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THE COSTS OF LIMITING FOSSIL-FUEL CO2 EMISSIONS:
A Survey and Analysis1 Michael Grubb
Energy and Environmental Programme, Royal Institute of International Affairs,
London, England
Jae Edmonds
Technical Leader, Economic Programs, the Pacific Northwest Laboratory,
Washington, DC, USA
Patrick ten Brink and Michael Morrison
Caminus Energy Limited, Cambridge, England
KEY WORDS:energy, greenhouse, climate change, greenhouse emissions reduction cost
TABLE OF CONTENTS
MODELLING AND COSTING DEFINITIONS AND PARADIGMS
ABATEMENT TECHNOLOGIES AND TECHNOLOGY COST CURVES
A REVIEW OF SYSTEM-WIDE ABATEMENT COST ESTIMATES
KEY DETERMINANTS: TECHNOLOGICAL VS ECONOMIC PERSPECTIVE
KEY DETERMINANTS: ABATEMENT STRATEGIES AND SCOPE OF ANALYSIS
In the late 1980s, interest nourished in the issue of global climate change. Many studies focussed on the options for limiting anthropogenic emissions of greenhouse- related gases and managing the consequences of global warming and climate change. Making appropriate policy choices requires information on both the costs and benefits, as they occur over time, of policy interventions, and an increasing number of studies have sought to quantify the costs especially of limiting CO2 emissions, as the dominant anthropogenic source. Such analyses now form an important part of overall policy assessments and influence international negotiations on policy responses. However, these studies are not well understood. In this paper we seek to analyze the literature on the costs of CO2 abatement.
The majority of work in estimating the costs of reducing greenhouse gas emissions has occurred since 1988, but interest in the issue of costing emissions reductions began more than a decade earlier with the work of Nordhaus (1, 2). Nordhaus's early work focussed on the issue of reducing fossil- fuel CO2 emissions, as did that of Edmonds & Reilly (3, 4), Kosobud et al (5), Seidel & Keyes (6), Rose et al (7), Lovins et al (8), Williams et al (9), Manne ( 10), Perry et al (11), Nordhaus & Yohe ( 12), and Mintzer (13), among others. Only Seidel & Keyes, Perry et al, and Mintzer examined non- CO2 emissions, and these studies treated them separately and in an ad hoc manner; none of the studies took land- use change into account explicitly.
While not the primary focus of their analysis, some of the studies conducted prior to 1988 analyzed the cost of emissions reductions. The results of these studies foreshadow the current debate. Edmonds & Reilly (14) noted in their 1985 literature assessment:
The economic costs of CO2 abatement policies have only been partially analyzed at this time. Edmonds and Reilly, Kosobud et al, and Nordhaus, each using a different model, indicate that the reduction in aggregate GNP associated with even stringent punitive strategies is not large, usually only a few percentage points. Lovins et al argued that the costs might actually be negative.
The purpose of this paper is fourfold. First, we seek to give a broad and accessible guide to the main studies reported over the past five years.3 Second, we seek to clarify the issues involved in estimating abatement costs through a systematic study and classification of the relevant concepts. Third, through critical analysis of reported results, we suggest ranges of plausible estimates. Finally, we highlight the most important areas of uncertainty or confusion and suggest areas on which future research needs to concentrate.
To this end, we start (Section 2) by noting differing uses of the term "costs" and the way in which scope and definition of analysis affects results.
2Note that the list of relevant emitted gases differs importantly from the list of greenhouse gases. The list of relevant greenhouse gases, that is, those gases that are effectively transparent to incoming sunlight but that absorb in the infrared spectrum, includes CO2, CH4, N2O, O3, H2O, CFCs, and CFC substitutes. Greenhouse- related emitted gases are linked to greenhouse gases through natural processes such as atmospheric chemistry and albedo.
1In finalizing this review, we have sought to reference the most accessible, relevant, and general sources, rather than obscure or superseded ones. In panicular, the series of papers by Cline, and by Manne &Richels, have each been brought together in books; various studies for the European Commission have been brought together in a two- volume edition of the European Economy; and many of the reports by the Organization for Economic Cooperation and Development (OECD) Economics Department have been reproduced in a special issue of OECD Economic Sludies. All these volumes were published dunng 1992, and to the extent possible we reference the books rather than the many separate research papers.
