosen weights are intended to
reflect the chemicals' relative potential to deplete stratospheric
ozone.  The ith chemical's weight is defined as
                       w. H (p. f. e.)/I (p. f. e.)
where
     p. = the annual global production of the chemical,

     f. = the fraction of production of the ith chemical that is likely
           to be released to the atmosphere, and
     e. = the estimated effect of an emitted kilogram of the chemical on
           stratospheric ozone relative to that of CFC-11.
None of these factors can be specified with certainty.  We estimate the
1985 production and use levels for each chemical based on the best
available data (see Hammitt et al., 1986.) The fraction of production
that will ultimately be released is based on detailed study of the
applications of each chemical (see Hammitt et al., 1986, and Palmer et
al., 1980).  The estimated relative ozone-depletion potencies are based
on  information from atmospheric models  (see Quinn et al., 1986).  These
relative potencies are sensitive to assumptions in the atmospheric
models; we use them only to suggest orders of magnitude for the weights.
     We construct two sets of weights:  one for the period 1985-2000 and
another for 2000-2040.  The weight for  each chemical is proportional to
the product of the chemical's annual production at the start of the
relevant period and a subjective factor designed to capture the other
two terms,  f. and e..  The factors for  CFC-11, -12, arid -113 are  1
because, despite their diverse uses, the majority of annual production
of  each CFC is emitted relatively promptly, and each presents about the
same potential threat to ozone per kilogram.  For carbon tetrachloride,

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                                 - 13 -
the weight is 0.064, the estimated share of production that is emitted
(most carbon tetrachloride produced is consumed in the production of
CFC-11 and -12).  Carbon tetrachloride presents about the same potential
threat per kilogram to ozone as the three CFCs.  The factor for methyl
chloroform is 0.1, since atmospheric models suggest its effect on ozone
is an order of magnitude smaller than the three CFCs.  Like the CFCs,
emissions are typically prompt.  Finally, we use a factor of 10 for both
Halons.  Their effect per kilogram on stratospheric ozone may be an
order of magnitude or more greater than that of the CFCs above.  We
choose a factor at the low end of this scale to reflect the fact that
Halons are banked for long periods of time between production and
emission, and consequently should not begin to contribute to ozone
depletion until much later, and also because a large fraction of the
banked Halon 1301 may be recovered and never emitted.
     The most important result of using this weighting scheme is that
the growth rates of chemicals produced in large volume, or likely to
have a larger depletion effect per gram, contribute more to the score
function than others.  As a result, the score function should serve as a
proxy for the potential for ozone depletion.

From  Score Function to Component Distributions
     Our approach makes ozone depletion the focus of concern, even
though it is represented only by a proxy.  Any value of the score
function could be produced by an infinite variety of production growth
rates for individual chemicals.  That problem lies at the core of using
scenarios; no one seriously expects any one scenario to occur in the
sense that all growth rates specified in the scenario persist as
expected over the life of the scenario.  Scenarios are designed to
illustrate the implications of an underlying probability distribution or
to represent some general kind of event that the probability
distribution suggests has a significant probability of occurring.   We
need a simple convention to pick the single set of time profiles that
make up a scenario.
     We seek scenarios that illustrate the different time profiles of
ozone depletion that production of the seven PODs might induce.
Otherwise, we are indifferent about the specific time profiles chosen

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                                 - 14 -
for individual chemicals.  It seems reasonable to seek a convention that
treats sources of uncertainty equally to avoid any manipulation of the
approach aimed at emphasizing one chemical over another.  Accordingly,
we choose as a convention to use the same quantiles for each of the
independent component distributions.  Other conventions could be chosen,
just as scenarios with similar policy implications can be defined in
different ways.
     The subjective probability distribution for ozone depletion stands
at the heart of EPA policy analysis.  If that distribution could be
approached directly, that would be the best path to follow.  This
section presents an alternative approach to take when the best
alternative appears too  costly.  Our approach still focuses on the
central point of interest—ozone depletion.  It seeks a method to
generate scenarios that  are  likely to capture and  illustrate the range
of ways in which economic and technological factors relevant to the
seven PODs could affect  stratospheric ozone depletion.
     The approach suggested  in this section is conceptual  in nature;  it
could be implemented in  many different ways.  Section III  explains the
specific method we have  developed to implement this concept.

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                                 - 15 -
         III.  THE  DISTRIBUTION OF THE SCORE FUNCTION
     To implement our approach, we need explicit subjective probability
distributions for production growth rates and for the score function.
In this section we develop a formulation that allows us to use a closed
analytic solution to convolute the distributions for the individual PODs
and to derive the distribution of the score function.  The subjective
probability distributions for the individual chemicals are described in
Sec. IV.
     Our method approximates the distribution for the score function
that would be developed if all the component variates that describe the
growth rates of individual PODs were distributed normally.l  Normal
distributions appear reasonable in all but a few instances, and these
can be accommodated without serious difficulty.   Our approximation would
be exact if the relative production shares of each chemical remained
constant over time.  These shares change in our analysis but not enough
to seriously threaten the integrity of the general results.
     The general conceptual approach outlined in Sec. II would allow a
more general implementation based on standard Monte Carlo techniques
that would require neither an assumption of approximate normality nor
the kinds of approximations used here.  Whether this approach would
justify the additional costs is unclear, since a Monte Carlo analysis
requires approximations when continuous distributions are approximated
by discrete ones.
     The approach presented in this section allows quick, low-cost
development of scenarios without sacrificing much accuracy.  We discuss
in turn the role of linear approximations in aggregating chemical use
and the closed analytic solution we use to choose chemical growth rates
that are consistent with any scenario chosen using the score function.
     Equivalently, we assume that the future quantities of PODs are
distributed approximately log-normally.   The correspondence between a
normally distributed growth rate and a log-normally distributed future
production level is good for modest growth rates.   Let Y  = Y  (1 + r)t
where Y. is production in year i and r is the growth rate.  Then log Y
= log YQ + t log (1 + r) = log YQ + t r for small  r.

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                                 - 16 -
AGGREGATING  CHEMICAL USE
     The growth rate for the production of each chemical is
characterized as the sum of the growth rates of general economic
activity (GNP) and of the specific intensity of use of each chemical,
defined as the level of use relative to the GNP.2  We focus on the
average annual growth rates of GNP and intensity for each chemical.  Our
subjective probability distributions for the growth rates of these
components are normal distributions.  Because the score function is a
linear combination of the component variables, our uncertainty about its
value is also described by a normal distribution.  The parameters of the
distribution of the score function's value can be expressed as simple
functions of the parameters of the distributions of the component
variables.
     We have subjective distributions for use of the seven PODs before
2000 for different world regions and, for CFC-11 and CFC-12, for product
applications.  We must aggregate these distributions to derive the
distributions for world use of each chemical and similarly aggregate
across chemicals to derive the distribution for the score function.  We
rely on linear approximations in making these aggregations.
     First consider the aggregation of growth rates for different uses
 of a chemical or for total use of a hemical in different world regions.
For example, we have developed subjective probability distributions for
CFC-12 use in aerosols, foam blowing, refrigeration, air conditioning,
and other applications (Hammitt et al., 1986).  Let x. be the amount of
CFC-12 used  in the ith application.  Then the total amount of CFC-12, x,
is simply I  x. and the rate of change in x can be related to the rate of
change of the {x.} at any instant in time in the following way:

        (l/x)(dx/dt) = I  [(xi/x)(l/xi)(dxi/dt)]                      (3.1)
      2This  is an approximation, but one that works well for small growth
 rates.  The exact relationship is  (1 + r) = (1 + g)(l + i) = 1 + g +
u, + 8uir> where r,  is the growth rate for the kth chemical, g is the
growth  rate  for GNP, and u,  is the growth rate for the intensity of use
of the  kth chemical relative to GNP.  For small g and u  , gu,  = 0 and r,
= g + u, .  This standard approximation  is often used in  economics.

