Accounting for Uncertainty in Value Judgements when Applying Multi-Attribute Value Theory

In environmental decisions, analysts commonly face substantial uncertainties around stakeholders’ values judgments. Multi-Attribute Value Theory (MAVT), a family of multi-criteria decision analysis techniques, is applied in participative settings to articulate stakeholders’ values in decision-making. In MAVT, value judgments represent the intensity of individuals’ preferences in a set of objectives, which are operationalized as scaling factors or weights. Different sets of weights may express variation in people’s preferences or value judgments. Unfortunately, there are still important methodological gaps regarding how to incorporate uncertainty and the substantial variation commonly encountered in stakeholders’ preferences. This article presents a model of uncertainty that encompasses the dispersion of value judgments in MAVT. To achieve this goal, we draw on info-gap theory, which provides a mathematically grounded method for exploring sensitivity to preference weights when there are relatively high levels of uncertainties. We experimentally tested the uncertainty model in an environmental decision problem. We found that MAVT can use info-gap analysis to deal with multiple value judgments, avoiding exclusive reliance on nominal expected values to inform decisions. We explored a mechanism to explicitly consider the trade-offs between the performance of alternatives and the level of uncertainty that in any specified context a decision maker is willing to accept. Findings emphasize the potential of MAVT to support environmental management decisions, particularly in situations where multiple stakeholders and their contested value judgments have to be considered simultaneously to explore uncertainties around value trade-offs.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

Opening new institutional spaces for grappling with uncertainty: A constructivist perspective

In the context of an increasing reliance on predictive computer simulation models to calculate potential project impacts, it has become common practice in impact assessment (IA) to call on proponents to disclose uncertainties in assumptions and conclusions assembled in support of a development project. Understandably, it is assumed that such disclosures lead to greater scrutiny and better policy decisions. This paper questions this assumption. Drawing on constructivist theories of knowledge and an analysis of the role of narratives in managing uncertainty, I argue that the disclosure of uncertainty can obscure as much as it reveals about the impacts of a development project. It is proposed that the opening up of institutional spaces that can facilitate the negotiation and deliberation of foundational assumptions and parameters that feed into predictive models could engender greater legitimacy and credibility for IA outcomes.     

Application of multicriteria choice-methods in assessing eutrophication

Multicriteria choice-methods, often used in policy analysis, were examined as a methodological procedure for eutrophication assessment. Multicriteria analysis ranked the sampling sites along two coastal areas, according to nutrient and chlorophyll concentrations. Three levels of nutrient loading were revealed, characterizing eutrophic, mesotrophic and oligotrophic waters. These results have been compared to station grouping based on multivariate analysis which indicated similar trends. Multicriteria choice-methods were shown to be an effective methodological tool in assessing eutrophication. In addition, this approach is compatible with multicriteria methods applied on policy-making and therefore the problem of eutrophication can be integrated with plan and project evaluation in environmental management.     

Disparate perceptions about uncertainty consideration and disclosure practices in environmental assessment and opportunities for improvement

The need to better address uncertainties in environmental assessment (EA) is well known, but less known is how those involved in, or affected by, EA processes understand and perceive uncertainties and how uncertainties are considered and disclosed. Based on a survey of 77 Canadian EA practitioners, regulators, and interest groups, this paper explores uncertainties in the EA process, uncertainty consideration and disclosure in EA practice and decision-making, and opportunities for improved disclosure. Nearly 80% of participants indicated that all EAs contain uncertainty; however, uncertainty disclosure was described as poor. Only 15% indicated that uncertainties are sufficiently acknowledged in practice and, when disclosed, considered by decision makers. Perceptions about uncertainty differed significantly between those who conducted EAs compared to those potentially affected by development, suggesting that either communication about uncertainty is poor, or participants' understandings about what is considered ‘good’ practice are very different. Almost half of the participants believe that there is overconfidence in impact predictions and mitigation measures, and the majority indicated that if uncertainties were more openly reported then EA would be a better tool for informing decisions. Most participants did not believe that EAs that openly disclose uncertainties lack credibility; and contrary to proponents' tendencies to limit disclosure, participants perceived limited risk of disclosure in terms of project approval. The majority of participants did not believe that there was sufficient guidance available on how to report uncertainties, or on how to use that information in decision-making. Results indicate a substantial need to better understand how uncertainties are viewed and dealt with in EA; the importance of uncertainty disclosure and consideration in EA; and the risks and benefits of uncertainty disclosure to proponents, decision makers, and the public. We identify several opportunities for improving the practice of uncertainty consideration and disclosure.     

