Marine Pollution Bulletin xxx (2015) xxx–xxx
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Correspondence Renewables-to-reefs: Participatory multicriteria decision analysis is required to optimize wind farm decommissioning
Smyth et al. (2015) present a detailed consideration of the ecological, societal, economic and regulatory aspects of wind farm decommissioning in the marine environment. The result is a consolidated base of information that will hopefully assist managers and the industry to prepare for the decommissioning phase. However, the analyses used to compare the two decommissioning options (partial and complete removal) are not sufficient to identify the best-performing option, nor do they provide a structured method for incorporating stakeholder values into the decision process. While we suspect the authors’ motives were to provide a general comparison for use as a guide, rather than an exact method to be implemented in specific decommissioning cases, future use of their methods may result in sub-optimal outcomes for both society and the marine environment. Smyth et al. (2015) also propose a large-scale ‘renewables-to-reefs’ program based on the outcomes of their analyses, which is premature given the lack of rigorous comparison between the two options. We therefore use this comment to outline the above issues with Smyth et al.’s (2015) methods and propose a more rigorous approach for wind farm decommissioning decisions based on multicriteria decision analysis (MCDA). The approach has recently been developed to optimize decommissioning decisions for offshore oil and gas infrastructure (see Fowler et al., 2014), which share many of the environmental and social considerations of wind farms, as well as similar decision challenges. 1. Decision dilemmas Smyth et al. (2015) use two main analyses to compare between decommissioning options for wind farms: a SWOT analysis and a comparison of ecosystem services provision. SWOT analyses are simply a list of the Strengths, Weaknesses, Opportunities and Threats that the user(s) can identify for each option. Although they are useful for understanding the range of considerations involved in a decision, and allow a qualitative comparison of ‘pros’ and ‘cons’ between options, they fail to sum up the performance of each option across all considerations so that a final decision can be made. This can clearly be seen in Table 1 and the related discussion in Section 3.3 of Smyth et al. (2015), where the partial removal option outperforms the complete removal option with respect to cost and environmental benefits, while the reverse is true for future site use. So which option should be selected, given both options have merits and detriments? Does the user decide that protecting the environment is of utmost importance, or perhaps they consider future site use to be essential?
http://dx.doi.org/10.1016/j.marpolbul.2015.07.002 0025-326X/Ó 2015 Published by Elsevier Ltd.
Leaving the user with such decision dilemmas presents two issues. Firstly, the user must attempt a series of complex trade-offs among competing considerations. In the simplified example above, there are only 3 considerations that the user must trade off in order to identify the decommissioning option that performs best overall; cost, environmental benefit and future site use. Actual decommissioning scenarios can involve over 30 considerations (see Table 2 of Smyth et al., 2015), each of which may vary among the different options (Cripps and Aabel, 2002; Fowler et al., 2014). The decision problem quickly becomes impossible for the user to optimize, that is, to identify the option which presents the best compromise across all considerations (Kiker et al., 2005). The comparison of ecosystem services provision by Smyth et al. (2015) also suffers from this issue. Decommissioning options were given a categorical performance score for each consideration (see their Table 2), yet no process was proposed for amalgamating scores across all considerations to identify the best-performing option overall. In such situations, it may be tempting to sum the scores for individual considerations and select the option with the highest overall score, as would be possible from Table 2 of Smyth et al. (2015). However, this method does not account for potential differences in the relative importance of considerations. For example, poor performance with regard to carbon sequestration could be completely offset by strong performance with regard to aesthetic benefits, when carbon sequestration should arguably have a far greater influence on the decision. For this reason, decision considerations must be weighted according to their importance and this weighting scale must be directly integrated into the selection process (see the MCDA section below). Instead of attempting to generate an overall performance score for each decommissioning option, Smyth et al. (2015) discuss at length the various decision considerations and their potential trade-offs (see their Section 3.4). While the discussion provides useful insights into the issues surrounding wind farm decommissioning, it does not provide a clear path forward for actually making those trade-offs and selecting an option, which is the most important aspect from a management and environmental perspective. The second issue with leaving the user to make the final comparison between decommissioning options involves the potential for bias to unduly influence the decision. Our cultural backgrounds, degree of training, and professional and personal experiences may lead us to prioritize some decision considerations over others (Kuhnert et al., 2010). Biases may be appropriate for decisions that involve one or only a small number of stakeholders, because such biases may actually represent priorities that are necessary for the decision. However, they are entirely inappropriate for decisions that involve a large number of stakeholders with conflicting values, such as decommissioning decisions for offshore infrastructure (Ekins et al., 2006; Fowler et al., 2014). Decision bias may undervalue the needs of particular stakeholder groups, leading to