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                                 - 17 -
If we define r as the growth rate of CFC-12, r. as the growth rate of
the ith application of CFC-12, and a. as the share of CFC-12 used in the
ith application (a. = x./l x.), Eq. (3.1) can be reexpressed as

        r = I (a± r..)                                               (3.2)
Given our small growth rates, r. - g + u.,3 where g is the percentage
growth rate for GNP and u. is the growth rate for the intensity of use
of the ith application relative to GNP.  Hence, Eq. (3.2) can be
rewritten as
        r = g + Z (a± u±).                                          (3.3)
     The derivation of Eq. (3.3) incorporates two linear approximations.
First, it assumes that the growth rates of two factors affecting a
variable can simply be summed to calculate the growth rate of the
variable itself.  Given the small growth rates we are considering, this
is adequate.  Second, although Eq.  (3.2) i& exact at any instant, it is
not exact over a discrete period of time unless all u. are equal and
hence all a. remain constant over the period.  Since we use the {a.}
corresponding to the beginning of the period, we are essentially using a
Laspeyres index to approximate aggregated growth rates; this index is
adequate so long as the {a.} do not shift too much over the period of
interest.*
     Similarly, to aggregate use across world regions we use a linear
formula to approximate the global growth rate.  If r. is the rate of
     3See footnote 2 above.
     ''Alternatives would include using the weights corresponding to the
end of the period (a Paasche index) or an intermediate set of weights.
As long as the correct weights do not shift much over the period, any of
these choices will produce similar results.  This is a specific example
of the general problem of defining index numbers.  For further
discussion, see Hirshleifer (1976) or other economics texts.

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                                 - 18 -
growth in the jth region and b.  is the share of global use there,  the
global growth rate
                j r.).                                              (3.4)
The {b } are fairly stable as long as uses in different regions  do  not
grow at markedly different rates.
     The second place where linear aggregation is  important  is  in the
definition of the score function.   We define the score function  as

      s = Z (wk rk)
        = 8 + z (wk V                                             (3-5)
              k

where wk is the subjective weight for the kth POD,  described in Sec.  II,
and u,  is the growth rate for the intensity of use  of the kth POD.

DERIVING  SCENARIOS FOR INDIVIDUAL CHEMICALS  FROM
THE SCORE  FUNCTION
     If g and u,  in Eq. (3.5) are normally distributed,  then s is
normally distributed as well.  This observation is  the key not only  to
convoluting uncertainties in the components into a  distribution for  the
score function but also to moving in the opposite direction.   Once a
scenario is defined in terms of a quantile of the distribution for s, we
can use the normality of the score function and its components to find
the common quantile for the component distributions that is consistent
with this scenario.
     Start by noting that the mean (m )  and variance (v  ) of s can be
                                     s                s
defined in terms of the means (m, ), variances (v, ), and  covariances
(v , ) of its components:
  JtK.

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                                 - 19 -
                m  = ra  + I (w. m. )
                 s    g       k k'

                          k
        vs=vg+I (wk2vk) + 2 I (wkwt vk£)                       (3.6)
The value of the score function at the q th quantile of its distribution


is





        s(q ) = m  + v '5 z(q )                                      (3.7)
           o     o    o      o




where z(q ) is the value of the z-statistic corresponding to the q th
         s                                                        s

quantile of the standard normal distribution.  Analogously, the q th


quantiles of the growth rates of GNP and the intensity of use of the ith


chemical can be defined as:





        g(q )  = m  + v '  z(q )
           c      g    g      <~

and                                                                  (3.8)


        u.(q ) =m. + v. '  z(q ).
         i Mc     i    i      c




We would like to find the value z(q ), and thus implicitly the quantile
                                   O

q , so that if we fix g and all the u,  at their q th quantiles, s will
 O                                   ix           C

take the value at its q th quantile.  To do this, for a given value of


s, substitute Eq. (3.8) into Eq. (3.5) and Eq. (3.6) into Eq. (3.7) and


set Eq. (3.5) equal to Eq. (3.7).  Rearranging yields





        z(qc) [vg'5 + z (Wi v..-5)]
        = z(qs) [vg + Z (w..2 Vi) + 2 I (wk W|l vk£)]'5                (3.9)


                      i             k>d
or

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                                   20 -
        z(q ) = z(q ) / 3                                           (3.10)
           c       s
where
        3 =
                     v    + I (w .  v . "  )
                      g         11
             [Vg + l (W1  Vi} + 2 l (wk
                                 k>£
     Equation (3.10) allows one easily to transform quantiles of the
distribution of the score function into the corresponding quantiles of
the distributions underlying the POD growth rates.   Each scenario is
based on a value of q ,  which yields z(q ), which in Eq. (3.10) yields
                     3                  S
z(q ).s  We know that 3  > 1 so that the quantiles for the component
distributions are closer to their medians than the corresponding
quantiles for the distribution of the score function.6  That is, the
quantiles of the component variates that correspond to a specified
subjective probability interval for the score function will span an
interval associated with a lower level of subjective probability for the
component variates.  As  shown in Table 5.2 below, the quantiles of the
component distributions  corresponding to the 90 percent subjective
probability interval for the score function approximately span a 62
percent subjective probability interval for each component variate.
      Note that we need not determine q  to calculate the growth rates
relevant to any scenario.   Once z(q ) is calculated from Eq.  (3.10), it
can be substituted into Eq. (3.8) and the appropriate values  of the
component growth rates can be calculated.
     6To see this, square the expression that defines 3 in Eq.  (3.10)
and subtract the denominator from the numerator.   This yields an
expression
     2 I [w^'V'5] + 2 I [wiW. ((vvv.)'5 - v  )] -
The first term must be positive.   To sign the second, note that the
subjective analog of the Pearson correlation coefficient, v../(v.v.)'
cannot exceed unity.  Hence, the second term is also positive.
Therefore the numerator must exceed the denominator and 3 must exceed
one .

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                                 - 21 -
     Adopting normal distributions for the component growth rates and
using linear approximations to convolute uncertainties and thereby
construct distributions for aggregations of the component random
variat.es considerably simplifies our analysis.   The scenarios generated
will reflect the influence of the approximations used.  The alternative
is to use a simulation technique like Monte Carlo, which itself normally
requires that we approximate the underlying distributions.  Given the
likely sources of error associated with the method presented here, we
believe it provides a good, quick, and low-cost method for developing
scenarios that reflect the jointness of the underlying subjective
probability distribution for production levels  of the chemicals of
interest to policymakers.

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                                  22  -
     IV.  SUBJECTIVE MARGINAL  PROBABILITY DISTRIBUTIONS
                 FOR  POTENTIAL OZONE DEPLETERS
     To construct scenarios  from  our subjective probability distribution
for the production growth rates for the  seven chemicals we are studying,
we must choose subjectively  based parameter values with which to
characterize it.   This section explains  how we choose these parameter
values for the period 1985 to 2040. l   It begins with a brief explanation
of the methodology used to develop the distribution based on information
reported in other Rand documents.   It  then summarizes our analysis of
the period 1985-2000.  Because Hammitt et al.  (1986) document our choice
of parameter values for this portion of  our analysis, we simply outline
the approach used and summarize the results.  Finally, the section
explains how parameters were developed for the period 2000-2040.

METHODOLOGY
     The ultimate object of  interest  in  developing the subjective
probability distribution is  how the production of seven chemicals grows
over time.  To examine this, we  focus  on production growth rates.  How
exactly should we represent  correlations among growth rates over time
for each chemical?  And how  exactly should we  express relationships
among growth rates for different  chemicals  in  any year?  Specifying
these relationships completely would  entail  a  density of detail not
warranted by the extent of our  knowledge about the  relationships.  We
seek a simplified specification  of the relationships  that  captures their
most important features.
      *It  is obviously difficult to think about events this far in the
 future.   We look ahead this far to accommodate the needs of atmospheric
 modelers.  Because the chemicals we are studying can remain in the
 atmosphere for  decades following their emission, atmospheric models rely
 on long  time  series of emissions as inputs.  We try to reflect the
 degree of our uncertainty about the far future in our choice of
 parameter values.