We clarify the way in which we use the term in this paper so that results are to the extent possible comparable.
Sections 3 and 4 then review abatement cost estimates. Section 3 summarizes estimates derived directly from studies of the technologies available for limiting emissions, and ways of interpreting them. Section 4 summarizes the results of studies that have sought to model the impact of CO2 abatement on whole energy systems.
Sections 5 and 6 then explore the modelling and assumption differences that affect cost estimates. Section 5 explains and classifies the different kinds of models that have been applied, and Section 6 reviews the impact of variations in key numerical parameters. Sections 2-6 draw heavily on the review of literature performed for Phase I of the United Nations Environment Programme (UNEP) Greenhouse Gas Abatement Costing Studies (16).
The paper then draws together the material in sections 2-6, to examine critically the nature and relative importance of these various sources of cost difference, and the implications that follow from this. Section 7 analyzes the economic and engineering perspectives, the differences between which are a major source of cost differences; the discussion includes the role of energy-efficiency and of low-carbon supply technologies, as well as resolution of these perspectives. Section 8 then examines issues relating to the strategy of abatement and scope of analysis. Finally, Section 9 draws general conclusions from the study, and suggests some implications for future research.
MODELLING AND COSTING DEFINITIONS AND PARADIGMS
The cost of emissions reductions is always computed as a difference in a given measure of performance between a reference scenario and a scenario that involves lower emissions. By far the most commonly used measures of performance are the net direct financial costs to the energy sector assessed at a specified discount rate; and the estimated impact on gross national product (GNP), or its close cousin GDP. GNP is the monetary value of new final goods and services produced in a given year, and it provides a measure of the scale of human activities that pass through markets, plus imputed values of some nonmarket activities. It is generally assumed that financial costs in the energy sector can be closely related to impacts on GNP, though as noted below this is not always the case.
Neither direct financial costs nor GNP provide direct measures of human welfare. One factor is that human welfare does not necessarily increase linearly with the degree of consumption; a given loss of income will likely matter far more to poor people, or poor countries, than to richer ones, for example. Some studies attempt to capture this through "equivalent welfare" measures, but these still rely centrally on a marketed-products basis. A broader limitation is revealed by the fact that there are many examples where GNP moves in the opposite direction to human well-being. For example, a disease that increases the sale of medicine may boost GNP but make individuals worse off; environmental disasters can stimulate economic activity, but the environment (and human enjoyment of it) is diminished.
This reflects the fact that GNP does not incorporate many nonmarket factors that affect welfare. Some studies have sought to examine explicitly the impact of abatement on various external costs, and concluded that these can be very significant (Section 8.4). However, in general, studies focus on financial costs or GNP impact. In the broader literature, other welfare indices have been attempted (such as the United Nations Development Programme's (UNDP) Human Development Index), but data are rarely adequate to quantify impacts in such terms in abatement-costing studies. At present, for quantifying results there is little practical alternative to working with monetary cost and GNP impacts, but the caveats about these as measures of welfare impacts need to be borne in mind.
Nor is GNP necessarily a good measure of consumption. For example, some forms of carbon taxation can move resources from consumption to investment, which can boost GNP but for many years may lower consumption. It is unclear whether welfare has improved or declined. Alternatively, tax revenues might be returned to households, which could raise household consumption but depress long-term GNP.
This also raises the issue of comparing costs in different periods. Results concerning abatement costs are sensitive to the assumed discount rate. This is particularly important with respect to evaluating the importance of the potential impacts from climate change, where the appropriate discount rate is both crucially important (because of the long timescales) and very uncertain (because of the timescales and because it is an attempt to make an explicit valuation of long-term public welfare); for a discussion see Cline (17). For assessing abatement costs, the timescales are less and the discount rate has to be related to the actual rates revealed or set by government for the sector in which the abatement investments are being made, so this is a less central (though still significant) issue. In this study we simply report results as estimated by the studies concerned, given the discount rates they assume (which, for the major energy investments considered in this study, are typically about 5-8% real discount rate).
