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.     

Climate impact on social systems: the risk assessment approach

A novel approach to the problem of estimating climate impact on social systems is suggested. This approach is based on a risk concept, where the notion of critical events is introduced and the probability of such events is estimated. The estimation considers both the inherent stochasticity of climatic processes and the artificial stochasticity of climate predictions due to scientific uncertainties. The method is worked out in some detail for the regional problem of crop production and the risks associated with global climate change, and illustrated by a case study (Kursk region of the FSU). In order to get local climatic characteristics (weather), a so-called statistical weather generator is used. One interesting finding is that the 3% risk level remains constant up to 1.0–1.1°C rise of mean seasonal temperature, if the variance does not change. On the other hand, the risk grows rapidly with increasing variance (even if the mean temperature rises very slowly). The risk approach is able to separate two problems: (i) assessment of global change impact, and (ii) decision making. The main task for the scientific community is to provide the politicians with different options; the choice of admissible (from the social point of view) critical events and the corresponding risk levels is the business of decision makers.     

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.     

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.     

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.     

Participatory integrated assessment of adaptation to climate change in Alpine tourism and mountain agriculture

Winter tourism and mountain agriculture are the most important economic sectors in a major part of the Swiss Alps. Both are highly sensitive to changing climatic conditions. In the framework of the CLEAR project, results from climate impact research in the field of tourism and agricultural production were used to investigate the perception of climatic change by stakeholders and to assess possible adaptations. We used a participatory integrated assessment (PIA) to involve the knowledge, values and experiences of the various social actors in tourism and agriculture (e.g., skiers, tourism managers, farmers) in the research process. Whereas climate change may have various severe direct impacts on the tourism industry, depending on the region, agricultural production may generally benefit from changed climatic conditions. But because of the dependence of farmers on “off-farm” income, the loss due to declining winter tourism in specific areas may cause more important indirect effects. However, the two sectors may adapt actively by choosing from a variety of strategies, and the loss of income from the tourism industry may support the re-evaluation of the various functions agriculture plays in mountain regions, beyond the production of food. The study demonstrates the suitability of the PIA approach to elucidate the interactions between different stakeholders and their perception of the climate change phenomena. A similar participatory approach could be a useful tool to transfer research results and expert knowledge to the political process addressing adaptations to climate change. This revised version was published online in July 2006 with corrections to the Cover Date.     

Evaluating Uncertain CO2 Abatement over the Very Long Term

Climate change research with the economic methodology of cost–benefit analysis is challenging because of valuation and ethical issues associated with the long delays between CO₂ emissions and much of their potential damages, typically of several centuries. The large uncertainties with which climate change impacts are known today and the possibly temporary nature of some envisaged CO₂ abatement options exacerbate this challenge. For example, potential leakage of CO₂ from geological reservoirs, after this greenhouse gas has been stored artificially underground for climate control reasons, requires an analysis in which the uncertain climatic consequences of leakage are valued over many centuries. We here present a discussion of some of the relevant questions in this context and provide calculations with the top–down energy-environment-economy model DEMETER. Given the long-term features of the climate change conundrum as well as of technologies that can contribute to its solution, we considered it necessary extending DEMETER to cover a period from today until the year?3000, a time span so far hardly investigated with integrated assessment models of climate change.     

Scientist–stakeholder collaboration in integrated assessment of climate change: lessons from a case study of Northwest Canada

Research on the climate change issue has generally focused on uncertainties in climate projections and calculation of mitigation costs. Most integrated assessment (IA) efforts have been directed at the mitigation component. The problem of climate change, however, is really about the potential effects on ecosystems, resources, and societies that depend on them. As illustrated by experiences from the Mackenzie Basin Impact Study, a case study from Northwest Canada, these effects will be unique to each region and country. Many of these will be indirect, including region specific thresholds, vulnerabilities and adaptations which may not be included in sectoral analyses. Science can define some of the “What if” aspects of climate change, but the regional “So what” and “What should be done” questions are largely unanswered and subject to intense debate in various political fora. IA needs to recognize the multiobjective and multistakeholder aspects of vulnerabilities, risks, and potential responses to climate change. IA could provide a more holistic analysis of the regional impacts dimension of climate change by including both modeling and non‐modeling approaches, and incorporating institutional and stakeholder issues that do not readily lend themselves to economic analyses.     

Anticipating Climate Threshold Damages

Several integrated assessment studies have concluded that future learning about the uncertainties involved in climate change has a considerable effect on welfare but only a small effect on optimal short-term emissions. In other words, learning is important but anticipation of learning is not. We confirm this result in the integrated assessment model “model of investment and technological development” for learning about climate sensitivity and climate damages. If learning about an irreversible threshold is included, though, we show that anticipation can become crucial both in terms of necessary adjustments of pre-learning emissions and resulting welfare gains. We specify conditions on the time of learning and the threshold characteristic, for which this is the case. They can be summarized as a narrow “anticipation window.”     

Global climate change and regional sustainable development: the case of Mackenzie Basin in Canada

Cohen et al. [16] suggest that in order to explore ways to bring climate change (CC) and sustainable development (SD) research together, it is necessary to develop more heuristic tools that can involve resource users and other stakeholders. In this respect, this paper focuses on methodological development in research to study climate change impacts and regional sustainable development (RSD). It starts with an introduction of an integrated land assessment framework (ILAF) which is part of the integrated phase of the Mackenzie Basin Impact Study (MBIS) in Canada. The paper then provides some articulation on how the integrated approach was applied in the Mackenzie Basin to show implications of climate change for RSD.     