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                                 - 23 -
Relationships Across Time
     Because our primary concern is with cumulative POD production, we
focus on average annual growth rates over long periods of time.
Specifically, to choose normal distributions to represent uncertainty
about growth rates, we must choose means and variances for our
distributions for the secular growth rate for each chemical and
covariances among growth rates for different chemicals in each period.
Because of our focus on long-term average rates we need not address year-
to-year variations associated with the business cycle or temporary
market conditions.  It is reasonable to ignore these events because
their influence on the variance of the average growth rate falls as the
length of the period grows and should be quite modest over the 15-year
and longer periods we consider.
     We break the total period from 1985 to 2040 into two subperiods and
examine the means and covariance structure of secular growth within
each.  Parameter values for the period 1985-2000 are based on analysis
in Hammitt et al. (1986), whose results reflect subjective judgments
about the range of reasonable growth rates for chemicals in different
applications.  These judgments are based on a detailed analysis of
market trends and potential changes in markets, technologies, and
regulations that could affect the use of these chemicals.  Parameter
values for the period 2000-2040 are based on concepts developed in Quinn
et al. (1986).  That document looks at historical trends in the
relationship between chemical use and income and uses these to project a
range of use levels over the period in question.  The analysis is
necessarily less detailed than that in Hammitt et al. (1986).  We draw
on results from Hammitt et al. in the later period to assure that our
assumptions in the two periods are mutually consistent.
     Although the structure of growth rates within each period may be
conceived as a set of means and a covariance matrix for each period, the
relationship between the periods is more difficult to represent
parametrically.   We choose a relationship that carries over the implicit
assumption of a positive correlation between yearly growth rates across
time within the two periods.2  To construct a high growth scenario for
      Heuristically, we can think of a growth rate as having two

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                                 - 24 -
the full period, we use high growth scenarios in each period.
Similarly, low growth scenarios use low growth rates in both periods.

Relationships  between Chemicals
     We treat the average annual growth rate as the sum of two terms:
(1) general economic growth and (2) growth of intensity of use relative
to GNP, which includes both growth in the product markets where the
chemical is used (relative to GNP) and growth in the use of the chemical
in the manufacture of the products.  We assume that sources of
uncertainty in the intensity of use of each chemical are uncorrelated
between chemicals, both within and across periods.  With a better
empirical understanding of the chemicals markets, it should be possible
to identify relationships of this kind in the future.  For now, however,
we assume them away.
     The general economic growth component is common to all of the
chemicals and consequently creates a positive covariance among the
growth rates for all of the chemicals.  Before 2000, we divide the world
into regions and specify general economic growth and chemical intensity
distributions for each; after 2000, we treat the world as a single unit.
When dealing with more than one region, we assume that growth rates in
different regions are positively correlated with one another.  The next
subsection discusses this in more detail.
     In sum, our method characterizes a wide variety of factors relevant
to uncertainty about the future use of these chemicals.  It reflects
interrelationships across time and across chemicals.  A more complicated
framework for relating growth rates could potentially capture subtleties
not represented here.  However, empirical data of the type and quality
necessary even to quantify all of the details of this system in a
historical period are not currently available.  Until better data are
available, a more detailed structure  is difficult to justify.

components.  The  first is a secular component that  can be  represented by
a  single  random variate for each  chemical.   The second is  an annual
component that  requires separate  random variates  for each  year.  These
can be  independent of one another over time  (though not necessarily
across  chemicals).  The first component embodies  the positive
correlation we wish to capture  in our choice of  a method  to  relate the
two periods.  The second is an  additional source  of uncertainty that
helps  explain why the variance  of  a mean growth  rate can  decrease  for
longer  periods.

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SUBJECTIVE  PROBABILITY DISTRIBUTION FOR THE
PRE-2000 PERIOD
     The subjective probability distribution for the period before 2000
is taken from Hammitt et al. (1986).  That source develops explicit 80
percent subjective probability intervals for the use and production of
the seven PODs through the end of the century.   It divides world use
into use in three major regions, and projects future use of CFC-11 and
-12 in each of the major products in which they are used.   The mean
rates of growth are based on analysis of trends and industry forecasts
for each application or chemical.  Although the reported mean rates are
not constant over the period for some of the uses, we have calculated
average annual rates over the period for use here.
     We aggregate our distributions for growth  rates across applications
of a single chemical, and across chemical use in different regions, to
obtain our distributions for world GNP and chemical intensity growth
using the methods described in Sec.  III.  When  aggregating distributions
across regions, we use a positive correlation (a coefficient of 0.75)
across regions for both GNP and chemical intensity growth  rates.   The
parameters of the resulting distributions are reported in  Table 4.1.
     The table displays the parameters of the growth rate  distributions
in two forms.   The columns labeled "intensity"  include the mean and
standard deviation of our distributions for the rate of growth of
intensity of use of each chemical,  relative to  general economic growth.
The last row of the table shows the mean and standard deviation of our
distribution for the general economic growth rate itself in these
columns.  The columns labeled "Production" report the mean and standard
deviation of our distributions  for growth rates for production of each
chemical,  including the effects of both general economic growth and
intensity of chemical use.   The mean of our distribution for the
production growth rate is the sum of the means  of our distributions for
general economic growth and intensity of use.   The standard deviation of
the distribution for the production growth rate is the square root of
the sum of variances for general economic growth and intensity of use.

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                                 -  26 -
                               Table 4.1
             PARAMETERS OF THE SUBJECTIVE JOINT PROBABILITY
                  DISTRIBUTION IN THE PRE-2000 PERIOD
          (Use in thousands of metric tons,  rates in "„ per year)
Intensity

Chemical
CFC-11
CFC-12
Carbon tetrachloride
CFC-113
Methyl chloroform
Halon 1301
Halon 1211
Gross global product
1985
Use
341.5
443.7
1029.0
163.2
544.6
10.8
10.8


Mean
0.02
-1.00
-0.49
3.27
-0.32
1.08
0.96
3.28
Standard
Deviation
0.98
1.05
1.02
1.67
1.10
2.29
2.33
1.15
Production

Standard
Mean Deviation [a]
3.30
2.28
2.79
6.55
2.96
4.36
4.24

1.51
1.56
1.54
1.03
1.59
2.56
2.60

   [a]  The covariance among the chemical production growth rates is the
variance of gross global product or 1.32.
     As shown by Table 4.1, we expect use of CFC-113 and the Halons to
grow more rapidly during the remainder of the century than do the other
chemicals.  This reflects a typical pattern of chemical use, in that
relatively recently marketed "specialty" chemicals that are produced in
limited quantities grow rapidly as they are adopted in applications to
which they are well suited.  Older chemicals, that are produced in
larger quantities, may not grow as quickly because they have already
been adopted in the applications for which they are best suited.  The
covariance among the production growth rates is equal to the variance of
general global economic growth because the intensities are uncorrelated
with one another and with general economic growth.3
     3The total growth rate for the ith chemical, r., equals g + u.,
where g is the general growth rate and u. is the growth of intensity of
use of the ith chemical relative to general economic growth.  Hence,
cov(r.,r.) = cov(g + u^g + u.) = var(g) + covCg.up + cov(g,u ) +
cov(u.,u.) = var(g), since all the covariances in the last step are
equal to zero.

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SUBJECTIVE PROBABILITY  DISTRIBUTION FOR THE
POST-2000  PERIOD
     The subjective probability distribution for the post-2000 period is
derived from  information from a number of sources.  We chose parameter
values that  reflect the rate of general economic growth based on data
from William  Nordhaus and Gary Yohe.h   We chose parameter values to
reflect the  rate of growth of chemicals relative to general economic
growth based  on concepts developed in Quinn et al. (1986) and the
parameter values chosen for the pre-2000 period.  Information from the
pre-2000 period is used to assure internal consistency in the
distribution.  This subsection first  considers how information from
these sources was used and then reports the resulting distribution for
the post-2000 period.

Development of the Subjective Probability Distribution
     During the post-2000 period, it  is much more difficult to rely on
detailed analyses of individual  chemical applications and markets than
it is in the pre-2000 period.  Our basic level of uncertainty about
events in this period makes it difficult to imagine the range of events
that might occur.  Quinn et al.  (1986), for example,  present the best
available analysis of the kinds  of events that might  be important to the
markets for PODs after the turn  of the century.   But  even this analysis
generally shows less variation in growth rates after  2000 than before.
In particular, it allows for no  variation in the rate of general
economic growth.  As a result, we build on the basic  concepts developed
in Quinn et al.  (1986), but seek a more realistically broad range of
uncertainty for the growth of production during this  period.
     Consider first the parameter values of the distribution for the
global economic growth rate.   We develop parameters for this
distribution based on distributions Nordhaus and Yohe have developed on
the projected rates of population and labor productivity growth.   We
start with a weighted average of their parameters for these
distributions over the periods 2000-2025 and 2025-2050.   We posit a
     ""Personal communication with Gary Yohe,  Wesleyan University,
Middletown, Connecticut,  8 January 1986.

