Mitigation Portfolio and Policy Instruments When Hedging Against Climate Policy and Technology Uncertainty

In this paper, we use a stochastic integrated assessment model to evaluate the effects of uncertainty about future carbon taxes and the costs of low-carbon power technologies. We assess the implications of such ambiguity on the mitigation portfolio under a variety of assumptions and evaluate the role of emission performance standards and renewable portfolios in accompanying a market-based climate policy. Results suggest that climate policy and technology uncertainties are important with varying effects on all abatement options. The effect varies with the technology, the type of uncertainty, and the level of risk. We show that carbon price uncertainty does not substantially change the level of abatement, but it does have an influence on the mitigation portfolio, reducing in particular energy R&D investments in advanced technologies. When investment costs are uncertain, investments are discouraged, especially during the early stages, but the effect is mitigated for the technologies with technological learning prospects. Overall, these insights support some level of regulation to encourage investments in coal equipped with carbon capture and storage and clean energy R&D.     

Uncertainty in Integrated Assessment Models of Climate Change: Alternative Analytical Approaches

Uncertainty plays a key role in the economics of climate change, and research on this topic has led to a substantial body of literature. However, the discussion on the policy implications of uncertainty is still far from being settled, partly because the uncertainty of climate change comes from a variety of sources and takes diverse forms. To reflect the multifaceted nature of climate change uncertainty better, an increasing number of analytical approaches have been used in the studies of integrated assessment models of climate change. The employed approaches could be seen as complements rather than as substitutes, each of which possesses distinctive strength for addressing a particular type of problems. We review these approaches—specifically, the non-recursive stochastic programming, the real option analysis, and the stochastic dynamic programming—their corresponding literatures and their respective policy implications. We also identify the current research gaps associated with the need for further developments of new analytical approaches.     

Integrated Assessment Modeling for Global Climate Change: An Infinite Horizon Optimization Viewpoint

In this paper one uses an infinite time horizon optimal control paradigm to deal with three important issues in global climate change integrated assessment, namely the equitable treatment of all the generations involved, the representation of technical progress, and the uncertainty concerning technological progress and climate change processes. The notion of economic sustainability is associated with the concept of turnpike in infinite horizon optimization models. The issue of deciding on the proper discount rate is addressed in this context and a method is proposed to reconcile long term sustainability and short term time preference for current generations. One also formulates a model where environmental damage and/or technical progress are represented as stochastic jump processes. One calls this random evolution a mode switching process. In this context, sustainability is represented by a family of turnpikes, and the economy will be driven from one steady state to the other as the modes switch. These concepts are illustrated on the DICE model and their possible implementation in other types of integrated assessment models is discussed.     

The Contribution of Mathematical Models to Climate Policy Design: a Researcher’s Perspective

Energy and the environment are closely interconnected. In particular, energy-related carbon dioxide emissions are major contributors to climate change. To analyze options within the energy sector to curb greenhouse gas emissions, or to study alternative climate strategies such as adaptation and geoengineering measures, policy-makers can rely on mathematical decision support models, in particular E3 (economy/energy/environment) models and integrated assessment models (IAMs). This paper reviews some of my recent contributions to climate policy design using different types of E3 models and IAMs.     

A Long-Term Electricity Dispatch Model with the TIMES Framework

A new Swiss TIMES (The Integrated MARKAL–EFOM System) electricity model with an hourly representation of inter-temporal detail and a century-long model horizon has been developed to explore the TIMES framework’s suitability as a long-term electricity dispatch model. To understand the incremental insights from this hourly model, it is compared to an aggregated model with only two diurnal timeslices like in most MARKAL/TIMES models. Two scenarios have been analysed with both models to answer the following questions: Are there differences in model solutions? What are the benefits of having a high number of timeslices? Are there any computational limitations? The primary objective of this paper is to understand the differences between the solutions of the two models, rather than Swiss policy implication or potential uncertainties in input parameters and assumptions. The analysis reveals that the hourly model offers powerful insights into the electricity generation schedule. Nevertheless, the TIMES framework cannot substitute for a dispatch model because some features cannot be represented; however, the long model time horizon and integrated system approaches of TIMES provide features not available in conventional dispatch models. The methodology of the model development and insights from the model comparison are described.     