Almost since the beginning of costing studies, a clear division has existed between those that fundamentally use an economic approach, which relies on observed market behavior and which generally assume that markets operate equally efficiently in the reference and abatement case; and those that use a technology-engineering approach, which emphasizes a technically optimal abatement scenario (which may be contrasted with a reference case that is by implication not optimal). The choice of "cost paradigm" in this sense is a fundamental determinant of results--including often the sign of abatement costs--and these differences form an important theme of this paper.
Economic studies use "top-down" models, which analyze aggregated behavior based on economic indices of prices and elasticities, and focus implicitly or explicitly on the use of carbon taxes to limit emissions. These studies have mostly concluded that relatively large carbon taxes (e.g. that could much more than double the minemouth cost of coal) would be required to achieve goals such as the stabilization of fossil-fuel carbon emissions .
Technology-oriented studies use "bottom-up" engineering models, which focus on the integration of technology cost and performance data. Many such studies have concluded conversely that emission reductions could be achieved with net cost savings.
The division between the "economic paradigm" and the "engineering paradigm" is closely related--but not identical--to the division between "top-down" and "bottomup" models, as it has emerged in the
Integrated Science Model for Assessment of Climate Change
Atul K. JainGlobal Climate Research Division
Lawrence Livermore National Laboratory
P.O. Box 808, L-262, Livermore, California 94551
Haroon S. Kheshgi
Exxon Research and Engineering Company
Route 22E, Annandale, NJ 08801
Donald J. Wuebbles
Global Climate Research Division
Lawrence Livermore National Laboratory
P.O. Box 808, L-262, Livermore, California 94551
This paper was prepared for submittal to the 87th Annual Meeting and Exhibition of the Air & Waste Management Association
Cincinnati, Ohio June 19-24,1994
April 1994
UCRL-JC-116526 Rev 1
INTRODUCTION
Past measurements show that greenhouse gas concentrations, many of which are affected by human related activities, are increasing in the atmosphere. There is wide consensus that this increase influences the earth's energy balance and concern that this will cause significant change in climate.1,2 Many different policies could be adopted in response to the prospects of greenhouse warming. Models are used by policy makers to analyze the range of possible policy options developed as a response to concerns about climate change. A fully integrated assessment model that spans the many aspects of climate change, including economics, energy options, effects of climate, and impacts of climate change, would be a useful tool. With this goal in mind, the science modules which estimate the effect of emissions of greenhouse gasses on global temperature and sea level are being developed. This is a report of the current characteristics and performance of an Integrated Science Model which consists of coupled modules for carbon cycle, atmospheric chemistry of other trace gases, radiative forcing by greenhouse gases, energy balance model for global temperature, and a model for sea level response.
Integrated assessment models should not only help to identify the relevant questions, but should also serve to structure the research results and thus facilitate clear communication between the scientists and policy makers. The process of global climate change and its possible ecological, economic and social impacts involves interactions between physical, ecological, economic and social systems. Research efforts can be divided into three broad areas: the relation between emissions and climate; the relation between climate and impacts; and the relation of policy and economics to emissions and impacts. This report addresses the first of these three.
Currently, only simplified models are used to analyze the large number of emission reduction scenarios required as part of the policy-making process. At present there are five such simplified models that attempt to relate emissions to climate change which are intended for use in an integrated assessment model: the Muenster Climate Model (MCM) developed by Vain and Bach3; the AMAC model developed by Prather4 for EPA; IMAGE model developed by Rotmans et al.5; STUGE developed by Wigley et al.6; and ICAM developed by Dowlatabadi and Morgan7. The Integrated Science Model presented in this report incorporates the previous lessons of these earlier models, while improving the modules for carbon cycle and atmospheric chemistry of other trace gases. Improvements in the understanding of these processes are discussed in the IPCC 1994 Report on Radiative Forcing of Climate. This model is used to estimate the relation between the time-dependent rate of greenhouse gas emissions and quantitative features of climate--global temperature, the rate of temperature change, and sea level--that are thought to be indicators of human impact on climate and ecosystems. Notwithstanding, there remains significant uncertainty in the modeled relation between emissions and climate.
