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.     

Role of and challenges to environmental impact assessment proponents in Pakistan

This study identified the role of and challenges faced by Environmental Impact Assessment (EIA) proponents in Punjab, Pakistan. Expected roles of proponents in EIA were taken from regulations, legislation and guidelines. The comments of consultants, Environmental Protection Agency (EPA) and non-governmental organisations (NGOs) regarding the role played by proponents were extracted from literature and used for evaluation. To identify the challenges of proponents in each step of the EIA, 40 semi-structured interviews were conducted with private and government proponents in Punjab. Oftentimes, projects start prior to obtaining an environmental approval. Proper scoping is seldom conducted. Stakeholder involvement in EIA is limited. Proponents sometimes do not share complete project information with consultants, which compromises the report quality and timely decision making. Moreover, some proponents attempt to influence the review and decision making and do not ensure compliance to approval conditions except for few multinationals. The key challenge highlighted by proponents was the discrimination on part of the EPA between private and government projects. Other challenges included lack of professionalism of some consultants and delayed and non-transparent decision making. Although regional in scope, the results of the study hold importance for EIA systems worldwide particularly in countries with similar economic systems who are facing a trade-off between economic growth and environmental sustainability.     

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.     

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.     

A multicriteria analytical framework for sustainability evaluation under methodological uncertainties

Multicriteria analysis is widely used to perform sustainability evaluation for purposes such as decision making or progress assessment following a chosen sustainable development concept. The stages of multicriteria analysis include indicator selection, data characterization, normalization, weighting, and aggregation. However, due to the various framings of sustainability, non-equivalent approaches could be adopted at each stage, introducing methodological uncertainty. Consequently, depending on the methods chosen, divergent and conflicting conclusions or decisions may result. This paper addresses the issue of methodological uncertainties in sustainability evaluation by analyzing how methodological uncertainties arise during multicriteria analysis, then proposing an analytical framework that employs uncertainty and sensitivity analyses to quantify and manage the effects of methodological uncertainties. The consideration of methodological uncertainties in the structure of multicriteria sustainability evaluation shifts the analysis from deterministic to probabilistic, which is advantageous to arrive at robust and homogenized sustainability conclusions or decisions.     

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.     

Consideration of climate change on environmental impact assessment in Spain

Most of the projects subject to environmental impact assessment (EIA) are closely related to climate change, as they contribute to or are affected by it. The growing certainty about climate change and its impacts makes its consideration an essential part of the EIA process, as well as in strategic environmental assessment (SEA).This paper examines how climate change (CC) has been taken into account in EIA in Spain through the analysis of 1713 environmental records of decision (RODs) of projects submitted for EIA. In 2013 Spain approved one of the most advanced laws in terms of CC consideration in environmental assessment, although it had not yet accumulated extensive practice on the issue. This contrasts with the situation of countries like Canada or the USA, which have a significant body of experience without specific legal requirements.Only 14% of the RODs analysed included references to CC, and in more than half of the cases it was a mere citation. Thermal power plants, which are subject to specific GHG regulations, show the highest consideration, while transport infrastructures, which are important contributors to CC, show a very low consideration. Almost all the references are related to their contribution to CC, while consideration of the effects of CC is minimal.The increasingly common incorporation of CC into SEA, should not imply its exclusion from EIA, because both processes have different aims and uses. Including the obligation to consider CC in the EIA regulations is highly desirable, but probably not enough without other measures, such as practical guidance, training and motivational programmes for practitioners and evaluators. But even these actions cannot ensure effective and adequate assessments of CC. Probably more resources should be spent on creating greater awareness in all the agents involved in EIA.     

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.     

Integrated Assessment: an emerging methodology for complex issues

Over recent years Integrated Assessment (IA) has been presented as a new and innovative approach to modern decision making. In this paper we explore some of the key features that we consider characterise IA; we present IA as a framework that allows a flexible approach to uncertainty in decision making and to which a broad palette of expertise can contribute. The example of the development of an international agreement to reduce acidic deposition is used to illustrate the current practical status of an IA. The scientific process leading to this agreement has previously been described as IA but we argue that, although it marks a change from traditional approaches, further progress is still required to satisfy the requirements for a successful and durable IA.     