Determining the global significance of local and regional mitigation strategies: Setting the scene with global integrated assessment models

Because of the importance and complexity of the processes involved in the response of land cover and land use to changing environmental conditions, other approaches are required to evaluate the effectiveness of mitigation options. One such approach is provided by the global integrated assessment model, IMAGE 2. This article presents the structure and some of the underlying assumptions of IMAGE 2, which illustrates the importance of feedback processes in evaluating the effectiveness of mitigation options with respect to land use. Although models such as IMAGE 2 are unsuitable for local and national mitigation evaluations, they can be used to define the regional and global constraints of the smaller scale assessments.     

Exploring the use of computer models in participatory integrated assessment – experiences and recommendations for further steps

Integrated assessment (IA) can be defined as a structured process of dealing with complex issues, using knowledge from various scientific disciplines and/or stakeholders, such that integrated insights are made available to decision makers (J. Rotmans, Enviromental Modelling and Assessment 3 (1998) 155). There is a growing recognition that the participation of stakeholders is a vital element of IA. However, only little is known about methodological requirements for such participatory IA and possible insights to be gained from these approaches. This paper summarizes some of the experiences gathered in the ULYSSES project, which aims at developing procedures that are able to bridge the gap between environmental science and democratic policy making for the issue of climate change. The discussion is based on a total of 52 IA focus groups with citizens, run in six European and one US city. In these groups, different computer models were used, ranging from complex and dynamic global models to simple accounting tools. The analysis in this paper focuses on the role of the computer models. The findings suggest that the computer models were successful at conveying to participants the temporal and spatial scale of climate change, the complexity of the system and the uncertainties in our understanding of it. However, most participants felt that the computer models were less instrumental for the exploration of policy options. Furthermore, both research teams and participants agreed that despite considerable efforts, most models were not sufficiently user-friendly and transparent for being accessed in an IA focus group. With that background, some methodological conclusions are drawn about the inclusion of the computer models in the deliberation process. Furthermore, some suggestions are made about how given models should be adapted and new ones developed in order to be helpful for participatory IA. This revised version was published online in July 2006 with corrections to the Cover Date.     

INASUD project findings on integrated assessment of climate policies

This communication summarizes the main findings of INASUD, an European-wide research project on integrated assessment of climate policies. The project aimed at improving the framing of climate policy analysis through the parallel use of various existing integrated assessment models. It provides a comprehensive examination of the link between uncertainty regarding damages and inertia in economic systems. Results show that the Kyoto targets and timing are consistent with the precautionary principle but offers little insurance for longer-term climate protection. Flexibility mechanisms offer potentials for cooperation with developing countries, and are necessary to tap the environmental and economic benefits of joint carbon and sulfur emissions abatement.     

A critical comparison of ten disposable cup LCAs

Disposable cups can be made from conventional petro-plastics, bioplastics, or paperboard (coated with petro-plastics or bioplastics). This study compared ten life cycle assessment (LCA) studies of disposable cups with the aim to evaluate the robustness of their results. The selected studies have only one impact category in common, namely climate change with global warming potential (GWP) as its category indicator. Quantitative GWP results of the studies were closer examined. GWPs within and across each study show none of the cup materials to be consistently better than the others. Comparison of the absolute GWPs (after correction for the cup volume) also shows no consistent better or worse cup material. An evaluation of the methodological choices and the data sets used in the studies revealed their influence on the GWP. The differences in GWP can be attributed to a multitude of factors, i.e., cup material and weight, production processes, waste processes, allocation options, and data used. These factors basically represent different types of uncertainty. Sensitivity and scenario analyses provided only the influence of one factor at once. A systematic and simultaneous use of sensitivity and scenario analyses could, in a next research, result in more robust outcomes.     

Issues in modeling induced technological change in energy, environmental, and climate policy

This paper addresses the objective of including Induced Technological Change (ITC) in research and policy models of energy, environment, and climate change. Theoretical foundations, fundamentals, and current methodologies for ITC models are reviewed. In addition, limitations and possible extensions to ITC models are explored. Current approaches to energy-environmental modeling that neglect technological characteristics such as heterogeneity, uncertainty, and path-dependence are likely to underestimate both the impact and the lags in the effectiveness of policy options.     