MODELING APPROACH
Fig. 1 shows the coupled model concept employed. The model consists of several sub-models converting emissions of major greenhouse gases to concentrations, an energy balance climate model for the atmosphere and the ocean, and a sea level rise model. These are linked in a simple way: the output of one model serves as input for the next. The following greenhouse gases contributing to the additional man-made greenhouse effect are used as input: CO2, CH4, N2O, CFC-11, -12, -113, -114, -115, HCFC-22, Halon-1301, carbon tetrachloride (CCl4), methyl chloroform (CH3CCl3), and stratospheric water vapor. The greenhouse effect is modeled as a dynamic process with discrete time steps of one year and a simulation period of 335 years, i. e. from 1765 (the beginning of the industrial era) to 2100. The model runs to simulate the periods of 1765 to 1990 and 1990 to 2100 are based on estimates of historical mission data and specific future emission scenarios. Fig. 1 also shows which modules will be added to the existing model in the near future. Trace gases not included in this study, such as Ozone, other CFCs and Halons, are planned to be included in the future. Here we give only a brief overview of various coupled models.
Concentration Models
CO2. The concentration of CO2 is calculated by a newly developed globally averaged carbon cycle model which consists of four reservoirs, namely the atmosphere, the terrestrial biosphere, the mixed ocean layer, and the deep ocean. The atmosphere and the mixed layers are modeled as well mixed reservoirs. Transport of total inorganic carbon in the deep ocean is modeled by a partial differential equation, spanning time and ocean depth, which accounts for vertical diffusion and upwelling. The rate of transport in the deep ocean is dependent on two parameters: eddy diffusivity and upwelling velocity8. Water upwells through the deep ocean column to the surface ocean layer from where it is returned, through a polar sea, to the bottom of the ocean column thereby completing the thermohaline circulation. Air-sea exchange is modeled by an air sea exchange coefficient in combination with the buffer factor that summarizes the chemical re-equilibration of sea water with respect to CO2 variations. An additional source term is added to the model deep ocean to account for the oxidation of organic debris containing carbon removed in the surface ocean layer by photosynthesis and brought to the deep ocean by particulate settling. To estimate the flux of CO2 between the terrestrial biosphere and the atmosphere, a multi-box, globally-aggregated, terrestrial-biosphere sub-model is coupled to the atmosphere box. The mass of the carbon contained in the different terrestrial reservoirs and the rate of exchange between them have been based on the analysis by Harvey.9 The photosynthetic rate of carbon fixation is modeled to increase logarithmically with atmospheric CO2 concentration and is proportional to a CO2 fertilization factor. The exchange coefficients between boxes contained in the terrestrial biosphere model are temperature dependent.
CFCs HCFCs and N2O. The past and future atmospheric N2O, CFC-11, -12, -113, -114, -115, HCFC-22, Halon-1301, CCl4, and CH3CCl3 concentrations are calculated by a simple mass balance model described by Bach and Jain10. In this model, the annual concentrations of specific gasses are determined by their initial concentrations, and emission and removal rates. The removal rates of these gasses are assumed to be inversely proportional to their atmospheric lifetimes.
The CFC content in the atmosphere is based on the amount that escapes into the atmosphere and is calculated directly from the amount produced. In this study the products of CFC-11 and CFC-12 are divided into four categories, namely, prompt emitters (aerosol and open cell foam), hermetically-sealed refrigeration, non-hermetically-sealed refrigeration and closed cell foam. Emission characteristics of these product classifications have been assessed using the assumptions of Bach and Jain10 and Gamlen et al.11 Most of the CFC-113 is emitted promptly, but an estimated 15% of the production is lost in waste disposal, dumps, and incinerators. 12 Thus for calculation purposes, we assume that world emission of CFC-113 is 85% of world production. Halons are largely banked in the fire extinguishing systems. Small amounts are emitted through leakage, fire practices and when the units are disposed. Thus it is assumed that for Halons the total annual production is added to the quantity that is already stored, the bank, and fixed fraction of this bank is emitted annually according to the procedure described by Bach and Jain.10 CFC-114, -115, CCl4, HCFC-22, and Methyl Chloroform will be released shortly after their production, thus it is assumed that their annual emission rates are equal to their production rates.
