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The Global Climate Policy Evaluation Framework

David Cohan and Robert K. Stafford

Decision Focus Incorporated
650 Castro Street, Suite 300
Mountain View, CA 94025

Joel D. Scheraga and Susan Herrod

Office of Policy, Planning, and Evaluation
U.S. Environmental Protection Agency
401 M Street, SW
Washington, DC 20460

Forthcoming in
Proceedings of the 1994 A&WMA
Global Climate Change Conference: Phoenix April 5-8,
Air & Waste Management Association, Pittsburgh, 1994.

ABSTRACT

The prospect of climate change confronts policy makers with difficult choices. The climate change issue is enormously complex, and involves significant physical, social, and political interactions, large uncertainties, potentially serious environmental effects, and significant costs of management. Yet, policy makers must somehow cope with this complex array of issues and uncertainties to make policy decisions today. Unfortunately, two extreme views have emerged, one arguing that society should do nothing until the key uncertainties have been resolved, the other that it should do everything possible to avoid the potential catastrophic outcomes. Policy makers must move beyond these two views to make wise and informed choices from a wide array of alternatives.

The Policy Evaluation Framework (PEF) is a decision analysis tool that enables decision makers to continuously formulate policies that take into account the existing uncertainties, and to refine policies as new scientific information is developed. It is designed to provide a framework for integrating and evaluating the best available information from the diverse elements that influence climate policy. PEF encourages exploration of the policy implications of alternative technological, economic, physical, and biological assumptions and scenarios .

PEF integrates deterministic parametric models of physical, biological, and economic systems with a flexible decision tree system. The deterministic models represent greenhouse gas emissions, atmospheric accumulation of these gases, global and regional climate changes, ecosystem impacts, economic impacts, and mitigation and adaptation options. The decision tree system captures the key scientific and economic uncertainties, and reflects the wide range of possible outcomes of alternative policy actions. The framework contains considerable flexibility to allow a wide range of scientific and economic assumptions or scenarios to be represented and explored

A key feature of PEF is its capability to address both mitigation policies and investments in anticipatory adaptation to protect ecological and economic systems, as well as interactions among such options. PEF's time structure allows issues related to the timing and flexibility of alternatives to be evaluated, while the decision tree structure facilitates examining questions involving the value of information, contingent actions, and probabilistic representations .

This paper is intended to introduce PEF to the global climate policy community. The paper provides an overview of the structure, modules, and capabilities of PEF, and discusses selected results from an initial set of illustrative applications. Fuller descriptions of the PEF methodology and results can be found in the EPA's forthcoming Integrated Assessment of Global Climate Change [1] and The Global Climate Policy Evaluation Framework [2].

INTRODUCTION AND OVERVIEW

The U. S. Environmental Protection Agency and Decision Focus Incorporated developed the Global Climate Policy Evaluation Framework to provide decision makers with a tool to evaluate policy alternatives associated with global climate change, while explicitly recognizing and addressing the existence of considerable uncertainty and scientific debate surrounding climate issues. PEF is an integrated assessment tool that allows policy makers to consolidate information from multiple disciplines into a single framework. It has particular strengths that allow decision makers to address immediate policy issues, including investments in mitigation and anticipatory adaptation1 options, the timing of policy actions, the implications of climate change for ecological and economic systems, and the question of insuring against uncertain but potentially significant future damages.

PEF is designed to help investigate and answer questions such as:

• When should society act? What are the benefits of keeping options open?
• What are the interactions between mitigation and adaptation policies?
• Are additional actions justifiable as insurance against uncertain future climate changes?
• What are the policy implications of thresholds or irreversibilities in ecosystems or the economy?
• What are the top priorities for future research?

By addressing the uncertainties in physical, biological, and economic systems explicitly, PEF allows policy makers to move beyond the polarized debate in which some argue that society should delay action until the many scientific uncertainties have been resolved, while others argue that the potential outcomes are so catastrophic that society should do everything possible to mitigate climate change. PEF is an integrated model that combines mitigation, adaptation, emissions, climate, economic sectors, and ecosystem effects into a single framework. It is flexible enough to represent virtually any combination of policy options, scenarios, assumptions, and specifications of key relationships. It is efficient enough to evaluate numerous combinations of policy options and scenarios. Both its relationships and its capabilities will continue to evolve as new information becomes available, and new needs arise.

