Evaluation of factors affecting stakeholder risk perception of contaminated sediment disposal in Oslo harbor.

The management of environmental pollution has changed considerably since the growth of environmental awareness in the late 1960s. The general increased environmental concern and involvement of stakeholders in today's environmental issues may enhance the need to consider risk in a much broader social context rather than just as an estimate of ecological hazard. Risk perception and the constructs and images of risks held by stakeholders and society are important items to address in the management of environmental projects, including the management of contaminated sediments. Here we present a retrospective case study that evaluates factors affecting stakeholder risk perception of contaminated sediment disposal that occurred during a remediation project in Oslo harbor, Norway. The choice to dispose dredged contaminated sediments in a confined aquatic disposal (CAD) site rather than at a land disposal site has received a lot of societal attention, attracted large media coverage, and caused many public discussions. A mixed method approach is used to investigate how risk perceptive affective factors (PAF), socio-demographic aspects, and participatory aspects have influenced the various stakeholders' preferences for the two different disposal options. Risk perceptive factors such as transparency in the decision making process and controllability of the disposal options have been identified as important for risk perception. The results of the study also support the view that there is no sharp distinction in risk perception between experts and other parties and emphasizes the importance of addressing risk perceptive affective factors in similar environmental decision-making processes. Indeed, PAFs such as transparency, openness, and information are fundamental to address in sensitive environmental decisions, such as sediment disposal alternatives, in order to progress to more technical questions such as the controllability and safety.

[1]  P. Slovic Perception of risk. , 1987, Science.

[2]  C. Starr Social benefit versus technological risk. , 1969, Science.

[3]  R. P. McDonald,et al.  Principles and practice in reporting structural equation analyses. , 2002, Psychological methods.

[4]  J. A. de Bruijn,et al.  Scientific expertise in complex decision-making processes , 1999 .

[5]  Ortwin Renn Risk Governance: Coping with Uncertainty in a Complex World , 2008 .

[6]  Michael Dear,et al.  Understanding and Overcoming the NIMBY Syndrome , 1992 .

[7]  Arne Remmen,et al.  Greening of Danish Industry - Changes in Concepts and Policies , 2001, Technol. Anal. Strateg. Manag..

[8]  E Ferguson,et al.  From comparative risk assessment to multi-criteria decision analysis and adaptive management: recent developments and applications. , 2006, Environment international.

[9]  Lennart Sjöberg,et al.  Rational Risk Perception: Utopia or Dystopia? , 2006 .

[10]  L. Sjöberg The Methodology of Risk Perception Research , 2000 .

[11]  Rakesh K. Sarin,et al.  RELATIVE RISK AVERSION. , 1982 .

[12]  Th. Plattner,et al.  under a Creative Commons License. Natural Hazards and Earth System Sciences , 2005 .

[13]  F. Cross Facts and values in risk assessment , 1998 .

[14]  G. Keijzers,et al.  The evolution of Dutch environmental policy: The changing ecological arena from 1970–2000 and beyond , 2000 .

[15]  Luiza Toma,et al.  Environmental risk perception, environmental concern and propensity to participate in organic farming programmes. , 2007, Journal of environmental management.

[16]  Melissa L. Finucane,et al.  Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality , 2004, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  Susan Miles,et al.  The Media and Genetically Modified Foods: Evidence in Support of Social Amplification of Risk , 2002, Risk analysis : an official publication of the Society for Risk Analysis.

[18]  Igor Linkov,et al.  Application of Multicriteria Decision Analysis Tools to Two Contaminated Sediment Case Studies , 2007, Integrated environmental assessment and management.

[19]  P. Bentler,et al.  Comparative fit indexes in structural models. , 1990, Psychological bulletin.

[20]  L. Cronbach Coefficient alpha and the internal structure of tests , 1951 .

[21]  J. Schafer,et al.  Missing data: our view of the state of the art. , 2002, Psychological methods.

[22]  Sabine E. Apitz,et al.  Is risk-based, sustainable sediment management consistent with European policy? , 2008 .

[23]  Matthijs Hisschemöller,et al.  Participation as Knowledge Production and the Limits of Democracy , 2005 .

[24]  Arnold Tukker,et al.  The Fourth Generation: New Strategies Call for New Eco-Indicators , 2001 .

[25]  W. Poortinga,et al.  Trust, the Asymmetry Principle, and the Role of Prior Beliefs , 2004, Risk analysis : an official publication of the Society for Risk Analysis.

[26]  M. Browne,et al.  Alternative Ways of Assessing Model Fit , 1992 .

[27]  Silvio Funtowicz,et al.  ‘Democratising’ expertise, ‘expertising’ democracy: What does this mean, and why bother? , 2003 .

[28]  Ketil Hylland,et al.  Development of sediment quality criteria in Norway , 2010 .

[29]  David N. Barton,et al.  Sediment and society: an approach for assessing management of contaminated sediments and stakeholder involvement in Norway , 2010 .

[30]  Gijs D Breedveld,et al.  From ecological risk assessments to risk governance: Evaluation of the Norwegian management system for contaminated sediments , 2010, Integrated environmental assessment and management.