Marjolein B. A. van Asselt’s research while affiliated with Maastricht University and other places

Two series of smog chamber experiments have been conducted to determine the par- ticulate yield from toluene photo oxidation and to investigate the dependence of the yield on experimental factors. Toluene was oxidized by HO radicals in the presence of NO by irradiating mixtures of toluene/isopropylnitrite/NO with UV light and experiments were done in the presence and absence of ammonium sulfate seed particles. Aerosol formation and growth was monitored using size distributions obtained from a Differential Mobility Analyzer and a Condensation Nucleus Counter. A Gas Chromatograph with an FID detector was used to monitor the toluene loss and a Chemiluminescence Analyzer measured the NO concentration. As expected the ozone concentration was found to be extremely low so the complicating ozone reactions are minimized. The experimental yields (the ratio between the organic aerosol mass formed and the mass of toluene reacted) were found to cluster around 10% but there were cases where the yields were as low as 1.7% and as high as 20%. The on-going work is focused on understanding the factors leading to the variability of experimental yields and on analyzing the data in the framework of the current gas/particle partitioning theory.

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 dilemmas and 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 in Integrated Assessment modeling, on which evaluation it is argued that complementary methods are needed that allow for pluralistic uncertainty management. The paper finalises 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.

Integrated Assessment is the practice of combining different strands of knowledge to accurately represent and analyse real word problems of interest to decision-makers. Since these problems rarely observe disciplinary boundaries, Integrated Assessment usually involves interdisciplinary research. However, what distinguishes Integrated Assessment from interdisciplinary research is its policy dimension, aiming to inform decision-makers on the complexity of real world problems. Unfortunately, the body of existing disciplinary knowledge is often insufficient for the construction of an accurate representation of real world problems. Integrated Assessment offers a systematic approach to identification of the gaps in disciplinary knowledge that have often frustrated policy analysis in the past. Thus, Integrated Assessment has increasingly been the source of critical questions and new directions of research in the disciplinary sciences. Integrated Assessment is particularly useful for analysis of real world problems that are complex, operate at different levels in time and space, are immersed in uncertainty and for which the stakes are high. Because there are no simple solutions to these complex problems facing humankind, Integrated Assessment aims at conveying innovative and sometimes counterintuitive insights into the issues at hand rather than ready-made solutions. Portraying and translating real world problems can be done from a plurality of perspectives. There is no one “right” way to represent and analyse the world, therefore a diversity of methods and approaches to Integrated Assessment are needed, ranging from model-based methods to participatory methods [22,29]. Generally, these methods are, in varying degrees, in their relative infancy. The currently most widely used method of performing Integrated Assessment is modelling. Integrated Assessment models are frameworks to organize and structure various pieces of recent scientific disciplinary knowledge. A key issue in Integrated Assessment (IA) modelling is uncertainty due to various reasons. First of all IA modelling is confronted with the inherent uncertainty and lack of knowledge that the disciplinary sciences face. Secondly, IA models have to deal with a variety of types and sources of uncertainty that have to be structured and combined in one way or another. And finally, IA models are prone to a cumulation of uncertainties, because of their ambition to cover the whole cause–effect chain of a particular real world problem. This all makes uncertainty one of the most problematic but also one of the most challenging issues in the field of IA modelling. This paper therefore focuses on the laborious relation between uncertainty and IA modelling. After a description of what IA models are and where they can be used for, the issue of uncertainty is raised and how IA models struggle with it. One possible way out is presented in terms of a pluralistic approach towards the management of uncertainties in IA modelling.

Nowadays cities are seen as motors for the sustainable development of European regions, and are thus of crucial importance for the future of Europe as a whole. Because the social, economic, ecological and institutional development of a city are increasingly interwoven, city management has become a complex enterprise. Management of complex systems such as cities requires the use of innovative, sophisticated planning tools that can assist in monitoring current conditions and projecting future developments. It also requires a well-structured participatory process of creating social support by stakeholders for long-term city visions. In this paper an integrated approach is proposed towards: (i) the development and implementation of a generic city planning tool that in principle can be applied to any kind of city. The proposed tool is a combination of an information system and a dynamic model, which enables the instrument to be used in both strategic and operational manners; and (ii) the development of long-term integrated visions for a more sustainable city through a participatory trajectory in which the integrated city planning tool can be supportive in developing stakeholder-based long-term visions for a more sustainable future of cities. To illustrate the planning tool for sustainable cities the case for Maastricht, a middle-size town in the Netherlands, is described, which will be carried out in the next 3 years. Copyright

Nowadays cities are seen as motors for the sustainable development of European regions, and are thus of crucial importance for the future of Europe as a whole. Because the social, economic, ecological and institutional development of a city are increasingly interwoven, city management has become a complex enterprise. Management of complex systems such as cities requires the use of innovative, sophisticated planning tools that can assist in monitoring current conditions and projecting future developments. It also requires a well-structured participatory process of creating social support by stakeholders for long-term city visions. In this paper an integrated approach is proposed towards: (i) the development and implementation of a generic city planning tool that in principle can be applied to any kind of city. The proposed tool is a combination of an information system and a dynamic model, which enables the instrument to be used in both strategic and operational manners; and (ii) the development of long-term integrated visions for a more sustainable city through a participatory trajectory in which the integrated city planning tool can be supportive in developing stakeholder-based long-term visions for a more sustainable future of cities. To illustrate the planning tool for sustainable cities the case for Maastricht, a middle-size town in the Netherlands, is described, which will be carried out in the next 3 years. Copyright © 2000 John Wiley & Sons, Ltd.

In line with the theoretical criteria and conditions discussed in the previous part of this thesis, a general framework for pluralistic integrated uncertainty management and risk analysis is proposed in this Chapter. The various steps will be discussed as concrete as possible. In the next part of the thesis, it will be explored in practice by means of the case of an example of an actual assessment process (Chapters 6–8). The aim is that by means of this testing, the theoretical outline can be developed into a more practically feasible framework (Chapter 9).

The decisions of modern life are complex, giving rise to often intractable uncertainty in decision making. This uncertainty can take several forms. Different perspectives lead people to perceive and seek to manage the world in different ways. The approach proposed in this thesis enhances awareness of this pluralism and helps Integrated Assessment practitioners to consider the possibilities and consequences of various equally legitimate possible development pathways and, hence, avoid being over deterministic and positivistic in their practice.

The primary aim of this thesis is to propose a new approach to decision-support that is practically feasible as well as theoretically sound. We therefore want to explore in a real-life context whether the prima framework, outlined and theoretically underpinned in the previous part of this thesis, has something to offer to the practise of Integrated Assessment. The aim of this practical test is twofold. First, we want to evaluate whether there is a potential need for a new or complementary approach to uncertainty management amongst practitioners. To that end, it is proposed to perform a retrospective case study involving previous decision-support on complex issues. Second, we want to explore the potential added value of the proposed approach compared to present assessment strategies for decision-support. Therefore, the retrospective analysis will be followed by a prospective study that enables to explore the practical feasibility of the prima-approach in a real life context. To do so, it is necessary to setup a mutual learning process, in which we, together with the analysts, explore whether and how the prima-approach is applicable in actual decision-support on complex issues.