Mathematics for Scenarios of Biodiversity and Ecosystem Services

Balancing biodiversity conservation with food security and the preservation of a broader set of ecosystem services is among the greatest challenges of the century. The creation of the International Panel for Biodiversity and Ecosystem Services (IPBES), at the interface between decision support and scientific knowledge, is clearly in line with this ecological-economic perspective. IPBES particularly puts forward the development of model-based scenarios making sense economically and ecologically and promoting sustainability. The present paper provides generic modeling methods and tools to address such challenges. The paper argues that the framework of controlled dynamic systems under uncertainty together with ecoviability metrics are especially well suited. Such a modeling framework indeed makes it possible to simultaneously account for complex dynamics, indirect or indirect drivers, uncertainties along with multiple sustainability objectives. These general ideas are exemplified with scenarios relating to two applied fields: (i) fisheries and marine biodiversity and (ii) land-use and avifauna.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

A Bayesian approach for incorporating uncertainty and data worth in environmental projects

A data worth model is presented for the analysis of alternative sampling schemes in a special project where decisions have to be made under uncertainty. This model is part of a comprehensive risk analysis algorthm with the acronym BUDA. The statistical framework in BUDA is Bayesian in nature and incorporates both parameter uncertainty and natural variability. In BUDA a project iterates among the analyst, the decision maker, and the field work. As part of the analysis, a data worth model calculates the value of a data campaign before the actual field work, thereby allowing the identification of an optimum data collection scheme. A goal function which depicts the objectives of a project is used to discriminate among different alternatives. A Latin hypercube sampling scheme is used to propagate parameter uncertainties to the goal function. In our example the uncertain parameters are the parameters which describe the geostatistical properties of saturated hydraulic conductivity in a Molasse environment. Our results indicated that failing to account for parameter uncertainty produces unrealistically optimistic results, while ignoring the spatial structure can lead to an inefficient use of the existing data.     

A review of uncertainty research in impact assessment

This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, including uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA.     

Evaluation of a real-time monitoring system for river quality — a trade-off between risk attitudes,costs, and uncertainty

Uncertainty is definitely one of the key topics in environmental assessment and management. Typically, attempts to reduce uncertainty are subject to expenses. But how to compare and trade-off expenses and the reduced uncertainty? They only seldom allow the use of a single unit. Instead, the whole analysis and decision procedure is very subjective. This paper presents one approach to handle such problems, namely the combined use of Bayesian influence diagrams, and probabilistic risk attitude analysis. The approach was used in the evaluation of three alternatives for a real time river water quality forecasting system. A trade-off analysis of risk attitudes, costs and uncertainty indicated the levels of socioeconomic utility required for investments in the respective systems, and accordingly illuminated the impact of the uncertainties involved on inference and decision-making with various risk attitudes and discount rates.     

Ecological footprint accounting: A multi-scale approach based on net primary productivity

The Ecological footprint accounting is a resource accounting tool that is used to track the sustainability of human systems. In this paper, we present a new approach to calculate the Ecological Footprint metrics at different geographic scales using Net Primary Productivity data. Our study focuses on the town of Afourar, Morocco, as a case study examined at three different scales; national, regional, and provincial scale. In contrast with other studies, our footprint accounting results are expressed in what we have called territorial hectares. The accounting results show that geographic scale has a significant influence on the footprint model, where three cases of sustainability were found. This implies that the efforts to maintain the sustainability of territories are more important at some scales than others. We argue that the relationship between sustainability and geographic scale is both strong and complex and that sustainability is a spatially relative concept. Therefore, we conclude that multi-scale analysis is crucial for making sustainable decisions and management policies.     

Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU

Investments in power generation constitute a typical budget allocation problem in the context of multiple objectives, while all factors influencing investor’s decisions for power plants are subject to considerable uncertainties. The paper introduces a multi-objective stochastic model designed to optimize budget allocation decisions for power generation in the context of risk aversion taking into account several sources of uncertainty, especially with regard to volatility of fossil fuel and electricity prices, technological costs, and climate policy variability. Probability distributions for uncertain factors influencing investment decisions are directly derived from the stochastic global energy model PROMETHEUS and thus they take into account complex interactions between variables in the systemic context. In order to fully incorporate stochastic characteristics of the problem, the model is specified as an optimization problem in which the probability that an objective exceeds a given threshold is maximized (risk aversion) subject to a set of deterministic and probabilistic constraints. The model is formulated as a mixed integer program providing complete flexibility on the joint distributions of rates of return of technologies competing for investments, as it can handle non-symmetric distributions and take automatically into account complex covariance patterns as emerging from comprehensive PROMETHEUS stochastic results. The analysis shows that risk is a crucial factor for power generation investments with investors not opting for technologies subject to uncertainty related to climate policies and fossil fuel prices. On the other hand, combination of options with negative covariance tends to benefit in the context of risk-hedging behavior.     