CH4. The methane concentration in the atmosphere is calculated by simulating the main atmospheric chemical processes influencing the global concentrations of CH4, CO, and OH, using the global CH4-CO-OH cycle model developed by Rotmans et al.13 The removal rates of CH4 and CO are determined by accounting for the uptake by soils, transport to the stratosphere, and oxidation by OH radicals. We assume the uptake velocity by soils and the transport velocity to the stratosphere to be time-independent, although there is evidence that these values change with time.14 The concentration of OH radicals is determined by the photochemical balance between production of OH and the loss rate due to reaction with CH4 and CO.15 The reaction rate constants for the reactions of CH4 and CO with OH are taken from the recent measurements by Vaghjiani and Ravishankara.16 The source of OH radicals in the troposphere is the reaction between excited state oxygen atoms and water vapor. The excited oxygen atoms are produced by ozone photolysis at wavelengths below about 310 nanometers. Thus, ozone is the source of hydroxyl in the troposphere. In turn, nitrogen oxides (NOx) are the photochemical source of tropospheric ozone. Under low-NOx conditions, the methane oxidation reactions result in a decrease of ozone and OH. When high-NOx conditions exist, methane oxidation results in a net increase of ozone and OH. In this study, we assume ambient conditions representative of the low-NOx case. The contribution of NOx to the greenhouse effect as a photochemical precursor of ozone is not considered in this study.
Climate Model
We use the globally averaged energy balance climate model developed by Harvey and Schneider.17 This box advection-diffusion model contains a vertically integrated atmosphere box, a mixed-layer ocean box, an advective-diffusive deep ocean, and a thin slab representing land thermal inertia. In the deep ocean, heat is transported upwards with an advection velocity, and downwards by physical processes represented by a single, effective diffusion coefficient. Perturbations in the net radiative forcing from CO2 and other trace gases are computed using formulae of Shine et al.18, which were derived from detailed radiative transfer models. For H2O the radiative forcing is approximately 1/3 that of CH4.18 The contribution of stratospheric H2O is very uncertain and may be less important than modeled using this formulae; its contribution, however, is small, amounting to a maximum of 0.4 Wm-2 by 2100.19
The response of the climate system to the changes in radiative forcing is principally determined by the climate sensitivity, deltaT2X, defined as the equilibrium surface temperature increase for doubling of atmospheric CO2 concentration. This parameter is intended to account for all the climate feedback processes not modeled explicitly. Explicit feedbacks included in the model are the temperature dependence of CO2 solubility (the buffer factor), terrestrial biosphere exchange rates, and methane chemical kinetics. Recent general circulation model estimates for deltaT2X range from 1.5 to 4.5 °C.1 Lindzen20 proposed the value of deltaT2X could be as low as 0.5 °C. Based on the observed temperature record, Schlesinger and Jiang21 found the value of deltaT2X =1.2 °C; but as discussed by Kheshgi and White22,23 there is large uncertainty in deltaT2X estimated from the observed temperature record because of the unknown contribution from the climate's natural variability.24 deltaT2X = 2.5 °C is considered by some25,26 as the best estimate of climate sensitivity. In the present study, the calculations have been performed for the three values of the climate sensitivity, namely 1.5, 2.5 and 4.5 °C.
Sea Level Rise Model
The effects of global warming on sea level are determined by four processes: (i) thermal expansion of the ocean water (ii) melting of mountain glaciers, (iii) ablation of the Greenland Ice Sheet, and (iv) ablation or accumulation of the Antarctic Ice Sheet (notably the West Antarctic Ice Sheet). The sea level model shown in Fig. 1 uses the calculated transient temperature changes to estimate sea level changes due to thermal expansion and melting ice.
For the calculation of the thermal expansion we use the thermal expansion coefficients from Leyendekkers27 which are salinity and temperature dependent. Vertical variations in thermal expansion are included explicitly in our model. Volume changes of glaciers and small ice caps are estimated according to Oerlemans.28 With respect to the Greenland and Antarctic Ice Sheets, the dynamic response can be ignored for the time scale considered here. The static changes in the surface mass balance are modeled according to Warrick and Oerlemans29 and Oerlemans.28
MODEL VALIDATION
We validate model components by comparison to available data. In this section we report comparisons of reconstructions of past sea level, global temperature and CO2 concentration to model results.