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                                 - 28 -
correlation coefficient of -0.2 between population growth and growth in
labor productivity over the period 2000-2040.5   From these,  we calculate
parameters for use in our analysis.   Since the  GNP growth rate is
approximately the sum of the population and labor productivity growth
rates,6 our mean GNP growth rate is the sum of  the means that Nordhaus
and Yohe use for population and labor productivity, and our variance is
the sum of the variances that they use for population and labor
productivity, less a small quantity to take account of the negative
correlation between them.7
     Now consider parameter values of the distributions for growth rates
of intensity of use relative to general economic growth.  The most
important concept in Quinn et al. (1986) is that the rate of growth in
the production of PODs will tend toward the rate of general economic
growth over the long run.  Quinn et al. use gross national product (GNP)
per capita as a measure of general economic income.  We believe a more
appropriate measure is GNP itself, since this captures growth in the
income of individuals and in the population as a whole.8  Hence, we
assume that on average intensity of use will not change over the long
run.
     5Global labor productivity and population are likely to be
inversely correlated over this period because population increases are
likely to be in the poorer nations that suffer from shortages of human
and physical capital.  Using an input-output model of the world economy,
Leontief  (1979) simulates how variations in population are  likely to be
inversely correlated with per capita GNP.  His results are  consistent
with the use of a correlation coefficient of -0.2.
     6See footnote 2 in Sec. III.
     7The adjustment term is (-0.2)(2)(standard deviation for population
growth rate)(standard deviation for growth rate of labor productivity).
This term is small enough so that the choice of a correlation
coefficient  does not change our results much.
     8 It has been suggested that a  rate of growth between that of GNP
per capita and GNP itself might be  most appropriate.  That  is because,
as indicated above,  it  is likely that population and GNP per capita are
negatively correlated.  We recognize that by reflecting this negative
correlation  in our distribution for GNP itself.  Once that  relationship
is accounted for, GNP  is a more useful measure of income than GNP per
capita.

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     For most chemicals, that implies a mean of zero for the rate of
growth of intensity.  The Halons are treated slightly differently.  For
Halon 1301,  we expect recycle and recovery to become important after
2000, creating a source of Halon 1301 that can compete with new
production.   As a result, even if the annual demand for new Halon 1301
grows at the rate of growth of the GNP, production will grow more
slowly.   This implies a negative growth rate of intensity of use.  For
Halon 1201,  we expect penetration of the fire extinguishant market to
slow beyond 2000, leading to a slightly negative growth rate for
intensity of use.
     Appropriate variances are harder to choose for these distributions
because the range of uncertainty is difficult to conceptualize in
markets for individual chemicals this far into the future.  We start
with the ranges suggested in Quinn et al. (1986).   This document
develops ranges of growth rates for CFC-11 and -12 and, to a lesser
extent, CFC-113.  We then compare these ranges with the ranges for these
chemicals developed in Quinn et al. and Hammitt et al. (1986) to the pre-
2000 period, a period we understand much better.
     Our comparison of the range of growth rates in the two periods is
based on a second important concept developed in Quinn et al.
Uncertainty in either period reflects the joint probabilities of many
individual events over time.  In a short time period, the number of
events relevant to our analysis--changes in regulation, technology,
product line, and so on--is small, leading to a possibility that any one
of these could lead to very large changes relative to the mean rate of
growth.  Over a longer period of time, these events tend to have
offsetting effects, suggesting that a reasonable range of average annual
growth rates in intensity of use should fall over time if the range of
events likely in any fixed length of time remains constant.  This is
simply a reflection of the fact that the variance of a mean of a set of
independent, identically distributed random variables falls as the
number of variables rises.  Because the pre-2000 period is so much
shorter than the post-2000 period, we must adjust variances in the two
periods before comparing them.

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                                 - 30 -
     We can use this view of the uncertainties underlying our
distributions for intensity growth rates to choose the variance of
growth rates in the post-2000 period based on those in the pre-2000
period.  To do so, calculate the variance for the pre-2000 period by
squaring the chosen standard deviation for each chemical.  Multiply this
by 15/40 = 0.375 to find the equivalent variance for the longer post-
2000 period.9  Adjust this variance up by a factor to reflect our belief
that uncertainty is higher in the post-2000 period.  Choosing this
factor is inherently arbitrary; after a review of the analysis of likely
trends in the post-2000 period in Quinn et al. (1986) and other
available sources, we choose a factor of 1.25.  Use this new variance as
a basis for the standard deviation of the post-2000 distribution for the
rate of growth of intensity of use relative to general economic growth.
The standard deviations reported in Table 4.2 are based on this
calculation.

Parameters  of the Joint Distribution
     Table 4.2 presents the parameter values of the subjective
probability distribution for growth rates in the post-2000 period.  Note
that the means of our subjective probability distribution for growth
rates are generally lower than for the period before 2000, and the
standard deviations are also smaller, as discussed above.  The means of
our subjective probability distribution for the growth rates for all of
the PODs except the Halons are equal.  Growth rates for the Halons are
lower because we expect growth to slow as the likely new applications
     9The variance of a mean of n independently and identically
distributed random variables with variance v is v/n.  Hence, the ratio
of variances for means based on two groups of these variables with group
sizes n  and n  is n /n .  We are not suggesting that events in
individual years are independent of one another.  But events in a time
period as long as five years probably are more or less independent of
events in the next five-year period.  The proportionality of the two
periods is the same whether we consider events within each period
associated with one-year or five-year subperiods.  We emphasize here
that we are dealing with subjective distributions.  We use statistical
concepts most commonly associated with a frequency view of statistics to
formalize our view of the sources of uncertainty underlying our
distributions for the two periods.

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                                 - 31  -
                              Table 4.2
             PARAMETERS OF THE SUBJECTIVE JOINT PROBABILITY
                  DISTRIBUTION IN THE POST-2000 PERIOD
                             (In °0 per year)
Intensity

Chemical
CFC-11
CFC-12
Carbon tetrachloride
CFC-113
Methyl chloroform
Halon 1301
Halon 1211
Gross global product

Mean
0
0
0
0
0
-0.45
-0.05
2.4
Standard
Deviation
0.67
0.72
0.70
1.15
0.75
1.57
1.60
0.96
Production

Mean
2.4
2.4
2.4
2.4
2.4
1.95
2.35

Standard
Deviation[a]
1.17
1.20
1.19
1.50
1.22
1.84
1.87

         [a]   The covariance among the  chemical production growth rates
       is the variance of gross  global  product or  0.92.
for these chemicals are exhausted.   The growth  is  slowest  for Halon  1301
where recovery and reuse of the chemical should significantly affect the
need for new production as its  likely markets are  penetrated.  Standard
deviations are also similar for all of the  PODs but  CFC-113 and the
Halons.  Regulatory uncertainty will remain high for CFC-113.  We are
significantly less certain in general about the future  of  the Halons
than about the future of the other  chemicals.

MARGINAL DISTRIBUTIONS FOR INDIVIDUAL CHEMICAL PRODUCTION
     Table 4.3 presents some illustrative quantiles  of  the marginal
distributions for production of individual  chemicals in 2000, 2020,  and
2040, together with estimated current world use.   These results suggest
that a wide range of outcomes are possible  as we move into the future.
To understand the full implications of the  subjective probability
distribution described here, we must view outcomes for  chemicals
jointly.  The joint results are presented in Sec.  V.