PEF's structure combines two components: (1) a deterministic model that describes the physical, biological, and economic impacts of greenhouse gas emissions; and (2) a decision tree system that organizes relevant information about the decisions and uncertainties. These components support the analytical tools that make it possible to evaluate policy alternatives under uncertainty. For a given set of assumptions, a specific physical and economic scenario, and a particular policy decision, the deterministic model calculates the resulting physical and economic impacts. The decision tree executes the deterministic model multiple times to evaluate the effect of various uncertainties and decisions.

The PEF framework may be divided into three levels:

• 1) the overall structure as a decision analysis tool with a decision tree and a deterministic model;
• 2) The specific equations used in the deterministic model in an application of the framework;
• 3) The numerical assumptions used as inputs in any specific set of analyses.

Both the deterministic model and the decision tree were designed with considerable flexibility to address a wide range of scenarios, options, and levels of detail, and to easily update relationships and assumptions in light of new information. The equations comprising the deterministic model are likely to evolve periodically as further research becomes available. The specific numerical assumptions can be changed readily to enable any set of assumptions and scenarios to be studied.

The scope of the framework includes both economic and ecosystem impacts, and both near-term and long-term adaptation and mitigation decisions. The near-term decisions are the primary focus of the model; the long-term decisions are included to provide a more realistic model of the consequences of near-term decisions, and to investigate the implications of the timing of actions.

DETERMINISTIC MODEL

PEF's deterministic model calculates the impacts of climate change given a set of policy alternatives and a single scenario for each input parameter. PEF provides the ability to disaggregate impacts by geographic region, economic sector and ecosystem type. The calculations within the deterministic model are divided into a series of modules:

• U. S. emissions
  
• Rest-of-world emissions
  
• Atmospheric processes and global climate
  
• Regional climate
  
• Economic impacts
  
• Ecosystem impacts.

Designing the deterministic model required tradeoffs between the detail of physical and economic representations and the simplicity needed for a practical analytical tool that can be used to rapidly evaluate an array of policy options and scenarios. This type of structure provides transparency, which also helps policy makers understand and interpret the results. For most processes, the model represents the physical relationships with parametric equations that can be calibrated to the results of larger, more detailed models. This approach provides the flexibility to represent many differing assumptions, opinions, or results. As PEF evolves, various relationships in the deterministic model will be updated to reflect new information.

The deterministic model uses reduced form models where it is appropriate to do so--that is, where the key aspects of the underlying phenomena are relatively well understood. The atmospheric process and global climate relationships, for example, use this approach. Where there is not yet a good understanding of the underlying processes, or where it is not reasonable to represent these processes with a reduced form model, the deterministic model uses structured functional forms. The economic impacts and ecosystem impacts relationships, for example, use this approach. All modules include enough parametric flexibility to represent, or to bound, any reasonable scenario. This capability allows sensitivity analyses to help prioritize refinements of the model. Each module is described below.

Mitigation and Adaptation Decisions

The current version of PEF includes first- and second-period mitigation and adaptation decisions. The model considers all combinations of alternatives. For example, selecting a first period mitigation alternative does not limit the range of first-period adaptation alternatives available, nor does it limit the range of second-period mitigation or adaptation alternatives available. Each period's decision may include up to six different mitigation and six adaptation alternatives.

An individual mitigation alternative includes the target reductions in U. S. and rest-of-world emissions over time for each greenhouse gas. The realized reductions, as a percentage of the target reductions, are specified separately for U. S. and rest-of-world emissions. Each alternative may also include the cost of the alternative, or the cost can be estimated using an endogenous model in PEF. Although PEF can estimate reductions in any greenhouse gas, the cost model currently estimates only the cost of carbon dioxide reductions. If an alternative scenario includes reductions in other gases, the cost of those reductions must be specified. This structure makes it possible to incorporate the cost and efficacy of mitigation from other models or studies.