Fig. 2 compares the computed atmospheric CO2 concentration to the observed CO2 record spanning from 1765 to 1990. The observed record from 1765 to 1959 is obtained from infrared laser spectroscopy measurements taken from the Siple ice-core30, and thereafter it is from the Mauna Loa Observatory, Hawaii.31 Starting from a preindustrial concentration of 278 ppmv CO2, the model result accurately reproduces the growth of CO2 evident in the record. In 1990, the modeled atmospheric CO2 concentration was 354.2 ppmv as compared to the observed concentration of 353.8 ppmv.
In Fig. 3, the record of the global mean surface air temperature compiled by Jones et al.32, given as anomalies from the mean temperature from 1950 to 1979, are compared with model results. The model calculations are presented for climate sensitivities deltaT2X of 1.5, 2.5 and 4.5 °C. The model temperature curves are based on the effects of the greenhouse gases taken into account here, while the temperature record also incorporates natural climatic variations and other possible additional anthropogenic influences. For example, solar irradiance changes as well as stratospheric and tropospheric aerosols have been estimated to have an effect the surface temperature33, 34, 35. In this paper, however, we do not account for the influence of solar irradiance and aerosols, because of the uncertainty in estimating both past and future effects. The model-calculated surface temperature changes in 1990, relative to a 1950-1979 reference period, are 0.23, 0.34, 0.48 °C for the CO2 doubling temperature sensitivities 1.5, 2.5 and 4.5 °C, respectively. This compares to an observed temperature anomaly of 0.38 °C in 1990.32
Fig. 4 compares the calculated mean sea level rise from 1880 to 1985 with the observed values shown as deviations from the 1951 to 1970 period.36 For the climate sensitivity range of 1.5 to 4.5 °C, the model-estimated sea level rise from 1765 to 1990 ranges from 5.6 to 13.6 cm. Our estimated mean sea level rise is similar to that obtained by Oerlemans37 (ca. 9.5 cm from 1850 to 1985), and Gornitz et al.38 (ca. 10 cm from 1880 to 1980).
This type of model validation increases the confidence in the model calculations which are the only tools available for evaluating possible future trends. Future emission scenarios are examined in the following section.
ASSESSING EMISSIONS AND STABILIZATION SCENARIOS
Concern over the potential impacts of climate change caused by increases in greenhouse gases has led to policy proposals to reduce the rate of greenhouse gas emissions. The objective put forth in the Framework Convention on Climate Change (FCCC) as signed at the UN Conference on Environment and Development (UNCED) in Rio in 1992 is:39
- ..."the stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system"
and
- ..."such a level should be achieved within a time frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner."
This objective, however, does not state quantitative targets. Specific measures will likely be designed to affect emission rates. The impacts of climate change are likely to be more closely related to properties of the climate system, such as sea level or global temperature, than to emission rates of greenhouse gases. Here we consider three observable quantitative properties of the climate system: global nearsurface temperature, the rate of temperature change, and sea level. While the Integrated Science Model is not intended to estimate impacts, it is our hope that relation of emission rates to properties of climate will assist in evaluating policy options.
We use our Integrated Science Model to estimate the rate of emissions implied by Stabilization Scenarios. Stabilization Scenarios set the time variation of greenhouse gas concentrations leading to constant concentrations at some level. We also estimate the buildup of greenhouse gas concentrations, global temperature and its rate of change, and sea level implied by Emissions Scenarios. Emissions Scenarios set the time variation of emission rates of the various greenhouse gases. These analyses allow comparison of these different types of scenarios, within model uncertainties. Our Integrated Science Model is used to estimate the above quantitative properties of climate resulting from an Emissions or Stabilization Scenario, however, it cannot be used to imply target values.
Stabilization Scenarios
Devising strategies to meet the Rio Convention's objective of stabilization of concentrations requires a quantitative relationship between emissions and concentration. The calculations presented in this section illustrate aspects of what may be required to achieve stabilization of CO2 concentration. For CO2, IPCC WG1 has provided illustrative CO2 concentration pathways shown in Fig. 5a leading to stabilized CO2 concentrations of 350, 450, 550, 650, and 750 ppmv. These concentration pathways span a range of scenarios from stabilization at recent CO2 concentration (350 ppmv) to a scenario (750 ppmv) that resembles the IPCC1 business-as-usual (BAU) scenario for times before 2100. In addition, one scenario for emissions caused by land use change was specified and is intended to be used in tandem with the five CO2 pathways. The relation between these scenarios and the FCCC39 stabilization objective has not been determined.
