Uncertainty management in integrated assessment modeling: towards a pluralistic approach

Integrated Assessment (IA) is an evolving research community that aims to address complex societal issues through an interdisciplinary process. The most-widely used method in Integrated Assessment is modeling. The state of the art in Integrated Assessment modeling is described in this paper in terms of history, general features, classes of models, and in terms of the strengths and weaknesses, and the dilemmasand challenges modelers face. One of the key challenges is the issue of uncertainty management. The paper outlines the sources and types of uncertainty modelers are confronted with. It then discusses how uncertainties are currently managed inIntegrated Assessment modeling, on which evaluation it is argued that complementary methods are needed that allow for pluralistic uncertainty management. The paperfinalises with discussing pluralistic concepts and approaches that are currently explored in the IA community and that seem promising in view of the challenge to incorporate explicitly more than one hidden perspective in models.     

Risk management and integrated assessment

Integrated Assessment (IA) is the pursuit of a research program generated by the limitations of traditional forms of risk management. This claim can be justified by the following argument. Over the last decades, analysts and practitioners have brought to maturity a large array of tools for risk management. Most of them rely on combining judgments of utility with judgments of probability. This is the approach of the Rational Actor Paradigm (RAP). With many environmental problems, however, RAP‐based tools have run into considerable practical and theoretical difficulties. In response to these difficulties, a series of alternative approaches to practical risk management and to the theoretical understanding of risk have been elaborated. They try to embed the rational choices of individual actors studied by RAP into a broader framework of social rationality. This task can be approached by distinguishing situations where an actor holds unambiguous judgments of preference and probability from situations characterized by ambivalent judgments. RAP can handle the former, but not the latter. Problems whose management requires a combination of widely differing scientific disciplines are especially likely to involve ambivalent judgments of probability. The study of such problems constitutes the research program of integrated assessment. It involves three main tasks: developing IA models which can represent ambivalent expectations and evaluations, developing IA models which use such representations to study non‐marginal changes of social systems, and developing procedures of participatory IA which enable researchers to engage in an iterative exchange with various stakeholders. This revised version was published online in August 2006 with corrections to the Cover Date.     

growing pains: a conceptual framework for considering integrated assessments

Policy concerns related to the environment have grown in the past decadesfrom relatively local and well-defined problems to increasingly complex andglobal issues. With this has grown the need to develop the capacity tointegrate, reconcile, organize, and communicate knowledge across scientificdisciplines, as well as to make this knowledge available and useful for policy-makers. One response to this has been the growing field ofIntegrated Assessment (IA). Our goal in this paper is to reflect on the purpose and valueof IA in principle. We propose a conceptual framework within whichindividual IA studies, and the practice of IA as a whole, can be placed andevaluated. The framework addresses both the integrative nature of IAs andtheir policy usefulness, including a self-awareness of their role and capabilities. We illustrate several stages in the evolution of integrated assessments: fromlinear to more complex chains of analysis, from non-adaptive to perfectly-adaptive to realistically-adaptive agents, from simplistic to sophisticated to pluralistic consideration of alternative underlying development paths, from strictly quantitative to quantitative and qualitative analyses, from science-driven to policy-driven, and from analyses that dictate to users to those that involvethose users in the actual assessment process. By so doing, we argue for botha richer form and process of IA. Ultimately, we feel that it may also benecessary to reconsider the framing of the questions that IAs have been askedto address, perhaps leading to the consideration of the use of other forms of mandated science.     

On the optimal control of carbon dioxide emissions: an application of FUND

This paper presents the Climate Framework for Uncertainty, Negotiation and Distribution (FUND), an integrated assessment model of climate change, and discusses selected results. FUND is a nine‐region model of the world economy and its interactions with climate, running in time steps of one year from 1990 to 2200. The model consists of scenarios for economy and population, which are perturbed by climate change and greenhouse gas emission reduction policy. Each region optimizes its net present welfare. Policy variables are energy and carbon efficiency improvement, and sequestering carbon dioxide in forests. It is found that reducing conventional air pollution is a major reason to abate carbon dioxide emissions. Climate change is an additional reason to abate emissions. Reducing and changing energy use is preferred as an option over sequestering carbon. Under non‐cooperation, free riding as well as assurance behaviour is observed in the model. The scope for joint implementation is limited. Under cooperation, optimal emission abatement is (slightly) higher than under non‐cooperation, but the global coalition is not self‐enforcing while side payments are insufficient. Optimal emission control under non‐cooperation is less than currently discussed under the Framework Convention on Climate Change, but higher than observed in practice. This revised version was published online in July 2006 with corrections to the Cover Date.     

Application of a risk assessment based approach to designing ambient air quality monitoring networks for evaluating non-cancer health impacts

An ambient air quality monitoring network has been establishedusing risk assessment techniques to evaluate adverse health effects from exposures to airborne contaminants. The risk assessment method was compared to traditional methods of establishing air quality monitoring networks: identifying maximumconcentration impacts or maximum total population. Results suggest that the health risk method best predicted the locationof adverse, non-carcinogenic respiratory illnesses during the evaluation period. Spearman Rank Correlation Coefficient, r _s, values obtained using the risk assessment method werestatistically greater than the values obtained using theconcentration and population methods. The concentration methodwas the least accurate predictor of adverse effects.     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

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.     