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                               - 32 -
                             Table 4.3

PRODUCTION LEVELS AT SPECIFIED QUANTILES OF THE SUBJECTIVE MARGINAL
         PROBABILITY DISTRIBUTIONS FOR INDIVIDUAL CHEMICALS

                    (In thousands of metric tons)
Chemical/
Year
CFC-11
1985
2000
2040
CFC-12
1985
2000
2040
Carbon
tetrachloride
1985
2000
2040
CFC-113
1985
2000
2040
Methyl
chloroform
1985
2000
2040
Halon 1301
1985
2000
2040
Halon 1211
1985
2000
2040

0.05

342
386
466

444
425
504


1029
1070
1280

163
262
256


545
574
672

11
11
7

11
11
8

0.25

342
479
907

444
532
1001


1029
1335
2519

163
348
605


545
721
1349

11
16
21

11
16
25
Quant ile
0.50

342
556
1435

444
622
1606


1029
1554
4014

163
422
1091


545
844
2179

11
20
44

11
20
53

0.75

342
644
2263

444
725
2565


1029
1807
6371

163
512
1956


545
986
3506

11
26
92

11
26
111

0.95

342
794
4326

444
901
4994


1029
2237
12290

163
671
4476


545
1229
6893

11
37
259

11
37
315

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                                 - 33 -
         V.   PRODUCTION  SCENARIOS BASED ON QUANTILES
                      OF  THE  SCORE FUNCTION
     Applying the methods described in Sec.  Ill  to  the  subjective
probability distribution defined in Sec.  IV  yields  scenarios  that we can
use to project alternative futures for the seven PODs analyzed here.
This section explains how the final calculations are made  and presents a
set of production scenarios based on our  technique.

CHOOSING  THE QUANTILES TO  USE FOR SCENARIO DEVELOPMENT
     A production scenario is based on a  particular quantile  of the
distribution of the score function defined in  Sec.  III.  We use the 5th,
25th, 50th, 75th,  and 95th percentiles as a  basis for scenarios that
represent, respectively, lower limit,  low, middle,  high, and  upper limit
cases relevant to policy decisions.   Other scenarios could obviously be
developed without difficulty using the techniques described here.  These
five appear to describe the relevant policy  space in a way that
facilitates analysis.
     Viewed in the context of EPA's policy analysis, the middle three
scenarios—representing low, middle, and  high  growth--should  be the most
useful.  The middle case represents a scenario defined such that the
effect of these seven PODs on ozone depletion  is equally likely to be
greater or smaller than the effect corresponding to this scenario.
Analogously, the low and high growth scenarios are  defined such that the
probabilities of greater or lesser effects as  a  result of  these
chemicals, conditional on the effect being greater  or smaller than the
median case, are equal.   Thus,  these three scenarios encapsulate
information on regions of the distribution for ozone depletion that
reflect the likely range of outcomes for  these seven chemicals.  The
limiting scenarios at the 5th and 95th percentiles  are better used to
think about the outer bounds of reasonable results  than to convolute
with other sources of uncertainty in EPA's planned  generation of many
cases.

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                                 - 34 -
     We start the development of scenarios with chemical weights for the
score function that reflect relative production levels in 1985.   Table
5.1 presents these weights.  These weights, together with the values of
the standard deviations from Sec.  IV and Eq.  (3.8) from Sec.  Ill, allow
us to calculate the value 3 with which to transform z-statistics from
the distribution for the score function into z-statistics for the
component economic-growth and intensity distributions.  These identify
intensity and general economic growth rates that can be used to
calculate a growth rate for each chemical for each scenario during the
pre-2000 period.  These growth rates, applied to actual production
levels in 1985, allow us to calculate the production paths relevant to
each chemical for each scenario up to 2000.
     The calculations for the post-2000 period are analogous.  We use
different weights and consequently a different value of (5, based on 2000
production levels for the 50th percentile growth scenario.  These are
also reported in Table 5.1.

                               Table 5.1
                            CHEMICAL WEIGHTS
Chemical
CFC-11
CFC-12
Carbon tetrachloride
CFC-113
Methyl chloroform
Halon 1301
Halon 1211
1985
0.265
0.344
0.051
0.126
0.043
0.085
0.085
2000
0.255
0.285
0.045
0.193
0.038
0.092
0.092
Difference
-0.010
-0.059
-0.006
0.067
-0.005
0.007
0.007
        NOTE:  The concepts underlying these weights are explained in
   Sees. II and III.  They reflect the production level, share of
   production that is emitted, and potential ozone-depletion risk
   per gram in the atmosphere of each chemical.  Of these factors,
   we assume that only production levels differ between the periods
   before and after 2000.

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                                  -  35  -
     Median growth  rates differ enough across chemicals during the pre-
2000 period to  lead to significant shifts in the chemical weights
between  1985 and 2000.  This means that our weighting system is only
approximate over this period; it effectively represents the use of a
Laspeyres index, with its potential problems.  Median growth rates after
2000 are equal  for  all chemicals but the Halons.  Although we use a
constant set of weights over a significantly longer period of time after
2000, the actual weights do not shift as much over this period as they
do from  1985 to 2000.*
     Applying these weights in Eq. (3.8) yields g values of 1.93 before
2000 and 1.83 afterward.  These yield the z-statistics for individual
scenarios shown in  Table 5.2.  The results in this table make it clear
how important it is to view chemicals jointly rather than individually.
To construct scenarios for the 5th percentile of the score function, we
must use z-statistics for component distributions that are consistent
with the 18th to 20th percentiles of these distributions.  A 25th
percentile scenario uses z-statistics consistent with the 36th
percentile of the component distributions.   Similar adjustments apply
for higher percentile scenarios.  Viewing these seven chemicals together
significantly narrows the range of growth rates represented in the
scenarios before and after 2000; the effect is slightly smaller after
2000.

CHEMICAL USE SCENARIOS
     Taken together with the parameter values from Sec.  IV,  the
z-statistics in Table 5.2 yield the growth rates in Table 5.3 as the
bases for production scenarios.   Table 5.4 shows the production levels
that result from these growth rates for 1985, 2000, 2020, and 2040.
Numbers like these calculated for the intervening years  provide the
basis for calculating emission scenarios,  which in turn  can provide
inputs to the type of policy analysis EPA is currently pursuing.   Moving
          largest difference is about 0.013, for Halon 1301.   Weights
corresponding to the median growth scenario in 2040 are CFC-11, 0.257;
CFC-12, 0.288; carbon tetrachloride, 0.046; CFC-113, 0.196;  methyl
chloroform, 0.039; Halon 1301,  0.079; and Halon 1211, 0.095.

-------
                                 -  36  -
                               Table  5.2

              Z-STATISTICS  AND  &  VALUES FOR  DISTRIBUTIONS
                  OF  THE SCORE  FUNCTION AND  COMPONENTS
Quantile
of the
Score
Function
0.05
0.25
0.50
0.75
0.95
& value


Score
Function
-1.645
-0.675
0
0.675
1.645

z-Statistics

Pre-2000
Components
-.854
-.351
0
.351
.854
1.93


Post-2000
Components
-.899
-.369
0
.369
.899
1.83
beyond these productions scenarios,  however,  takes us beyond the scope

of this Note.2
     2For information on how to transform production scenarios into
emission scenarios, see Palmer et al.  (1980).