Underwater noise modelling for environmental impact assessment

Assessment of underwater noise is increasingly required by regulators of development projects in marine and freshwater habitats, and noise pollution can be a constraining factor in the consenting process. Noise levels arising from the proposed activity are modelled and the potential impact on species of interest within the affected area is then evaluated. Although there is considerable uncertainty in the relationship between noise levels and impacts on aquatic species, the science underlying noise modelling is well understood. Nevertheless, many environmental impact assessments (EIAs) do not reflect best practice, and stakeholders and decision makers in the EIA process are often unfamiliar with the concepts and terminology that are integral to interpreting noise exposure predictions. In this paper, we review the process of underwater noise modelling and explore the factors affecting predictions of noise exposure. Finally, we illustrate the consequences of errors and uncertainties in noise modelling, and discuss future research needs to reduce uncertainty in noise assessments.     

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.     

Meaningful and efficient? Enduring challenges to Aboriginal participation in environmental assessment

This paper explores the underlying practice-based challenges to meaningful and efficient Aboriginal participation in environmental assessment (EA) - participation that provides meaningful opportunities for Aboriginal communities to shape EA, yet assures a degree of efficiency for project proponents who need to obtain EA approvals in a timely and financially viable manner. We do so based on an analysis of the EA policy community's experience with uranium exploration and mining in Saskatchewan, Canada. Many of the challenges to meaningful and efficient Aboriginal participation that emerged are multi-dimensional, often concerning participation processes, decision-making, and relationships. Although scholars have explored many of these issues and have proposed numerous solutions, challenges persist in practice. Several other issues also emerged from our study that have received limited attention, including the non-commitment to early and ongoing participation by smaller project proponents, and the EA exemption of exploration projects; the limited availability of information to project developers on local right holders and Aboriginal interests; expectations about the integration of traditional knowledge and land use in EA not aligning with the information that is available to proponents; confusion about who is responsible for initiating early participation and consultation processes; the lack of early relationship building with potentially affected communities, particularly by governments; and the lack of other viable avenues, outside EA, for Aboriginal communities to raise more strategic issues of concern that affect traditional lands and treaty rights.     

Approaches for performing uncertainty analysis in large-scale energy/economic policy models

A number of key policy insights have emerged from the application of large-scale economic/energy models, such as integrated assessment models for climate change. These insights have been particularly powerful in those instances when they are shared by all or most of the existing models. On the other hand, some results and policy recommendations obtained from integrated assessment models vary widely from model to model. This can limit their usability for policy analysis. The differences between model results are mostly due to different underlying assumptions about exogenous processes, about endogenous processes and the dynamics among them, differences in value judgments, and different approaches for simplifying model structure for computational purposes. Uncertainty analyses should be performed for the dual purpose of clarifying the uncertainties inherent in model results and improving decision making under uncertainty. This paper develops a unifying framework for comparing the different types of uncertainty analyses through their objective functions, categorizes types of uncertainty analyses that can be performed on large models, and compares different approaches to uncertainty analysis by explaining underlying assumptions, suitability for different model types, and advantages and disadvantages. The appendix presents a summary of integrated assessment models for climate change that explicitly account for uncertainty.     

Optimization and Decision Heuristics for Chesapeake Bay Nutrient Reduction Strategies

Regional policies to achieve water quality goals assign a unique pollution control technology to every pollution source in a watershed, thereby defining a watershed strategy. For watersheds with even a modest number of pollution sources and control alternatives, the decision problem has combinatorial complexity. The perception of complexity—manifested in innumerable feasible watershed strategies—commonly induces the use of simplifying decision heuristics and ad hoc decision rules that reduce decision complexity by limiting the choice set to a “manageable” number of alternatives. In problems with large complex choice sets, these decision heuristics simplify decision making by excluding the vast majority of feasible alternatives a priori. In contrast, watershed-scale optimization enables decision makers to consider all feasible alternatives implicitly, exploiting rather than restricting the complexity of the feasible choice set. This contrast is illustrated using mixed-integer linear programming to identify interstate watershed strategies that achieve Chesapeake Bay nutrient reduction goals for the Potomac River Basin. The use of optimization in collaborative decision making helped refine and capture decision makers’ underlying values and preferences in policy-relevant constraints reflecting equity and political feasibility. Optimization formulations incorporating these constraints identified more effective and desirable management alternatives that would not otherwise have been considered using familiar decision heuristics and traditional comparisons among a limited number of ad hoc scenarios. Incorporating optimization in collaborative decision making generated superior watershed strategies and eased the cognitive limitations on decision making by substituting the computational burden of solving mixed-integer linear programs for decision makers’ cognitive burden of enumerating alternatives and scenarios for environmental systems with combinatorial complexity.     