We use our Integrated Science Model to perform an inverse carbon cycle calculation to estimate the time varying fossil fuel emissions of CO2, shown in Fig. 5b, required to match the five concentration stabilization scenarios. These calculations are considered in the IPCC 1994 Report on Radiative Forcing of Climate for which the results of our Integrated Science Model was contributed.40 All the calculations show that stabilization requires a reduction in emissions at some time in the future. In all the stabilization cases, there are increasing emissions initially followed by rapid decreases. Moreover, in case S350 fossil fuel emissions are reduced to below zero, before rising to a small positive value. Negative emissions would have to be accomplished by introduction of a new (or enhancement of an existing) CO2 sink. These results show that the small relative changes in prescribed CO2 concentrations lead to large changes in fossil fuel emissions. The high sensitivity of the inverse calculation implies that uncertainties will be magnified when using this approach to define strategies for emission reductions that would track a prescribed path to concentration stabilization. Estimation of the effect of the terrestrial biosphere feedback (to rising CO2 and changing climate) on carbon cycle is a likely source of inaccuracy. In addition, the inverse calculation also requires estimates of land use emissions whose future magnitudes are highly uncertain which implies a comparable uncertainty in estimated CO2 emissions goals.
Defining Requirements for Limiting Climate Change and Protecting Ecosystems
One way of developing criteria for climate and ecosystem protection would be to determine the maximum rate at which ecosystems can adapt to changes in temperature and precipitation patterns. At the Villach and Bellagio Climate Conferences41 it was suggested that a global rate of temperature change of 0.1 °C per decade change be taken as an initial target value, which would allow for the adaptation of ecosystems. However, decadal changes in global temperature greater than 0.1 °C are evident in the instrumental record (see Fig. 3). We use 0.1 °C per decade and a mean global warming of 2 °C from preindustrial time to 2100 as Illustrative Reference Values for climate and ecosystem protection. In the following analysis of Emissions Scenarios, results can be compared to these Illustrative Reference Values.
IPCC Emissions Scenarios
Table 1a lists the Emission Scenario from 1990 to 2100 for the twelve greenhouse gases corresponding to Scenario IS92a of the Intergovernmental Panel of Climate Change (IPCC)42. This scenario is a close approximation to the earlier IPCC1 BAU Scenario. Scenario IS92a takes into account only those emission control policies that were internationally agreed upon at that time.42
In Scenario IS92a, CO2 produced from fossil fuel burning and cement production increases by factor of three from 1990 to 2100, whereas CO2 emissions from forest burning are considerably reduced. In the late 21st century there is a small rate of CO2 absorption from the atmosphere due to reforestation. N2O and CH4 emissions, which include both anthropogenic and natural sources, increase ~30% and 60%, respectively, by 2100. CFCs and Halon are being completely phased out and to a large extent substituted by the partially-halogenated HCF-22. Greenhouse gas emissions, reported as Equivalent CO2 Emissions (see Table 1a for values and definition), increase 74% between 1990 and 2100.
Table 1b shows the emission changes of low emissions IPCC scenario IS92c.42 CO2 produced from fossil fuels and cement production show a 23% reduction. There is an increase in N2O and CH4 of 6% and 8%, respectively, and although the CFCs and Halon are being phased out, the nine fold increase of HCFC-22 of IS92a is maintained. Overall, in terms of Equivalent CO2 Emissions, there is a 26% reduction.