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                     - 37 -







                   Table 5.3




GROWTH RATES FOR SCENARIOS BEFORE AND AFTER 2000




                 (In °0 per year)
Scenarios /Quant lies
Chemical
CFG- 11
CFC-12
Carbon
tetrachloride
CFC-113
Methyl
chloroform
Halon 1301
Halon 1211
Period
Pre-2000
Post-2000
Pre-2000
Post-2000
Pre-2000
Post-2000
Pre-2000
Post-2000
Pre-2000
Post-2000
Pre-2000
Post-2000
Pre-2000
Post-2000
0.
1.
0.
0.
0.
4.
0.
1.
0.
0.
0.
1.
-0.
1.
-0.
05
47
93
39
89
15
51
03
86
93
91
12
20
12
19
0
2
1
1
1
5
1
2
1
2
1
2
-1
2
1
.25
.54
.80
.50
.78
.56
.63
.17
.77
.03
.79
.94
.07
.94
.51
0
3
2
2
2
6
2
2
2
2
2
4
2
4
2
of the Score Function
.50
.29
.40
.27
.40
.55
.40
.96
.40
.79
.40
.07
.00
.07
.47
0.
4.
3.
3.
3.
7.
3.
3.
3.
3.
3.
5.
2.
5.
3.
75
03
00
04
02
54
18
74
03
55
01
34
92
34
39
0
5
3
4
3
8
4
4
3
4
3
7
4
7
4
.95
.12
.86
.15
.91
.97
.29
.88
.94
.64
.89
.15
.22
.15
.72

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                 - 38 -
               Table 5.4

SELECTED PRODUCTION LEVELS FOR SCENARIOS
BASED ON QUANTILES OF THE SCORE FUNCTION

       (In thousands of metric tons)
Chemical/
Year
CFC-11
1985
2000
2040
CFC-12
1985
2000
2040
Carbon
tetrachloride
1985
2000
2040
CFC-113
1985
2000
2040
Methyl
chloroform
1985
2000
2040
Halon 1301
1985
2000
2040
Halon 1211
1985
2000
2040

0.05

342
426
617

444
471
671


1029
1183
1701

163
300
367


545
636
897

11
13
12

11
13
14

0.25

342
498
1017

444
555
1124


1029
1391
2827

163
367
700


545
752
1517

11
17
26

11
17
31
Quant ile
0.50

342
556
1435

444
622
1606


1029
1554
4014

163
422
1091


545
844
2179

11
20
44

11
20
53

0.75

342
619
2022

444
696
2287


1029
1736
5686

163
485
1695


545
946
3123

11
24
76

11
24
91

0.95

342
723
3295

444
817
3788


1029
2032
9343

163
591
3174


545
1113
5217

11
31
162

11
31
196

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                                 - 39 -
                          VI.  CONCLUSIONS
     The EPA faces a difficult policy problem.   The agency needs to
understand the many uncertainties that affect the relationship between
decisions to reduce the global use of PODs and  the effects that such
reduction might have on human health, materials degradation,  crop
yields, and other activities of interest.   We address only a small
subset of these uncertainties in this Note.  But the relationship of
these uncertainties to other parts of this policy problem provides the
basic motivation.  On the one hand, the problem is so complex that it
must be broken into pieces if we hope to produce useful results.  On the
other, the characterization of uncertainties in any part of this problem
is likely to be more useful if it properly reflects the concerns of the
problem as a whole.  We offer a way to build scenarios relevant to one
piece of the problem that relates them back to  the problem as a whole.
     This Note addresses uncertainties associated with production of
seven PODs.  Ideally, we would like to develop  a subjective probability
distribution for these chemicals and convolute  the uncertainties
reflected in this distribution with other sources of uncertainty
relevant to stratospheric ozone depletion.  In  such an approach,
developing a probability distribution for the PODs would be one step in
a process to develop a distribution for ozone depletion itself.  This
cannot be done because the cost of calculating  ozone-depletion profiles
is too high to allow extensive use of the Monte Carlo methods needed to
convolute all of the uncertainties relevant to  ozone depletion in a
complete and detailed way.
     Calculation costs dictate that only a limited number of cases be
considered in the atmospheric models used to study ozone depletion.
Hence, we must assure that the cases considered embody as much
information as possible.  That is, whether we examine it in detail or
not, a distribution for ozone depletion exists  that is consistent with
our assumptions about the uncertainties associated with inputs to the
atmospheric models and with the models themselves.  Since we cannot
investigate this distribution of ozone depletion directly and in detail,

-------
                                 - 40 -
the cases we use to examine parts of the distribution should tell us
something about where they lie in the distribution and about the
probability density of the distribution in their vicinity.   Our method
provides a way to relate scenarios for the future production of seven
PODs to the probability distribution for ozone depletion.
     The specific method we use is simple; the concept it  is based on
could be used to develop more complex methods that might be more
satisfactory.  It remains for future analysis to determine  how much
improvement additional complexity would allow.  For now, the specific
method we offer can be thought of as an illustration of a more general
conceptual approach and a practical way to implement that approach until
a better method is developed.
     Here is a quick overview of the approach.  Characterize uncertainty
about the growth rates of general economic activity and intensity of use
of chemicals relative to it with independent normal probability
distributions.  Choose values for the means and variances of these
distributions.  Define a policy-relevant score function as  a linear
combination of these growth rates.  Calculate the mean and  variance of
its subjective probability distribution.  Define scenarios  in terms of
quantiles of the distribution of the score function.  Identify growth
rates in the component distributions that are compatible with the value
of the score function for the quantile defining each scenario; use a
simple convention to do this.  Use the growth rates of the  component
distributions for a scenario to calculate the growth rates  for each
chemical in that scenario.
     The key to this approach is the score function.  It provides a
policy-relevant scale with which to compare alternative scenarios for
seven chemicals along a single dimension.  The dimension chosen is one
that should be related to the ozone depletion likely to result from the
scenarios it is used to describe.  The relationship is probably crude,
but the scale reflects the kind of simple weighting scheme  that EPA
policymakers have found useful in the past to specify the  relative
danger associated with different chemicals and hence the joint danger
associated with any set of production levels of these chemicals.  More
complicated score functions could be considered if we were  interested in
using a Monte Carlo technique to convolute uncertainties.   Ironically,

-------
                                  - 41  -
as the score function comes closer to approximating the actual joint
effect of a set of chemicals on ozone depletion, using it to develop
scenarios may become less attractive.  That is because a direct approach
to the subjective probability distribution for ozone depletion becomes
more attractive, eliminating the need for developing scenarios.
     Restricting our subjective distributions to normal distributions
and relying on linear approximations simplifies the analysis
considerably and in fact makes a closed analytical solution to the
convolution of uncertainties possible.  Abandoning normality, or some
other parametric distributions, would give us greater freedom to reflect
uncertainties as we see them but would require the use of a simulation
technique like Monte Carlo to convolute uncertainties.  Once this step
is taken, we probably no longer need to rely on linear approximations.
Simulations themselves, of course, typically require simplifying
assumptions and approximations to implement them at a reasonable cost.
Whether the approximations associated with normal distributions and
linear aggregations here induce more serious errors than the
simplifications and approximations required by a technique like Monte
Carlo is an empirical question.  It deserves closer attention if this
approach is to be used often in the future.
     Whether an analytical approach like that used here or a Monte Carlo
approach is taken, the interrelationships among chemicals deserve more
attention.  For example, CFC-11 and -12 are produced together.   Although
the proportions in which they are produced are variable,  it would be
surprising if cost considerations did not induce a positive correlation
in their production rates.   Alternatively, CFC-113 and methyl chloroform
are substitutes, but both are subject to a similar set of government
regulations.   Changes in markets and regulations that underlie the
scenarios used here could induce either a negative or positive
correlation in their growth rates.  These considerations  and others like
them suggest that future efforts to build scenarios for these chemicals
should give closer attention to the relationships in intensity of use
for different chemicals.  Our technique makes that simple to do.
     The techniques proposed here can produce a wide variety of
scenarios.  They are based on simple quantiles of the score function.
The low, middle, and high growth scenarios associated with the 25th,

-------
                                 - 42 -
50th, and 75th percentiles of its distribution characterize the relevant
policy space and should properly represent a reasonable range of effects
of market and technological developments in the larger context of EPA's
policy analysis.  Developing scenarios for other factors conditional on
the rate of general economic growth might also be worth exploring.  That
is because the level of the effects of ozone depletion on human
activities like materials degradation and crop yields is likely to
depend on the general rate of economic growth:  Higher chemical growth
rates will presumably have larger effects" on ozone depletion which, in
turn, will have more effect on crop yields if high economic growth has
created a demand for more crops.  Such relationships may prove to be
quite important in sorting out the joint effects of different sources of
uncertainty.  Our technique could accommodate scenarios conditioned on
general economic growth by calculating the moments for score functions
conditional on economic growth rates; how those growth rates would be
chosen remains a problem.
     In the end, the approach taken in this Note offers a simple
solution to a complex problem.  More complex solutions may well justify
their additional costs but that is not immediately clear.  Additional
attention to substantive  issues associated with the construction of
scenarios for application to the issue of potential ozone depletion is
likely to be more productive in the short run.