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mistrust of the decision process and dissatisfaction with the final outcome. It is therefore essential that the decision method used for wind farm decommissioning provides an objective comparison of overall performance between options, so that the effects of any user biases on the final decision are minimized. 2. Stakeholder participation Smyth et al. (2015) note the importance of stakeholder participation in wind farm decommissioning, yet do not suggest a process by which such participation should occur. Approaches to stakeholder participation should be considered early on in any discourse relating to offshore decommissioning, because early stakeholder engagement is essential for effective participation in environmental decisions (Reed, 2008) and methods of stakeholder participation must be tailored to suit the particular decision scenario and the participants involved (Irvin and Stansbury, 2004). Planning for stakeholder engagement and participation is likely to be especially important for wind farm decommissioning given the likely conflicts among key stakeholder groups. Clashes between stakeholders regarding the initial placement (‘siting’) of wind farms indicate that considerable conflict can be expected between operating companies, commercial fishers and the general public (Haggett, 2008), particularly with regard to leaving part of the structure in the marine environment (i.e. partial removal). Careful planning of stakeholder engagement will be required for each decommissioning case to minimize conflict and ensure resulting decisions are both equitable and transparent. Decommissioning decisions for wind farms are most likely to be optimized using direct stakeholder participation. Direct participation refers to the contribution of relevant data, as well as construction of the decision model itself (Mendoza and Prabhu, 2005). Note that the latter condition requires participation from the commencement of the decision process, not merely during later implementation phases, as has been common practice for environmental decisions to date (Reed, 2008). Representatives from all stakeholder groups should be involved with initially defining the objectives of a decommissioning project, as well as compiling a list of decision considerations that reflect these objectives (e.g. Table 2 of Smyth et al., 2015). Such lists are often compiled by technical experts and simply presented to stakeholders as a final product. However, technical experts may overlook considerations that are essential to the objectives of particular stakeholder groups. Stakeholders should also assist with weighting the decision considerations in order of their importance to the decision. For example, stakeholders could be asked to order the ecosystem goods and services presented in Table 2 of Smyth et al. (2015) from most important through to least important to the decision. Such information would then ensure that the selection of a particular decommissioning option for wind farms was not overly influenced by relatively trivial considerations in the eyes of stakeholders. The participatory steps suggested above will go a long way to ensuring that the needs of stakeholders are met during decommissioning of wind farms. The contribution of stakeholders to the decision model, through construction of the consideration list and weighting scale, will encourage trust in the process and therefore reduce the chance of stakeholder disillusionment following the decommissioning decision (Sheppard, 2005). Given the likely conflicts between stakeholder groups involved with wind farm decommissioning, minimizing controversy both during and after the decision process will be critical to a successful outcome. The importance of managing conflict during decommissioning decisions can be seen in historical controversies surrounding the offshore oil and gas industry. For example, the proposed offshore
disposal of the Brent Spar oil storage facility in the North Sea in 1995 generated such hostility from an environmental NGO (Greenpeace) and the general public that the structure was eventually taken to shore for dismantling (Jørgensen, 2012), despite this option being less safe and more costly, with little additional environmental benefit. Analyses following the event indicated that the conflict arose from miscommunication of information to stakeholders, rather than any credible threat to the offshore environment (Löfstedt and Renn, 1997). This event clearly demonstrated that even accidental stakeholder neglect has the power to derail otherwise carefully-planned decommissioning decisions in the offshore environment. 3. Participatory multicriteria decision analysis Multicriteria decision analysis (MCDA) is fast becoming the benchmark for optimizing environmental decisions. MCDA refers to a suite of methods that allow decision-makers to assess and compare the performance of alternative options across multiple, potentially competing, considerations (criteria). Importantly, MCDA can handle the complex series of trade-offs generated when no single option performs best overall; a scenario which seems likely for wind farm decommissioning (Smyth et al., 2015). In this way, MCDA can assist the decision-maker to identify the option that provides the best compromise in a particular scenario. The approach is particularly useful for environmental decisions such as decommissioning of offshore infrastructure, because it can accommodate the competing views of multiple stakeholder groups and can incorporate a wide range of data types (Mendoza and Martins, 2006). MCDA has already been successfully applied to decisions in forestry management (Kangas and Kangas, 2005), waste disposal (Merkhofer et al., 1997) and water use (Keeney et al., 1996), among others. Participatory MCDA simply refers to approaches that involve stakeholders in both the development and running of the decision model, as discussed in the previous section. While specific methods of MCDA differ in their modeling procedures, most follow a general process: (1) define the decision aims, (2) identify criteria that address the aims, (3) identify alternative options, (4) assess the performance of each option for each criteria, (5) weight criteria according to importance, (6) combine performance for individual criteria into an overall performance estimate for each option and (7) select the overall best-performing option (Ananda and Herath, 2009; Linkov et al., 2004). In their comparison of partial and complete removal of wind farm infrastructure, Smyth et al. (2015) succeed in completing Steps 1 through 4, yet do not directly address Steps 5 and 6. It is therefore difficult to achieve Step 7 in an objective manner. We propose the use of Multicriteria Approval (MA) for making decommissioning decisions for wind farms. MA follows the general steps of MCDA set out above and employs voting principles to compare the performance of alternative options (Steps 6 and 7). Each option is ‘approved’ or ‘disapproved’ for each criterion based on a threshold performance level set by the decision-maker. Criteria are then ordered from most important to least important and the option approved for the greatest number of sequentiallyimportant criteria is selected. MA was specifically designed for decisions involving mixed datasets of low quality (Fraser and Hauge, 1998), and can incorporate both qualitative and quantitative data, making it particularly suited to offshore decommissioning decisions where high-quality environmental data are often lacking (Macreadie et al., 2011). The simplicity of the MA method means it can be easily understood by non-technical decisionmakers and stakeholders, thereby ensuring that the decision process does not become a ‘black box’.