A particular adaptation alternative includes four components: the dollar investment in economic adaptation by sector over time; the dollar investment in protecting ecosystems (ecosystem adaptation) by ecosystem type over time; the allocation of each sector's economic adaptation investment across the regions; and the allocation of each ecosystem type's adaptation investment across the regions. Adaptation alternatives may differ both in amount and timing of spending. In PEF, the cumulative investment, less depreciation, can reduce the impact of climate change on the economy and on ecosystems. The spending is expressed in annual rates of spending in billions of constant dollars. The parameters that describe the effect of adaptation on the impacts and the rate at which the adaptation investment depreciates are specified separately.

U. S. and Rest-of-world Emissions

Although they are distinct modules, the U. S. and rest-of-world emission modules are described together because their structures are identical. PEF can treat U. S. and rest-of-world emissions separately, or it can treat them together by including the U.S. emissions with the rest-of-world.

Given a particular mitigation alternative, with its associated emissions reductions, the emission modules estimate the annual emissions from U. S. and rest-of-world sources of each gas. Emissions are built up from the baseline emissions scenario, the target reduction due to mitigation, and a parameter representing the efficacy of mitigation.

PEF provides several alternatives in selecting the gases to include in an analysis. The model includes specialized atmospheric process relationships for carbon dioxide, methane, and nitrous oxide. Carbon dioxide can be modeled alone or with these other gases. Beyond these, PEF can include any other gases as well, such as CFCs or HCFCs, that fit into the standard relationships described below. The mitigation alternatives may address any of these gases.

Atmospheric Processes and Global Climate

The atmospheric processes and global climate module calculates the changes in global average temperature and average sea level from the emissions of greenhouse gases. In the most detailed analyses, the concentrations, equilibrium and realized temperatures, and sea level can be reported at each time increment.

The module uses the Maier-Reimer and Hasselmann model, as described by T. M. L. Wigley [3], for future carbon dioxide emissions, while it uses a single-sink decay model for past carbon dioxide emissions and for all emissions of other gases. The module uses the IPCC radiative forcing relationships [4] to calculate radiative forcing directly from the concentrations of greenhouse gases. Following the IPCC [4], it assumes a linear relationship between changes in radiative forcing and the equilibrium temperature. It uses a parametric model to describe the relationship between equilibrium and realized temperature, which treats each increase in equilibrium temperature as a pulse that becomes realized over time. A parametric model, based on STUGE [6], is used to calculate the change in global sea level.

Regional Climate

PEF's regional climate model calculates regional changes in temperature, precipitation, and runoff from the changes in global mean temperature. In addition, it provides the global changes in sea level and carbon dioxide concentration as inputs to the impact modules.

The choice of regional climate variables is driven by the requirements of the damage functions. The model can be easily expanded to meet the requirements of the economic damage functions and the ecosystem failure relationships (described below) as they evolve.

General circulation models still offer little insight into the nature of regional changes in temperature and precipitation, runoff, and soil moisture. PEF therefore provides flexible general relationships for regional changes, so that the sensitivity of analytical results to different assumptions about regional climate effects can be explored. The existing structure includes separate variables for each of the regional climate indicators to allow analyses of the influence of an individual indicator and the value of resolving its uncertainty.

Economic Impacts

This module calculates the monetary impact of climate change and the cost of policy actions from the adaptation and mitigation policies and from the regional climate indicators. The module calculates impacts by sector in each region, using up to fifteen sectors in up to ten regions, accounts for adaptation, and estimates the annual damages.

Economic impacts are those that would typically appear in GDP calculations or other monetized economic measures. In general, the economic impacts include effects on activities that take place within economic markets, or on goods that are exchanged on economic markets. The model also places a monetary value on the ecosystem impacts, wherever possible. These generally are effects that are not manifested in markets.

PEF allows spending on both ecosystem and economic adaptation to influence the economic impacts. Spending is accumulated into a stock of investment, which depreciates at a rate determined by an input variable. Adaptation spending targeted at ecosystems are also allowed to affect the economic sector through cross-effect parameters. The cross effects of ecosystem adaptation may increase or decrease the economic impacts. The savings due to economic adaptation are a function of both the adjusted stock of adaptation investment and the impacts before adaptation. Both the depreciation rates and the efficacy of adaptation may vary across sectors.

PEF assumes that the total impacts to a sector can be estimated by adding the impacts due to temperature change, precipitation change, and the other climate indicators. It could, however, be modified to include interaction terms between climate indicators. Damages may be estimated using any combination of linear functions, power functions of arbitrary power, logistic functions, and step functions. PEF uses a separate set of parameters for each combination of sector, region, and climate indicator.