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                                 - 43 -

                               Appendix

       BASIC CODE USED TO IMPLEMENT AGGREGATIONS AND CONVOLUTION

     This appendix documents four BASIC programs that we employ to
convolute the distributions corresponding to different applications  of
CFC-11 and CFC-12, and to total use of each chemical.  In general,
variable names follow a few rules.   Those beginning with "mid" indicate
mean growth rates; those beginning with "sig" indicate standard
deviations.  The suffix ".g" refers to GNP, ".int" to intensity of use,
and ".com" to total use (combined GNP and intensity effects) .
     The first program is used to derive the means and standard
deviations of the distributions of the intensity growth rates  for CFC-11
and CFC-12 from the information presented in Hammitt et al.  (1986).
That source projects use in each major application for the United States
and the other CMA reporting countries separately.   It provides a
baseline projected use for each application and region together with
factors that, when multiplied by the base projected use in 2000,
characterize an 80 percent subjective probability interval for use.   The
program uses the estimated 1985 use, the projected base use  in 2000,  the
factors characterizing the uncertainty range,  and the parameters of  the
subjective distribution for GNP growth to calculate the parameters of
,the intensity growth rates for each region and application.   It also
convolutes these distributions to calculate the parameters of  the
distribution of rate of growth of intensity of total CFC-11  or CFC-12
use by region.
     The second program is used to  aggregate chemical use across
regions.  It takes as input the estimated 1985 use,  projected  baseline
2000 use, and factors characterizing the 80 percent subjective
probability interval to calculate the parameters of the intensity growth
rates by region,  and convolute these to find the parameters  of the world
intensity growth rate.  A similar program that uses the parameters of
the intensity growth rate distributions for each region is used to
calculate the parameters of the distribution of world intensity growth
rates for CFC-11 and -12.

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                                 -  44  -
     The third program calculates  the  parameters of the score function
distribution.   As input,  it requires the parameters of the distribution
of world GNP growth/  world intensity growth  for each chemical, and
weights that reflect  the  relative  ozone-depletion potency of each
chemical.  We run this program twice to calculate the parameters
corresponding to each period separately.
     The last program is  used to calculate the production of each
chemical corresponding to different quantiles of the score function, and
to quantiles of the marginal distributions for individual chemical
growth.  As input it  requires the  intensity  and GNP growth rates for the
pre- and post-2000 periods and the values of P for each period.
Variable names ending in  n.e" indicate first (early) period values
whereas names ending  in ".1" indicate  values in the later period.  These
suffixes are sometimes combined with the suffixes mentioned earlier; for
example, ".eg" refers to  GNP growth in the first period.
     A listing of the program code follows:
PROGRAM 1:  BASIC CODE TO CALCULATE PARAMETERS OF CFC-11 AND CFC-12
INTENSITY GROWTH RATES, BY REGION AND APPLICATION, 1985-2000
                                                     intensity
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
241
250
260
270
280
290
300
310
320
rem file cfc.bas to calculate CFC-11 and 12 in
rem for US and non-US reporting companies
open "incfc" for input as #1
input#l,n,mid.g, sig.g
for i = 1 to n
input#l,bO (i) ,bn(i) , lofact (i) ,hifact (i)
next
base = 0
for i = 1 to n
lorate(i) = (bn(i) * lofact(i) / bO (i) ) A (1/15)
lorate(i) = (lorate(i) - 1) * 100
hirate(i) = (bn(i) * hifact (i) / bO (i) ) A (1/15)
hirate(i) = (hirate(i) - 1) * 100
mid(i) = (lorate(i) + hirate(i)) / 2 - mid.g
sig(i) = (hirate(i) - lorate(i)) / (2 * 1.2816)
sig(i) = (sig(i)A2 - sig.gA2)A0.5
base = base + bO(i)
next
mid.int = 0
sig.int = 0
for i = 1 to n
share (i) = bO (i) / base
midterm(i) = share(i) * mid(i)
sigt(i) = share (i) * sig(i)

-------
                                 - 45 -
330     sigtsq(i)  = sigt(i)A2
340     mid.int = mid.int + midtenn(i)
350     sig.int = sig.int + sigtsq(i)
360     next
370     mid.com = mid.int + mid.g
380     sig.com = (sig.int + sig.gA2)A0.5
390     sig.int = sig.intA0.5
400     open "outcfc" for output as #2
410     print "mid.int = ",mid.int
420     print "sig.int = ",sig.int
430     print#2,"mid.int = ",mid.int
440     print#2,"sig.int = ",sig.int
450     print#2,"mid.g = ",mid.g
460     print#2,"sig.g = ",sig.g
470     print#2,"mid.com = "/mid.com
480     print#2,"sig.com = ",sig.com
490     print#2,"  share(i)";"  mid(i)   ";"  sig(i)"
500     for i = 1 to n
510     print#2,using"####*.####";share(i),mid(i),sig(i)
520     next
530     print#2,"bO","bn","lofact","hifact","lorate","hirate"
540     for i = 1 to n
550     print#2,bO(i) ,bn(i),lofact(i),hifact(i),lorate(i),hirate (i)
560     next
PROGRAM 2: BASIC CODE TO CALCULATE PARAMETERS OF WORLD
INTENSITY GROWTH RATES FOR OTHER CHEMICALS, 1985-2000

100     rem  file chm.bas to calculate world intensity for other chemicals
110     open "inchm" for input as #1
120     input#l,n
130     rho(l)  = 1.00
140     rho(2)  = 0.75
150     mid.g(l) = 3.0
160     sig.g(l) = 1.17
170     mid.g(2) = 3.5
180     sig.g(2) = 1.17
190     mid.g(3) = 3.0
200     sig.g(3) = 1.56
210     for i = 1 to n
220     input#l,bO(i),bn(i),lofact(i),hifact(i)
230     next
240     base = 0
250     for i = 1 to n
260     lorate(i) = (bn(i)  * lofact(i) / bO(i))A(1/15)
270     lorate(i) = ((lorate(i)  - 1)  * 100) - mid.g(i)
280     hirate(i) = (bn(i)  * hifact(i) / bO(i))A(1/15)
290     hirate(i) = <(hirate(i)  - 1)  * 100) - mid.g(i)
300     mid(i)  = (lorate (i) + hirate(i)) / 2
310     sig.c(i) = (hirate(i) - lorate(i)) / (2 * 1.2816)
320     sig(i)  = ((sig.c(i)A2) -  (sig.g(i)A2))A0.5
330     base = base + bO(i)
340     next

-------
                                 - 46 -
350     mid.int - 0
360     sig.int - 0
370     for i = 1 to n
380     shared) - bO(i) / base
390     midterm(i) = share(i) * mid(i)
400     sigt(i) = share(i) * sig(i)
410     sigtsq(i) = sigt(i)A2
420     mid.int = mid.int + midterm(i)
430     sig.int - sig.int + sigtsq(i)
440     next
450     if n - 3 then goto 480
460     crossprd - 2 * sigt(l) * sigt(2)
470     goto 490
480     crossprd - 2 *  (sigt(1)*sigt(2)  + sigt(1)*sigt(3)  + sigt(2)*sigt(3))
490     for i - 1 to 2
500     sig.int(i) - (sig.int + rho(i)  * crossprd)*0.5
510     next
520     open "outchm" for output as #2
530     print "mid.int - ",mid.int
540     print "rho,std dev"
550     for i - 1 to 2
560     print rho(i),sig.int(i)
570     next
580     printf2,nmid.int - ",mid.int
590     printf2,"rho,std dev"
600     for i - 1 to 2
610     print#2,rho(i),sig.int(i)
620     next
630     print#2,"mid(i)","sig(i)","share(i)"
640     for i = 1 to n
650     print#2,mid(i),sig(i),share(i)
660     next
670     print#2,"bO","bn","lofact","hifact","lorate","hirate"
680     for i - 1 to n
690     print#2,bO(i),bn(i),lofact(i),hifact(i),lorate(i),hirate(i)
700     next
PROGRAM 3: BASIC CODE TO CALCULATE PARAMETERS OF THE DISTRIBUTION
OF THE SCORE FUNCTION