Representing uncertainty in climate change scenarios: a Monte-Carlo approach

Climate change impact assessment is subject to a range of uncertainties due to both incomplete and unknowable knowledge. This paper presents an approach to quantifying some of these uncertainties within a probabilistic framework. A hierarchical impact model is developed that addresses uncertainty about future greenhouse gas emissions, the climate sensitivity, and limitations and unpredictability in general circulation models. The hierarchical model is used in Bayesian Monte-Carlo simulations to define posterior probability distributions for changes in seasonal-mean temperature and precipitation over the United Kingdom that are conditional on prior distributions for the model parameters. The application of this approach to an impact model is demonstrated using a hydrological example. This revised version was published online in July 2006 with corrections to the Cover Date.     

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology.     

Earth system analysis and management

A research strategy based upon models of intermediate complexity addressing crucial aspects of global environmental change is presented. The key idea behind that strategy is to compress system complexity either by formal techniques such that first-order aspects are preserved, or to employ semi-qualitative schemes to describe and simulate the dominant dynamical patterns identified by panoramic inspection.Specific realizations of the overall heuristic philosophy are introduced as elements of a comprehensive research program on global change. Topics encompass global climate modeling, a decision analysis framework for managing the global warming problem by balancing adaptation and mitigation efforts, a generic approach to integrated regional climate impact assessment and its implementation in specific regions, as well as a new technique to link regional and global patterns of environmental change by using advanced modeling tools.     

Health impact assessment in spatial planning in England –types of application and quality of documentation

Health Impact Assessment (HIA) is a decision support approach which is applied in various shapes and forms throughout the world. In England, amongst a range of areas of application, HIA is applied in local (spatial) plan making and project development planning. Whilst various authors have reflected on HIA practice in England, the extent of application and its quality has remained unclear. This paper aims at addressing this gap by reporting on the results of a systematic review of HIA in planning. It is found that between 100 and 200 HIAs are likely being produced each year in England. Whilst most assessments are rapid (desk based), there are also examples of comprehensive and intermediate HIAs, where a participatory procedural approach is followed. An important finding is that those HIAs applied within the context of other assessments (integrated impact assessment -IIA, strategic environmental assessment - SEA/ sustainability appraisal -SA and environmental impact assessment – EIA) tend to be of a higher quality than standalone HIAs, mainly because of the existing comprehensive statutory procedural requirements for these other assessments into which HIA can be integrated.     

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.     

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.     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.     

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.     

Integrating Impacts into Adaptation Measures

A mechanism has been established to improve integration of international climate-related programmes. Known as the Climate Agenda it outlines a programme, that in a cost-effective way, responds to national obligations to respond to international agreements as well as their national needs for social and economic development. The paper briefly describes the Climate Agenda and the incorporation within it of studies of climate impact assessments and response strategies to reduce vulnerability. The need for increased emphasis on climate impact assessment and for the development of effective adaptation measures is emphasised following the elaboration of a Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC). UNEP's efforts to identify national programmes contributing to the Climate Agenda are described.The response from developing countries has, however, been very disappointing, even from countries where we know work is ongoing through funding by GEF or US Country Studies Program and other bilateral programmes. Initial compilation of information available so far shows that many developed countries are putting a lot into the area of impact assessment of not just climate change, but also climate variability. There remain some research gaps, especially in the area of assessment of climate impacts on ecosystems, hydrological systems, etc. Considerable efforts are presently being directed at reduction of emissions of greenhouse gases and in the case of developing countries, most efforts are being directed towards completing national communications and providing baseline data for future studies.The paper refers to early activities by UNEP in cooperation with other international organizations to undertake integrated assessments of the impacts of climate change on important socio-economic sectors and the later incorporation of lessons learned into the IPCC Guidelines for Assessing Impacts of Climate Change.Later sections outline the development of a handbook on methods for climate change impact assessment and adaptation strategies as a practical approach to national assessments and the development of appropriate and cost-effective response to climate change.The initiation of a GEF-funded project to apply the methods contained in the handbook and improve the results based on national studies is also described for both developed and developing countries.Working in collaboration with a team of international experts under the coordination of the Institute of Environmental Studies at Vrije University (Amsterdam), the goal of this ongoing project is to develop a valuable methodological tool that Parties to the UNFCCC may apply to develop national climate change impact and adaptation assessments. Development of these guidelines was linked to a series of country studies in Antigua and Barbuda, Estonia, Cameroon and Pakistan funded under a UNEP/GEF project. The application of the first version of the UNEP Handbook by national study teams in these four countries is making valuable technical and practical contributions and will ensure that the next version of the Handbook will be a more useful tool for experts in developing countries undertaking similar studies in the future. The methods contained in the Handbook are also the basis for similar assessments funded under bilateral development programmes in other countries. These and similar studies elsewhere are coordinated with the UNEP programme and will eventually aim to create reliable and comparable assessments, a compatible set of tools for such purpose and the identification of realistic adaptation options for incorporation into national planning for adapting to climate change. The paper also addresses how climate impact assessment and response strategies are undertaken as part of national enabling activities carried out in co-operation with UNEP.     

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.