The Benefits of Cooperation Under Uncertainty: the Case of Climate Change

This article presents an analysis of the behaviour of countries defining their climate policies in an uncertain context. The analysis is made using the S-CWS model, a stochastic version of an integrated assessment growth model. The model includes a stochastic definition of the climate sensitivity parameter. We show that the impact of uncertainty on policy design critically depends on the shape of the damage function. We also examine the benefits of cooperation in the context of uncertainty: We highlight the existence of an additional benefit of cooperation, namely risk reduction.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.     

Integrated assessment modeling of global climate change: Transparent rational tool for policy making or opaque screen hiding value‐laden assumptions?

One of the principal tools used in the integrated assessment (IA) of environmental science, technology and policy problems is integrated assessment models (IAMs). These models are often comprised of many sub‐models adopted from a wide range of disciplines. A multi‐disciplinary tool kit is presented, from which three decades of IA of global climatic change issues have tapped. A distinction between multi‐ and inter‐disciplinarity is suggested, hinging on the synergistic value added for the latter. Then, a hierarchy of five generations of IAMs are proposed, roughly paralleling the development of IAMs as they incorporated more components of the coupled physical, biological and social scientific disciplines needed to address a “real world” problem like climatic change impacts and policy responses. The need for validation protocols and exploration of predictability limits is also emphasized. The critical importance of making value‐laden assumptions highly transparent in both natural and social scientific components of IAMs is stressed, and it is suggested that incorporating decision‐makers and other citizens into the early design of IAMs can help with this process. The latter could also help IA modelers to offer a large range of value‐containing options via menu driven designs. Examples of specific topics which are often not well understood by potential users of IAMs are briefly surveyed, and it is argued that if the assumptions and values embedded in such topics are not made explicit to users, then IAMs, rather than helping to provide us with refined insights, could well hide value‐laden assumptions or conditions. In particular, issues of induced technological change, timing of carbon abatement, transients, surprises, adaptation, subjective probability assessment and the use of contemporary spatial variations as a substitute for time evolving changes (what I label “ergodic economics”) are given as examples of problematic issues that IA modelers need to explicitly address and make transparent if IAMs are to enlighten more than they conceal. A checklist of six practices which might help to increase transparency of IAMs is offered in the conclusions. Incorporation of decision‐makers into all stages of development and use of IAMs is re‐emphasized as one safeguard against misunderstanding or misrepresentation of IAM results by lay audiences.     

Mind the gap in SEA: An institutional perspective on why assessment of synergies amongst climate change mitigation, adaptation and other policy areas are missing

This article takes its point of departure in two approaches to integrating climate change into Strategic Environmental Assessment (SEA): Mitigation and adaptation, and in the fact that these, as well as the synergies between them and other policy areas, are needed as part of an integrated assessment and policy response. First, the article makes a review of how positive and negative synergies between a) climate change mitigation and adaptation and b) climate change and other environmental concerns are integrated into Danish SEA practice. Then, the article discusses the implications of not addressing synergies. Finally, the article explores institutional explanations as to why synergies are not addressed in SEA practice. A document analysis of 149 Danish SEA reports shows that only one report comprises the assessment of synergies between mitigation and adaptation, whilst 9,4% of the reports assess the synergies between climate change and other environmental concerns. The consequences of separation are both the risk of trade-offs and missed opportunities for enhancing positive synergies. In order to propose explanations for the lacking integration, the institutional background is analysed and discussed, mainly based on Scott's theory of institutions. The institutional analysis highlights a regulatory element, since the assessment of climate change synergies is underpinned by legislation, but not by guidance. This means that great focus is on normative elements such as the local interpretation of legislation and of climate change mitigation and adaptation. The analysis also focuses on how the fragmentation of the organisation in which climate change and SEA are embedded has bearings on both normative and cultural-cognitive elements. This makes the assessment of synergies challenging. The evidence gathered and presented in the article points to a need for developing the SEA process and methodology in Denmark with the aim to include climate change in the assessments in a more systematic and integrated manner.     