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We suggest participatory MA for wind farm decommissioning be implemented on a case-by-case basis, following the approach developed by Fowler et al. (2014) for decommissioning of offshore oil and gas infrastructure. Focus groups should be used to elicit stakeholder opinions on decision aims (Step 1), the criteria list (Step 2) and the relative weighting of criteria (Step 5). Visualization aids including 3D computer simulations should be used to describe the decision problem to stakeholders and introduce the alternative options available (Sheppard and Meitner, 2005). Criteria lists can also be developed visually using a decision matrix, which is a two-dimensional array consisting of the range of alternative options on one axis and the list of criteria on the other. The decision matrix is then passed to technical experts who score the performance of each option for each criterion, incorporating stakeholder opinion for those criteria where stakeholders possess unique knowledge (e.g. aesthetic impact). A rank-based system will likely be useful for scoring the relative performance of decommissioning options for individual criteria, because current knowledge on environmental aspects of offshore structures is still too poor to quantify performance for most environmental criteria. Ranks incorporate a degree of uncertainty into performance assessments and prevent decision errors of large magnitude (Kangas and Kangas, 2003). The outcomes of participatory MA for wind farm decommissioning should be explored with stakeholders to ensure understanding of final decisions. Rudimentary sensitivity analyses are useful for this purpose; stakeholders can be shown the effect of systematic changes to the weightings scale and performance scores on the final outcome. In some cases, decisions are quite robust to variations in input data (e.g. Fowler et al., 2014), and demonstrating this to stakeholders can engender trust in the decision. At other times, there will be little distinction between a number of alternative options (Kangas et al., 2006), despite the model selecting a single best performer. This outcome suggests that multiple options come close to optimizing the decision problem, and therefore selection of one or the other is unlikely to result in substantial error. Alternatively, little data may have been available on key considerations to the decision, in which case further data collection will be required to break the deadlock. 4. Conclusions Although offshore wind farms will not reach the decommissioning phase for a decade or more, planning for decommissioning decisions and stakeholder consideration should begin now. Lessons should be learned from the offshore oil and gas industry, which is currently struggling with the aftermath of poor decision processes during the decommissioning phase. The lack of appropriate decision support tools and inadequate stakeholder involvement have resulted in a hostile decommissioning environment, fueled by mistrust and skepticism, particularly in the UK. Avoiding a similar scenario will be central to the success of decommissioning for wind farms globally. Here, we have outlined a rigorous process for making decommissioning decisions which, if uptaken by the offshore wind energy industry, will optimize decisions while simultaneously minimizing stakeholder conflict. However, considerable research is required to understand the priorities and preferences of the stakeholder groups that will be involved. The dearth of knowledge regarding the ecology of offshore wind farms must also be addressed if the performance of alternative options is to be accurately assessed and compared. Considerable progress on both these fronts can be achieved in time for the decommissioning phase of offshore wind farms, providing research is prioritized now.
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Ashley M. Fowler Centre for Environmental Sustainability (CEnS), School of Life Sciences, University of Technology Sydney, Broadway, NSW, Australia E-mail address:
[email protected] Peter I. Macreadie Plant Functional Biology and Climate Change Cluster (C3), School of Life Sciences, University of Technology Sydney, Broadway, NSW, Australia Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, VIC, Australia
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David J. Booth Centre for Environmental Sustainability (CEnS), School of Life Sciences, University of Technology Sydney, Broadway, NSW, Australia Available online xxxx