100     rem  file joint.bas to calculate joint scenarios for all chemicals
110     rem  uses world gnp and world intensity distributions for each chemical
120     open "injoint" for input as #1
130     input#l,n,mid.g,sig.g
140     base = 0
150     for i = 1 to n
160     input#l,wgt(i),bO(i),mid(i),sig(i)
170     share (i) = wgt(i) * bO(i)
180     base = base + share(i)
190     next
200     mid.int = 0
210     sig.int = 0
220     beta = 0

-------
                                 - 47 -
230     for i = 1 to n
240     shared) = share (i) / base
250     midterra(i) = shared) * mid(i)
260     mid.int = mid.int + midterm(i)
270     sigt(i) = shared) * sig(i)
280     sig.int = sig.int + sigt(i)"2
290     beta = beta + sigt(i)
300     next
310     mid.com = mid.int + mid.g
320     sig.com = (sig.int + sig.gA2)A0.5
330     sig.int = sig.infO.5
340     beta =  (beta + sig.g) / sig.com
350     open "outjoint" for output as #2
360     print "mid.com = ",mid.com
370     print "sig.com = ",sig.com
380     print "mid.int = ",mid.int
390     print "sig.int = ",sig.int
400     print"mid.g= ",mid.g
410     print"sig.g= ",sig.g
420     print "beta = ",beta
430     print#2,"mid.com = ",mid.com
440     print#2,"sig.com = ",sig.com
450     print#2,"mid.int = ",mid.int
460     print#2,"sig.int = ",sig.int
470     printf2,"mid.g - ",mid.g
480     print#2,"sig.g = ",sig.g
490     print#2,"beta = ",beta
500     print#2,"mid(i)","sigd)", "share (i)"
510     for i = 1 to n
520     print#2,midd) ,sig(i),share (i)
530     next
540     print#2,"wgt(i)","bO(i)","midterm(i)","sigt(i)
550     for i = 1 to n
560     print#2,wgt(i),bO(i),midterm(i),sigt(i)
570     next
PROGRAM 4:  BASIC CODE TO CALCULATE CHEMICAL PRODUCTION CORRESPONDING
TO QUANTILES OF THE SCORE FUNCTION AND TO QUANTILES OF MARGINAL
CHEMICAL USE DISTRIBUTIONS

100     rem  file scenar.bas to calculate quantiles of joint  and individual
110     rem  chemical production distributions  over time
120     rem  subscript 1—CFC-11,  2—CFC-12,  3—CT,  4—CFC-113,  5—MC,
130     rem  6—Halon 1301,  7—Halon 1211,  0—Joint weighted  production
140     open "inscen" for input as #1
150     dim g(5,ll),q(5,7,ll),c<5,7,ll),year(ll)
160     input#l,beta.e,beta.1
170     inputf1,mid.eg,sig.eg,mid.lg,sig.lg
180     for i = 0 to 7
190     input#l,bO(i),mid.e(i),sig.e(i),mid.l(i),sig.l(i)
200     next
210     data -1.645,-0.675,0.0,0.675,1.645
220     for j  = 1 to 5

-------
                                 - 48 -
230     read zj(j)
240     zc.e(j) = zj(j) / beta.e
250     zc.l(j) - zj(j) / beta.l
260     rate.eg(j) = mid.eg + zc.e(j) * sig.eg
270     rate.e(j,0) =mid.e(0) + zj(j) * sig.e(O)
280     for t = 0 to 3
290     g(j,t) =  (1 + rate.eg(j)7100)A(t * 5)
300     q(j,0,t) = bO(0) *  (1 + rate.e(j,0)/100)A(t  *  5)
310     next t
320     rate.lg(j) = mid.lg + zc.l(j) * sig.lg
330     rate.l(j,0) -mid.1(0) + zj(j) * sig.l(O)
340     for t = 4 to 11
350     tm3 = t - 3
360     g(j,t) - g(j,3) *  (1 + rate.lg(j)7100)A(tm3  *  5)
370     q(j,0,t) = q(j,0,3) *  (1 + rate.1(j,0)7100)A(tm3  *  5)
380     next t
390     for i = 1 to 7
400     rate.e(j,i) = mid.e(i) + zc.e(j) * sig.e(i)  +  rate.eg(j)
410     rc.e(j,i) - mid.e(i) + mid.eg +  (zj(j)  * (sig.e(i)A2  + sig.egA2)A0.5)
420     for t = 0 to 3
430     q(j,i,t) = bO(i) *  (1 + rate.e(j,i)/100)A(t  *  5)
440     c
-------
                                 - 49 -
850     if i = 5 then print#2,"Methyl chloroform"
860     if i = 6 then print#2,"Halon 1301"
870     if i = 7 then print#2,"Halon 1211"
880     print#2,"Components of Joint Quantiles"
890     print#2," year";"       c(.05)";"      c(.25)";"      c(.50)";
                       c(.75)";"      c(.95)"
900     for t = 0 to 11
910     print#2,using"#####       ",-year (t) ,q(l, i,t) ,q(2,i,t) ,q(3,i,t),
                q(4,i,t),q(5,i,t)
920     next t
930     next i
940     for i = 1 to 7
950     printf2,"  "
960     if i = 1 then print#2,"CFC-11"
970     if i = 2 then print#2,"CFC-12"
980     if i = 3 then print#2,"Carbon tetrachloride"
990     if i = 4 then print#2,"CFC-113"
1000    if i - 5 then print#2,"Methyl chloroform"
1010    if i = 6 then print#2,"Halon 1301"
1020    if i = 7 then print#2,"Halon 1211"
1030    printf2,"Quantiles of Chemical Production"
1040    print#2," year";"       c(.05)";"      c(.25)";"      c(.50)";
                       c(.75)";"      c(.95)"
1050    for t = 0 to 11
1060    print#2,using"#####       ";year(t),c(1,i,t),c(2,i,t),c(3,i,t),
                c(4,i,t),c(5,i,t)
1070    next t
1080    next i

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                                  - 51  -
                             REFERENCES
Hammitt, James K., Kathleen A. Wolf, Frank Camm, William E. Mooz,
  Timothy H. Quinn, and Anil Bamezai, Product Uses and Market Trends for
  Potential Ozone-Depleting Substances: 1985-2000, The Rand Corporation,
  R-3386-EPA, May 1986.

Hirshleifer, Jack, Price Theory and Applications, Prentice-Hall, Inc.,
  Englewood Cliffs, N.J., 1976

Kahneman, Daniel, Paul Slovic, and Amos Tversky, Judgment Under
  Uncertainty:  Heuristics and Biases, Cambridge University Press,
  Cambridge, 1982.

Leontief, Wassily, "Population Growth and Economic Development:
  Illustrative Projections," Population and Development Review, Vol. 5,
  No. 1, 1979.

National Academy of Sciences, Halocarbons:  Effects on Stratospheric
  Ozone, Washington D.C., 1976.

National Academy of Sciences, Protection against Depletion of
  Stratospheric Ozone, Washington B.C., 1979.

National Academy of Sciences, Causes and Effects of Stratospheric Ozone
  Depletion:  An Update, Washington D.C., 1982.

National Academy of Sciences, Causes and Effects of Changes in
  Stratospheric Ozone:  Update 1983, Washington B.C., 1984.

Palmer, Adele R., William E. Mooz, Timothy H. Quinn and Kathleen A.
  Wolf, Economic Implications of Regulating Chlorofluorocarbon Emissions
  from Nonaerosol Applications, The Rand Corporation, R-2524-EPA, June
  1980.

Quinn, Timothy, Kathleen A.  Wolf, William E.  Mooz, James K. Hammitt,
  Thomas W.  Chesnutt,  and Syam Sarma, Projected Use,  Emissions and Banks
  of Potential Ozone-Depleting Substances, The Rand Corporation,
  N-2282-EPA, January 1986.

Ramanthan,  V.,  R. J.  Cicerone,  H. B. Singh,  and T. J. Kiehl,  "Trace
  Gases and Their Potential  Role in Climatic Change," J.  Geophysical
  Res., Vol.  90,  June 20,  1985.

U.S. Environmental Protection Agency, "Ozone-Depleting
  Chlorofluorocarbons,  Proposed Production Restriction," Federal
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