On the representation of impact in integrated assessment models of climate change

The paper provides an overview of attempts to represent climate change impact in over twenty integrated assessment models (IAMs) of climate change. Focusing on policy optimization IAMs, the paper critically compares modeling solutions, discusses alternatives and outlines important areas for improvement. Perhaps the most crucial area of improvement concerns the dynamic representation of impact, where more credible functional forms need to be developed to express time‐dependent damage as a function of changing socio‐economic circumstances, vulnerability, degree of adaptation, and the speed as well as the absolute level of climate change.     

Modelling Equity: A Debate About Values

This paper discusses equity issues in relation to climate change. Models of long-term climate assessments study changes in relative prices. These changes lead to gains and losses for different economic actors and these consequences are held responsible for problems related to social acceptability. Policy recommendations issued by such models cannot be put into practice. Equity should be integrated into those models in order to make them more relevant for policy. This paper considers this problem in three parts.The first part shows that equity is only one aspect of the social dimension of sustainable development, which cannot be treated separately. It invites an understanding of complexity. Equity is also interrelated with the economic and ecological dimensions of sustainable development.The second part deals with the fact that different aspects of equity have to be taken into account and several concepts of equity co-exist. If only distribution of income is taken into account, equity can effectively be addressed through economic growth, but the specific characteristics of sustainable development are left out of the analysis.Therefore, the third part is a questioning of traditional modelling approaches and of the reasons why modelling should be carried out. The paper concludes with a short discussion about the normative content of any attempt to model climate change.     

The Effect of Green Investments in an Agent-Based Climate-Economic Model

Climate-economic modeling often relies on macroeconomic integrated assessment models (IAMs) that in general try to capture how the combined system reacts to different policies. Irrespective of the specific modeling approach, IAMs suffer from two notable problems. First, although policies and emissions are dependent on individual or institutional behavior, the models are not able to account for the heterogeneity and adaptive behavior of relevant actors. Second, the models unanimously consider mitigation actions as costs instead of investments: an arguable definition, given that all other expenditures are classified as investments. Both are challenging if the long-term development of climate change and the economy shall be analyzed. This paper therefore proposes a dynamic agent-based model, based on the battle of perspectives approach (Janssen [1]; Janssen and de Vries [2]; Geisendorf [3, 4]) that details the consequences of various behavioral assumptions. Furthermore, expenditures for climate protection, e.g., the transition of the energy system to renewables, are regarded as investments in future technologies with promising growth rates and the potential to incite further growth in adjoining sectors (Jaeger et al. [5]). The paper analyzes how a different understanding of climate protection expenditures changes the system’s dynamic and, thus, the basis for climate policy decisions. The paper also demonstrates how erroneous perceptions impact on economic and climate development, underlining the importance to acknowledge heterogeneous beliefs and behavior for the success of climate policy.     

Correcting the carbon cycle representation: How important is it for the economics of climate change?

Economic analyses of the greenhouse effect are typically carried out within the framework of computable general equilibrium models which represent the climate system by simple two box proxies based upon the pioneering work of Nordhaus. Since errors in predicting the carbon budget can imply high costs, there is some need to include more sophisticated climate models into the economics of global climate change. This paper presents a non-linear pulse representation of the process-based and data-validated Bern carbon model. Compared to the Nordhaus approach this leads to different results with respect to optimal climate policy and atmospheric carbon dioxide concentration. In particular, our results suggest that economic studies which use a Nordhaus representation of the climate system are biased towards high carbon emission and low abatement levels.     

Models at the interface between science and society: impacts and options

Within the CLEAR project a new approach to integrated assessment modelling has been developed for the participatory integrated assessment of regional climate change involving citizens' focus groups. The climate change decision problem was structured by focusing separately on climate impacts and mitigation options. The attempt was made to link the different scales of the problem from the individual to the global level. The abstract topic of climate change was related to options on the level of a citizen's individual lifestyle. The option of a low energy society was emphasised in order to embed the climate change decision problem in a wider range of societal concerns. Special emphasis was given to the characterisation and communication of uncertainties. The chosen approach allows different kinds of uncertainties in one framework to be addressed. The paper concludes with a summary of the experience made, and recommendations for the use of models in participatory integrated assessments. This revised version was published online in July 2006 with corrections to the Cover Date.