Equivalent CO2 Emissions for the scenarios IS92a, IS92c are shown in Fig. 6a. Equivalent CO2 Emissions are based on the 100-year GWP-estimates of the IPCC43. For comparison between scenarios and for comparison to the FCCC stabilization objective we also define and calculate Equivalent CO2 Concentration:
(formula)
[CO2]equivalent = [CO2]1765 · exp [SIGMA eta i] [i=Trace 6.3W/m2][Gases
The radiative forcing of gas i is (eta)i (W/m2). The combined radiative effect of all greenhouse gases considered in our Integrated Science Model is represented by the Equivalent CO2 Concentration calculated for the two IPCC scenarios is shown in Fig. 6b. In IS92a scenario the Equivalent CO2 Concentration is modeled to have increased from 415 ppmv to over 900 ppmv by 2100, and is rate of increase is accelerating. In contrast, in IS92c scenario the Equivalent CO2 Concentration is modeled to have increased to 600 ppmv by 2100, and the rate of increase is still positive but decreasing. The concept of climate stabilization would ultimately call for a constant Equivalent CO2 Concentration.
Equivalent CO2 Concentrations for the IPCC scenarios are used to calculate global mean temperatures. We use the Integrated Science Model to estimate the rates and levels of global mean temperature change. Temperature and its rate of change can then be compared to the Illustrative Reference Values described above. Fig. 7a shows estimates of the global temperature change from its preindustrial value for Emissions Scenarios IS92a and IS92c. Estimates are, of course, highly dependent on the value of climate sensitivity. Results for deltaT2X = 1.5 and 4.5 °C are shown. This range in climate sensitivities results in a range of estimated temperature rise comparable to that caused by the difference between scenarios. The results indicated that both IPCC scenarios are sufficient to keep the increase the global temperature below the illustrative warming ceiling of 2 °C (for times up to 2095) for a climate sensitivity of 1.5 °C. Both scenarios lead to greater than 2 °C warming for a climate sensitivity of 4.5 °C . In scenario IS92a, a warming of 2 °C is exceeded as early as 2030, 2055, and 2095 for climate sensitivities of 4.5, 2.5, and 1.5 °C, respectively.
The rate of the climate change is thought to exert stress on ecosystems. While changes in, for example, precipitation or infrequent events such as droughts or storms may be more directly related to this stress, there remains great uncertainty in estimating these characteristics of climate. Instead we consider only the rate of global temperature change shown in Fig. 7b. From preindustrial time to 1950 the rate of warming estimated to be caused by the anthropogenic release of greenhouse gases is calculated to be less than 0.08 °C per decade (Fig.7b). The observed rate of temperature change over this time period, largely effected by natural variability, is significantly greater (Fig. 3). It is remarkable that the rate of anthropogenic-caused temperature change is calculated to be not much greater than the present for IS92a, and less than the present for IS92c. There may, however, be greater sensitivity of ecosystems to temperature increase in warmer climates.
The model estimated effect on sea level is shown in Fig. 8 of scenarios IS92a and IS92c. There is a longer time lag for effects on sea level, than on global temperature. For the climate sensitivity range of 1.5 to 4.5, the model-estimated sea level rise in 1990 ranges from 5.6 to 13.6. Estimates of sea level rise from 1990 to 2100 range from 16 cm for IS92c with a climate sensitivity of 1.5 °C, to 46 cm for IS92a with a climate sensitivity of 4.5 °C.
CONCLUSIONS
Integrated assessment models are intended to represent processes that govern physical, ecological, economic and social systems. This report describes a scientific model relating emissions to global temperature and sea level. This model is intended to be one component of an integrated assessment model which is, of course, much more comprehensive. The model is able to reproduce past changes in CO2 concentration, global temperature, and sea level. The model is used to estimate the emissions rates required to lead to stabilization of CO2 at various levels. The model is also used to estimate global temperature rise, the rate of temperature change, and sea level rise driven by IPCC emissions scenarios IS92a and IS92c. The emission of fossil fuel CO2 is modeled to have the largest long term effect on climate. Results do show the importance of expected changes of trace greenhouse gases other than CO2 in the near future. Because of the importance of these other trace gases, further work is recommended to more accurately estimate their effects.
ACKNOWLEDGMENTS
Work was performed under the auspices of the U. S. Department of Energy at the Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48 and was supported in part by the Department of Energy's Environmental Science Division.
REFERENCES
27. J. V. Leyendekkers, Thermodynamics of Sea Water. Dekker, New York, 1976, 262-304.
28. J. Oerlemans, "A Projection of Future Sea Level", Climatic Change, 15, 151-174 (1989)
37. J. Oerlemans, "A projection of future sea level", Climatic Change 15, 151-174 (1989).
