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.     

Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in a stochastic programming version to provide a hedging emission policy to cope with the uncertainty characterizing climate sensitivity. The TD model we use is the computable general equilibrium model GEMINI-E3. Through Monte Carlo simulations of randomly generated uncertain parameter values, one provides a stochastic micro- and macro-economic analysis. Through statistical analysis of the simulation results, we analyse the impact of the uncertainties on the policy assessment.     

Approaches for performing uncertainty analysis in large-scale energy/economic policy models

A number of key policy insights have emerged from the application of large-scale economic/energy models, such as integrated assessment models for climate change. These insights have been particularly powerful in those instances when they are shared by all or most of the existing models. On the other hand, some results and policy recommendations obtained from integrated assessment models vary widely from model to model. This can limit their usability for policy analysis. The differences between model results are mostly due to different underlying assumptions about exogenous processes, about endogenous processes and the dynamics among them, differences in value judgments, and different approaches for simplifying model structure for computational purposes. Uncertainty analyses should be performed for the dual purpose of clarifying the uncertainties inherent in model results and improving decision making under uncertainty. This paper develops a unifying framework for comparing the different types of uncertainty analyses through their objective functions, categorizes types of uncertainty analyses that can be performed on large models, and compares different approaches to uncertainty analysis by explaining underlying assumptions, suitability for different model types, and advantages and disadvantages. The appendix presents a summary of integrated assessment models for climate change that explicitly account for uncertainty.     

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Economic development, variation in weather patterns and natural disasters focus attention on the management of water resources. This paper reviews the literature on the development of mathematical programming models for water resource management under uncertainty between 2010 and 2017. A systematic search of the academic literature identified 448 journal articles on water resource management for examination. Bibliometric analysis is employed to investigate the methods that researchers are currently using to address this problem and to identify recent trends in research in the area. The research reveals that stochastic dynamic programming and multistage stochastic programming are the methods most commonly applied. Water resource allocation, climate change, water quality and agricultural irrigation are amongst the most frequently discussed topics in the literature. A more detailed examination of the literature on each of these topics is included. The findings suggest that there is a need for mathematical programming models of large-scale water systems that deal with uncertainty and multiobjectives in an effective and computationally efficient way.     

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.     

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.     

Uncertainty and economic analysis of climate change: A survey of approaches and findings

The analysis of climate change is confronted with large uncertainties that need to be taken into account to arrive at meaningful policy recommendations. The main contribution of economics to this interdisciplinary task is to provide formal frameworks and techniques for analyzing climate policy in the context of uncertainty. This paper will give an overview of existing approaches and findings to provide a broad picture of what economics can contribute to the debate.     

The Impact of Uncertainty in Climate Targets and CO2 Storage Availability on Long-Term Emissions Abatement

A major characteristic of our global interactive climate-energy system is the large uncertainty that exists with respect to both future environmental requirements and the means available for fulfilling these. Potentially, a key technology for leading the transition from the current fossil fuel-dominated energy system to a more sustainable one is carbon dioxide capture and storage. Uncertainties exist, however, concerning the large-scale implementability of this technology, such as related to the regional availability of storage sites for the captured CO₂. We analyze these uncertainties from an integrated assessment perspective by using the bottom-up model TIAM-ECN and by studying a set of scenarios that cover a range of different climate targets and technology futures. Our study consists of two main approaches: (1) a sensitivity analysis through the investigation of a number of scenarios under perfect foresight decision making and (2) a stochastic programming exercise that allows for simultaneously considering a set of potential future states-of-the-world. We find that, if a stringent climate (forcing) target is a possibility, it dominates the solution: if deep CO₂ emission reductions are not started as soon as possible, the target may become unreachable. Attaining a stringent climate target comes in any case at a disproportionally high price, which indicates that adaptation measures or climate damages might be preferable to the high mitigation costs such a target implies.     

Agent-based integrated assessment modelling: the example of climate change

Current approaches to deal with the socio-economic implications of climate change rely heavily on economic models that compare costs and benefits of different measures. We show that the theoretical foundations underpinning current approaches to economic modelling of climate change are inappropriate for the type of questions that are being asked. We argue therefore that another tradition of modelling, social simulation, is more appropriate in dealing with the complex environmental problems we face today.     

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.     

Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU

Investments in power generation constitute a typical budget allocation problem in the context of multiple objectives, while all factors influencing investor’s decisions for power plants are subject to considerable uncertainties. The paper introduces a multi-objective stochastic model designed to optimize budget allocation decisions for power generation in the context of risk aversion taking into account several sources of uncertainty, especially with regard to volatility of fossil fuel and electricity prices, technological costs, and climate policy variability. Probability distributions for uncertain factors influencing investment decisions are directly derived from the stochastic global energy model PROMETHEUS and thus they take into account complex interactions between variables in the systemic context. In order to fully incorporate stochastic characteristics of the problem, the model is specified as an optimization problem in which the probability that an objective exceeds a given threshold is maximized (risk aversion) subject to a set of deterministic and probabilistic constraints. The model is formulated as a mixed integer program providing complete flexibility on the joint distributions of rates of return of technologies competing for investments, as it can handle non-symmetric distributions and take automatically into account complex covariance patterns as emerging from comprehensive PROMETHEUS stochastic results. The analysis shows that risk is a crucial factor for power generation investments with investors not opting for technologies subject to uncertainty related to climate policies and fossil fuel prices. On the other hand, combination of options with negative covariance tends to benefit in the context of risk-hedging behavior.     

The Kyoto Protocol and non-CO2 Greenhouse Gases and Carbon Sinks

Many trace constituents other than carbon dioxide affect the radiative budget of the atmosphere. The existing international agreement to limit greenhouse gases, the Kyoto Protocol, includes carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF₆) and credit for some carbon sinks. We investigate technological options for reducing emissions of these gases and the economic implications of including other greenhouse gases and sinks in the climate change control policy. We conduct an integreated assessment of costs using the MIT Emissions Prediction and Policy Analysis (EPPA) model combined with estimates of abatement costs for non-CO₂ greenhouse gases and sinks. We find that failure to take advantage of the other gas and sink flexibility would nearly double aggregate Annex B costs. Including all the GHGs and sinks is actually cheaper than if only CO₂ had been included in the Protocol and their inclusion achieves greater overall abatement. There remains considerable uncertainty in these estimates, the magnitude of the savings depends heavily on reference projections of emissions, for example, but these uncertainties do not change the overall conclusion that non-CO₂ GHGs are an important part of a climate control policy.     

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.     

Behavioural determinants of an individual's intention to adapt to climate change: Both internal and external perspectives

Climate change has had a significant negative impact on socio-economic factors and the earth's ecology. To cope with climate change, many countries have employed various policies and measures to reduce damage due to climate change. For individual residents, adaptation behaviour is vital for reducing individual welfare losses. This research analysed how psychological determinants and other external factors influence residents' intention to adapt to climate change. We proposed an extended protection motivation theory (PMT) model, developed a reliable scale and conducted a nationwide field survey. We interviewed 1402 residents in 29 provinces, and 874 valid questionnaires were collected, providing data that were used in a structural equation model. The results show that our model can serve as a reliable framework for analysing the determinants of residents' intention to adapt to climate change. Policy is the most important factor for stimulating the formation of residents' adaptation intention. Risk appraisals and adaptation appraisals have positive and significant impacts on the intention of residents to adopt climate change adaptation behaviour. Information and climate perception do not directly influence residents' behavioural intentions but indirectly affect their intentions through the process of risk appraisal and adaptation appraisal. Corresponding policy suggestions are made that may be helpful for the formulation of adaptation policies.     

Optimal Control Models and Elicitation of Attitudes towards Climate Damages

This paper examines the consequences of various attitudes towards climate damages through a family of stochastic optimal control models (RESPONSE): cost-efficiency for a given temperature ceiling; cost-benefit analysis with a pure preference for current climate regime and full cost-benefit analysis. The choice of a given proxy of climate change risks is actually more than a technical option. It is essentially motivated by the degree of distrust regarding the legitimacy of an assessment of climate damages and the possibility of providing in due time reliable and non controversial estimates. Our results demonstrate that (a) for early decades abatement, the difference between various decision-making frameworks appears to matter less than the difference between stochastic and non stochastic approach given the cascade of uncertainty from emissions to damages; (b) in a stochastic approach, the possibility of non-catastrophic singularities in the damage function is sufficient to significantly increase earlier optimal abatements; (c) a window of opportunity for action exists up to 2040: abatements further delayed may induce significant regret in case of bad news about climate response or singularities in damages.     

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.     