An environmental risk assessment framework for enhanced oil recovery solutions from offshore oil and gas industry

Environmental risk assessments are necessary to understand the risk associated with enhanced oil recovery (EOR) solutions and to provide decision support for choosing the best technology and implementing risk-reducing measures. This study presents a review of potentially relevant environmental/ecological risk assessment (ERA) guidelines and, based on this review, proposes an initial suggestion of an ERA framework for understanding the environmental impacts from EOR solutions. We first shortlist the important elements necessary for conducting an ERA of EOR solutions from the selected guidelines. These elements are then used to build the suggested ERA framework for produced water discharges, drilling discharges and emissions to air from EOR solutions, which is the primary objective of the present study. Furthermore, the emphasis is placed on identifying the knowledge gaps that exist for conducting ERA of EOR processes. In order to link the framework with the current best environmental practices, a review of environmental policies applicable to the marine environment around the European Union (EU) was conducted. Finally, some major challenges in the application of ERA methods for novel EOR technologies, i.e. uncertainties in the ERA due to lack of data and aggregation of risk from different environmental impacts, are discussed in detail. The frameworks suggested in this study should be possible to use by relevant stakeholders to assess environmental risk from enhanced oil recovery solutions.     

Indices for assessment and monitoring of large mammals within an adaptive management framework

Many development projects intended to exploit natural resourcesare occurring in fragile ecosystems, and therefore the need forsound biodiversity assessment and monitoring programs is growing.Large mammals are important components of these fragile ecosystems, yet there are few strategies that attempt to assess and monitor entire large mammal communities in relation to development projects. We propose the use of two indices applied within a framework of adaptive management. An occurrence indexassesses the composition and distribution of large mammals at a site, and an abundance index monitors the abundance of large mammals over time in relation to development. We discuss the design, applicability and effectiveness of these indices based onour experience with a natural gas development project in the Amazon forests of southeastern Peru.     

A framework for assessment and monitoring of small mammals in a lowland tropical forest

Development projects in tropical forests can impact biodiversity.Assessment and monitoring programs based on the principles of adaptive management assist managers to identify and reduce suchimpacts. The small mammal community is one important component ofa forest ecosystem that may be impacted by development projects. In 1996, a natural gas exploration project was initiated in a Peruvian rainforest. The Smithsonian Institution's Monitoring andAssessment of Biodiversity program cooperated with Shell Prospecting and Development Peru to establish an adaptive management program to protect the region's biodiversity. In thisarticle, we discuss the role of assessing and monitoring small mammals in relation to the natural gas project. We outline theconceptual issues involved in establishing an assessment andmonitoring program, including setting objectives, evaluating the results and making appropriate decisions. We also summarizethe steps taken to implement the small mammal assessment, provideresults from the assessment and discuss protocols to identifyappropriate species for monitoring.     

An assessment and monitoring program for birds in the Lower Urubamba region,Peru

We developed an assessment and monitoring plan for birds in connection with the exploration and potential development of a large natural gas field in the Lower Urubamba drainage of Peru, a project of Shell Prospecting and Development Peru (SPDP). Our objectives were to: (1) inventory the birds in the area, including information on habitat use and abundance, and (2) devise long-term monitoring protocols for birds. We sampled birds through a combination of visual and auditory surveys and mist-netting at 4 well sites and 3 sites along the Urubamba and Camisea rivers. We recorded 420 speciesduring 135 days of field work. We consider the highest prioritiesfor a future monitoring program to be: (1) establish whether edge effects are occurring at well sites, along roads and alongthe planned pipeline route and determine the significance and extent of these effects and (2) assess the impact of increased human access to the area on game and other exploited species. The remoteness of the area, its rugged terrain and dense vegetation and the lack of trained personnel limit the choice of survey and monitoring methods. We recommend use of mist-netting and transects for monitoring edge effects and useof transects for monitoring game and other exploited species.     

Dynamic Cost-Effective Reduction Strategies for Acidification in Europe: An Application to Ireland and the United Kingdom

This paper describes the application of an optimisation model for calculating cost-effective abatement strategies for the reduction of acidification in Europe while taking into account the dynamic character of soil acidification in a number of countries. Environmental constraints are defined in terms of soil quality indicators, e.g., pH, base saturation or the aluminium ion concentration in the soil solution within an optimisation model for transboundary air pollution.We present a case study for Ireland and the United Kingdom. Our results indicate that reduction of sulphur dioxide emission is more cost-effective than that of nitrogen oxides or ammonia. The reduction percentages for sulphur dioxide are highest, for two reasons: (i) marginal sulphur dioxide reduction costs are relatively low compared to marginal reduction costs of nitrogen oxides and ammonia and (ii) sulphur dioxide reduction is more effective in reducing acidification in physical terms than nitrogen oxides or ammonia abatement. Our dynamic analysis shows that a (fast) improvement of soil quality requires high emission reduction levels. These reduction levels are often higher than reduction levels that are typically deduced from the static critical loads approach. Once soil quality targets are reached, in our model, less stringent emission reductions are required to maintain the soil quality at a constant and good target level. Static critical load approaches that ignore dynamic aspects therefore may underestimate the emission reductions needed to achieve predefined soil quality targets.