Uncertainty Assessment of Voc Emissions from Paint in the Netherlands Using the Nusap System

We demonstrate an innovative approach to uncertainty assessment known as the NUSAP system, to assess qualitative and quantitative uncertainty for the case of emissions of volatile organic compounds (VOC) from paint in The Netherlands. Using expert elicitation, we identified key sources of error, critical assumptions, and bias in the monitoring process. We assessed pedigree and probabilistic uncertainty of all input quantities. We used four pedigree criteria to assess the strength of the knowledge base: proxy representation, empirical basis, methodological rigour and degree of validation. Using Monte Carlo analysis, we assessed sensitivity and propagation of uncertainty. Results for sensitivity and pedigree were combined in a NUSAP Diagnostic Diagram, which effectively highlighted the assumption for VOC percentage of imported paint as the weakest spot in the monitoring of VOC emissions. We conclude that NUSAP facilitates systematic scrutinization of method and underlying assumptions and structures creative thinking on sources of error and bias. It provides a means to prioritise uncertainties and focus research efforts on the potentially most problematic parameters and assumptions, at the same time identifying specific weaknesses in the knowledge base. With NUSAP, nuances of meaning about quantities can be conveyed concisely and clearly, to a degree that is not possible with statistic methods only.     

Coping with uncertainty in environmental impact assessments: Open techniques

Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which the EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries.     

Who cares? Don't underestimate the values of SEA monitoring!

Until now, monitoring of large-scale regional funding programmes has been rare, although their large scope and abstract planning targets generally involve high levels of uncertainty. This study applies and examines a newly developed methodological approach for monitoring such programmes. It also critically reflects to what extent the Strategic Environmental Assessment (SEA) contributes to a better consideration of environmental sustainability and to a learning effect among the stakeholders as well as within the decision-making process. The interviews conducted during the SEA monitoring revealed a very low recognition of the SEA, and its content, among project applicants of the transnational regional funding programme. They further show that more information on the SEA and its recommendations to mitigate negative environmental impacts would be beneficial in the future. Overall, the monitoring confirmed, however, that the institutions responsible for the programme were aware of the benefits of considering environmental sustainability. The long-term application of SEA in an iterative process provided positive learning effects on environmental sustainability and awareness for environmental aspects. This study also shows how SEA monitoring can serve as a tool to enhance visibility and foster communication among decision makers and applicants.     

Fragmentary provisions for uncertainty disclosure and consideration in EA legislation,regulations and guidelines and the need for improvement

The consideration and disclosure of uncertainties is fundamental to a credible EA process, but little is known about the nature and type of requirements and guidance available to proponents, practitioners and decision makers about how to deal with uncertainties. This paper examines the provisions for considering and disclosing uncertainties in EA. Methods are based on a comparative review of uncertainty provisions in EA legislation, regulations and guidance documents under Canadian federal, provincial and territorial jurisdictions. Results show 10 types of provisions applied at different stages of the EA process with considerable jurisdictional variability and incoherence. The most common provision was that decision makers can request that project proponents provide more information, followed by the preparation of contingency plans, and that practitioners document their assumptions about data reliability. Most of these provisions were found in guidelines, versus legislation or regulations; and most addressed impact management, with very few provisions for addressing uncertainty during EA review and decision making. Current practices of uncertainty (non)disclosure and (non)consideration in EA can be explained, in part, by the superficial nature and limited extent of the requirements and guidance made available to EA practitioners, proponents, and decision makers. The existing requirements placed on proponents and practitioners to disclose and consider uncertainties are necessary, but insufficient. Stronger, more coherent and transparent requirements for those tasked with EA review and decision making to consider uncertainty information when disclosed, and the development of practical guidance on how to do so, are needed.     

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.     

Industrial point source CO<Subscript>2</Subscript> emission strength estimation with aircraft measurements and dispersion modelling

CO₂ remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO₂ emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO₂ industrial point source, located in Biganos, France. CO₂ density measurements were obtained by applying the mass balance method, while CO₂ emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.     

Sizing an Off-stream Reservoir with Respect to Water Availability,Water Quality,and Biological Integrity

Sizing a new reservoir is a challenging task, which normally requires simultaneously a cost-effective, risk-informed, and forward-looking decision analysis with respect to basin-wide hydrological features, environmental quality, and biological integrity. Such a sustainable planning approach takes into account the global trend to balance the needs of economic growth, ecological conservation, and environmental protection. To achieve the goal of sustainability, emphasis in this paper was placed upon the correlation of three physical, chemical, and biological indices, including the dissolved oxygen (DO), the 5-day biochemical oxygen demand (BOD₅), and the index of biotic integrity (IBI), for the optimal planning of a reservoir in a river basin. This new methodological paradigm has been employed for sizing an off-stream reservoir in the Hou-Lung River Basin, central Taiwan. The internal linkage between the water quality parameters (DO and BOD₅) and the IBI levels further enables us to formulate a special biotic integrity constraint which reflects fish community attributes to suit a relatively low-density and unspecialized freshwater fish fauna in response to the changing water quality conditions in the river basin. The tradeoffs among economic, environmental, and ecological aspects for reservoir sizing can then be based on the river flow patterns, the water demand, the water quality standards, and the anticipated biological integrity in some critical river reaches. Findings in a preliminary case study suggest that an optimal pumping scheme may be smoothly maintained on a yearly basis within a combined multicriteria and multiobjective decision-making process.