The model does not address reactive adaptation explicitly. Instead, the damages in each sector are meant to represent the impacts of climate change, net of the impacts of reactive adaptation. Anticipatory adaptation may reduce damages either by reducing the sensitivity of an economic sector to climate change or by reducing the need for reactive adaptation with more effective anticipatory adaptation.

Ecosystem Impacts

Very few models exist to guide the initial development of the ecosystem impact module. As a result, PEF uses a simple model which is divided into three processes: estimating the fractional loss of each type of ecosystem by region; estimating the value per unit area lost by region and ecosystem type; and calculating the annual (monetized) impact by region and ecosystem type.

In estimating the fractional loss of ecosystems, the model assumes that changes in climate make some fraction of the ecosystem valueless. This could represent total failure of some fraction of land that had been populated by a particular type of ecosystem, or it could represent a partial loss of all of the land of that ecosystem type within the region.

Once the model has estimated a fractional loss, it then uses a valuation function to estimate the value per unit area by type and region. As with the economic impact module, any combination of linear, arbitrary power, logistic, and step functions can be used to estimate the ecosystem damages. This would allow, for example, the value per acre of a particular type in a given region to increase sharply as the ecosystem becomes scarce. Similar to the economic impacts module, adaptation investments may be made to reduce the amount of ecosystem damage. Ecosystem adaptation is modeled in the same way as economic adaptation, with a stock of investment, depreciation, efficacy of adaptation, and cross effects from economic sector investments.

In the final step, the model combines the area lost, the valuation per acre, and the level of economic and ecosystem adaptation into an annual impact, measured in dollars, of ecosystem or nonmonetary damages. This version of the model, while crude, can perform "what-ifs" analyses regarding non-market impacts to provide useful policy insights. Despite its simplistic nature, this model represents an improvement over those that ignore the potential non-market impacts of climate change.

Time Structure

The time horizon for an analysis, which is specified by the analyst, determines the beginning and end of the period for which impacts are calculated. Within this horizon, PEF's current structure contains two points at which decisions are made. The first set of decisions occurs at the beginning of the time horizon, while the second set may occur at any point within the time horizon. The beginning of each time period, the time step between calculations, and the end of the horizon are user-specified.

Relating this to the levels described in the overview, the use of two decision periods is part of level two and is embedded in PEF's relationships. As such, it could be changed, but not on a regular basis. The beginning and end of the horizon, and the length of the time step, are part of level three and thus can be changed from run to run.

DECISION TREE AND ANALYSIS CAPABILITIES

While the core mathematical relationships representing physical and economic processes are located in the deterministic model, linking the deterministic model with a decision tree enables a wide variety of analyses to be carried out. Policy evaluation can be thought of as two interrelated processes: comparing different alternate actions based on cost, effectiveness, impacts, etc., and determining the effect of important uncertainties on physical and economic impacts and on the choice of preferred policies. The decision tree facilitates both processes by selecting and executing appropriate runs of the deterministic model, compiling the results, and presenting the information concisely.

PEF provides a range of built-in analyses, which can be subdivided into deterministic and probabilistic analyses. Deterministic analyses investigate the preferred policy options under various climate and impact scenarios. Probabilistic analyses use the likelihoods of different outcomes to evaluate appropriate options under conditions of uncertainty.

ILLUSTRATIVE RESULTS

This section describes some illustrative results derived using PEF, based on a set of assumptions that treats the U. S. in aggregate, with a single geographic region, economic sector and ecosystem type. While disaggregated analyses are underway, these preliminary analyses illustrate some insights that PEF can provide. More detailed analyses and insights drawn from PEF are described in the EPA's forthcoming Integrated Assessment of Global Climate Change [1].

How Do Mitigation and Adaptation Strategies Depend on Uncertainties?

The most basic issue that PEF can address is the relationship between uncertainties and the preferred levels of mitigation and adaptation. An interesting question regards how preferred strategies change under various climate scenarios. (The temperature lag describes the rate at which increases in equilibrium temperature become observable.) At this point, the value of the analyses is not primarily in determining a single correct policy to implement, but rather in evaluating the potential effects of uncertainties on appropriate decisions. Uncertainty in the climate scenario, by itself, affects the preferred level of action: as the climate scenario becomes worse (more rapid change), more action is warranted.