An approach to deal with uncertainty in energy and environmental planning: the MARKAL case

This paper presents a new concept to include uncertainty management in energy and environmental planning models developed in algebraic modeling languages. SETSTOCH is a tool for linking algebraic modeling languages with specialized stochastic programming solvers. Its main role is to retrieve from the modeling language a dynamically ordered core model (baseline scenario) that is sent automatically to the stochastic solver. The case presented herein concerns such a study realized with the IEAMARKAL model used by many research teams around the world.     

The Biodiversity Crisis and Adaptation to Climate Change: A Case Study from Australia's Forests

If current trends continue, human activities will drastically alter most of the planet's remaining natural ecosystems and their composite biota within a few decades. Compounding the impacts on biodiversity from deleterious management practices is climate variability and change. The Intergovernmental Panel on Climate Change (IPCC) recently concluded that there is ample evidence to suggest climate change is likely to result in significant impacts on biological diversity. These impacts are likely to be exacerbated by the secondary effects of climate change such as changes in the occurrence of wildfire, insect outbreaks and similar disturbances. Current changes in climate are very different from those of the past due to their rate and magnitude, the direct effects of increased atmospheric CO₂ concentrations and because highly modified landscapes and an array of threatening processes limit the ability of terrestrial ecosystems and species to respond to changed conditions. One of the primary human adaptation option for conserving biodiversity is considered to be changes in management. The complex and overarching nature of climate change issues emphasises the need for greatly enhanced cooperation between scientists, policy makers, industry and the community to better understand key interactions and identify options for adaptation. A key challenge is to identify opportunities that facilitate sustainable development by making use of existing technologies and developing policies that enhance the resilience of climate-sensitive sectors. Measures to enhance the resilience of biodiversity must be considered in all of these activities if many ecosystem services essential to humanity are to be sustained. New institutional arrangements appear necessary at the regional and national level to ensure that policy initiatives and research directed at assessing and mitigating the vulnerability of biodiversity to climate change are complementary and undertaken strategically and cost-effectively. Policy implementation at the national level to meet responsibilities arising from the UNFCCC (e.g., the Kyoto Protocol) and the UN Convention on Biological Diversity require greater coordination and integration between economic sectors, since many primary drivers of biodiversity loss and vulnerability are influenced at this level. A case study from the Australian continent is used to illustrate several key issues and discuss a basis for reform, including recommendations for facilitating adaptation to climate variability and change.     

A General Equilibrium Assessment of Climate Change Impacts on Swiss Winter Tourism with Adaptation

Winter alpine tourism has been repeatedly identified as one of the economic sectors most at risk from climate change in Switzerland. However, all of the costs that have been estimated so far for the Swiss tourism sector are, to some extent, misleading as they do not, or only partially, incorporate adaptation possibilities and general equilibrium effects. We attempt to fill this gap using a computable general equilibrium model that is specifically designed for the purposes of this research. Our modeling efforts first consist in creating a tourism sector with a part of it being dependent on snow. We also carefully model the snowmaking technology. Using climate change scenarios on future snow cover, we analyze their impacts on the Swiss ski industry. We find welfare effects for the Swiss economy ranging from − 23 to 113 million CHF in 2050. This range arises from the use of various assumptions concerning adaptation possibilities. We also show that geographical substitutions between international ski destinations have large positive effects for Switzerland. From a more general perspective, our results exemplify the risks of estimating the consequences of climate change based only on domestic impacts of climate change with no adaptation being implemented.

     

Cost-Benefit Analysis and the environment: The time horizon is of the essence

Cost-Benefit Analysis is a key tool for evaluating welfare gains or losses from an investment. It is now well established that environmental impacts are crucial to consider the full welfare implications of a project. Debate has focussed on approaches to improve the valuation of environmental impacts, and controversy in the discounting of future impacts to present values. The issue of the time horizon of analysis is frequently overlooked. The framing of the time horizon has major implications, as environmental costs and benefits often accrue in the long-term. The technical aspects of setting the time horizon are reviewed, along with updates to practice guidance, noting the longer time horizons now becoming typical. It is demonstrated that the time horizon can have a considerable impact on results, even more substantial than the discount rate. While uncertainty is noted as a technical challenge to longer-term analysis, the use of scenarios and sensitivity testing are noted as an appropriate response. For projects with long-term environmental effects, such as those related to air pollution, climate change and ecosystem damages, it is recommended to use timescales of 100+ years for economic evaluation of the impact. Failing to fully capture these long-term welfare gains and losses will distort analysis with a bias towards those projects that are more carbon-intensive, or environmentally damaging. Such a bias would undermine not only the evaluation, but welfare and sustainable development in general.