The preferred alternatives are also strongly sensitive to the impacts scenarios.(The scenarios are defined by the impacts, as a percentage of gross domestic product, that result from a 2. 5°C increase in realized temperature.) Although these results are preliminary, they suggest that uncertainties in the impacts resulting from a given level of climate change may be as important to policy decisions as the uncertainty in the extent of climate change itself.

How Do Mitigation and Adaptation Strategies Interact?

In addition to investigating the sensitivity of policies to uncertainties, PEF can provide insights into the interaction between policies. The preferred level of mitigation is sensitive to the preferred level of investment in adaptation, but the preferred level of adaptation is less sensitive to the preferred level of mitigation.

Because mitigation and adaptation work through different mechanisms, they interact asymmetrically. Whereas investment in adaptation are directly targeted at the impacts, investments in mitigation reduce impacts indirectly through changes in the climate. Therefore, while potentially more expensive, adaptation could have larger effects on impacts more quickly. Thus, mitigation becomes less cost-effective when high levels of adaptation investment reduce the impacts, while adaptation is still effective in the presence of high levels of mitigation,

What are the Implications of Thresholds?

Physical, biological, or economic systems may exhibit threshold behavior, experiencing sharp changes in response as driving factors cross thresholds. This could happen, for example, as species become extinct, or as increases in sea level overwhelm coastal defenses.

Date suggest that the preferred reduction in emissions is more sensitive to the time at which the threshold occurs than to the magnitude of the impacts.

CONCLUSIONS

The Policy Evaluation Framework provides a flexible and powerful tool for policy makers. PEF's design evolved from a set of questions that are at the heart of global climate policy debate. PEF addresses all facets of the climate issue that must be considered to answer these policy questions, using the best available scientific and socioeconomic information. PEF is even flexible enough to address "what if" questions to explore different assumptions about aspects of climate change where limited information exists.

PEF has been used to investigate the relationships between the key uncertainties and the available policy alternatives. Nothing hinders the adaptability of the model to new information in science or economics. Further efforts will focus on refining the assumptions and scenarios used, especially in developing sectorally disaggregated impact functions.

ACKNOWLEDGMENTS

David Wilson of Stanford University, Nathan Chan, David Gess, Tricia Jimenez, Binna Kim, Mia Morsy, and Elisabeth Moyer at Decision Focus Incorporated, and Frances Sussman at ICF Incorporated made valuable contributions to this effort. This work was funded in part by the EPA under contract number 68-W2-0018.

DISCLAIMER

The views expressed in this paper are the authors' own and do not represent official EPA policy.

Forthcoming in Proceedings of the 1994 A&WMA Global
Climate Change Conference: Phoenix April 5-8. Air &
Waste Management Association: Pittsburgh 1994

1 Adaptation is defined as actions taken to protect ecological or economic systems from climate change. It is divided into anticipatory adaptation, spending in advance of observed climate change, and reactive adaptation, spending in response to climate change. Anticipatory adaptation may reduce damages either by directly reducing the sensitivity of ecological or economic system to climate change, or by replacing reactive adaptation with more effective anticipatory adaptation

REFERENCES

1. Integrated Assessment of Global Climate Change. Joel D. Scheraga, ed.; United States Environmental Protection Agency, forthcoming.

2. Chan, Nathan Y. et al.; The Global Climate Policy Evaluation Framework: A technical report prepared by Decision Focus Incorporated for the United States Environmental Protection Agency, forthcoming.

3. Wigley, T. M. L. "A Simple Inverse Carbon Cycle Model," Global Biogeochemical Cycles, December 1991.

4. Climate Change: The IPCC Scientificc Assessment; Houghton, J. T.; Jenkins, G. J.; and Ephraums, J. J. eds.; Cambridge University Press, Cambridge: 1990.

5. Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment; Houghton, J. T., Callander, B. A., and Vainey, S. K., eds.; Cambridge University Press, 1992.

6. Wigley, T.M.L.; Holt, T.; and Raper, S. C. B. STUGE: an Interactive Greenhouse Model. Climatic Research Unit, University of East Anglia, Norwich, U.K., Oct. 1991.

 

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