Consideration of scales in offshore wind environmental impact assessments

Quality of environmental impact assessments (EIAs) has been criticized, in part due to a lack of accounting in these tools for differing spatial and temporal scales inherent in ecological data. In the United States, leases of outer continental shelf blocks for offshore wind projects and their construction and operation plans require EIAs in accordance with the National Environmental Policy Act of 1969 and the 1978 Council on Environmental Quality Regulations for Implementing the Procedural Provisions of the National Environmental Policy Act. This study evaluated consideration of spatiotemporal scales of stressors, receptors (specifically cetaceans), and effects in eight federal offshore wind energy EIAs against 26 criteria extracted from federal regulations. The criteria analysis determined that EIAs do not consistently or comprehensively address spatiotemporal scales with respect to federal requirements. Deficiencies in addressing spatiotemporal scales may result from imprecise regulations, intent to simplify encyclopedic documents, or lack of data resulting in incomplete assessments, inappropriate mitigation actions, and projects delays. Recommendations to improve compliance with federal regulations include making federal guidance binding, focusing on non-trivial impacts of species, tiering information, and incorporating outcomes of marine spatial planning.     

An Inexact Fuzzy-robust Two-stage Programming Model for Managing Sulfur Dioxide Abatement Under Uncertainty

In this study, an inexact fuzzy-robust two-stage programming (IFRTSP) method is developed for tackling multiple forms of uncertainties that can be expressed as discrete intervals, probabilistic distributions and/or fuzzy membership functions. The model can reflect economic penalties of corrective measures against any infeasibilities arising due to a particular realization of system uncertainties. Moreover, the fuzzy decision space can be delimited into a more robust one with the uncertainties being specified through dimensional enlargement of the original fuzzy constraints. A management problem in terms of regional air pollution control has been studied to illustrate the applicability of the proposed approach. Results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers identify desired pollution-abatement strategy with minimized system cost and maximized environmental efficiency.     

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.     

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.     

Monitoring: The missing piece: A critique of NEPA monitoring

The U.S. National Environmental Policy Act (NEPA) of 1969 heralded in an era of more robust attention to environmental impacts resulting from larger scale federal projects. The number of other countries that have adopted NEPA's framework is evidence of the appeal of this type of environmental legislation. Mandates to review environmental impacts, identify alternatives, and provide mitigation plans before commencement of the project are at the heart of NEPA. Such project reviews have resulted in the development of a vast number of reports and large volumes of project-specific data that potentially can be used to better understand the components and processes of the natural environment and provide guidance for improved and efficient environmental protection. However, the environmental assessment (EA) or the more robust and intensive environmental impact statement (EIS) that are required for most major projects more frequently than not are developed to satisfy the procedural aspects of the NEPA legislation while they fail to provide the needed guidance for improved decision-making. While NEPA legislation recommends monitoring of project activities, this activity is not mandated, and in those situations where it has been incorporated, the monitoring showed that the EIS was inaccurate in direction and/or magnitude of the impact. Many reviews of NEPA have suggested that monitoring all project phases, from the design through the decommissioning, should be incorporated. Information gathered though a well-developed monitoring program can be managed in databases and benefit not only the specific project but would provide guidance how to better design and implement future activities designed to protect and enhance the natural environment.     

Sensitivity analysis of water quality for Delhi stretch of the River Yamuna,India

Simulation models are used to aid the decision makers about water pollution control and management in river systems. However, uncertainty of model parameters affects the model predictions and hence the pollution control decision. Therefore, it often is necessary to identify the model parameters that significantly affect the model output uncertainty prior to or as a supplement to model application to water pollution control and planning problems. In this study, sensitivity analysis, as a tool for uncertainty analysis was carried out to assess the sensitivity of water quality to (a) model parameters (b) pollution abatement measures such as wastewater treatment, waste discharge and flow augmentation from upstream reservoir. In addition, sensitivity analysis for the “best practical solution” was carried out to help the decision makers in choosing an appropriate option. The Delhi stretch of the river Yamuna was considered as a case study. The QUAL2E model is used for water quality simulation. The results obtained indicate that parameters K ₁ (deoxygenation constant) and K ₃ (settling oxygen demand), which is the rate of biochemical decomposition of organic matter and rate of BOD removal by settling, respectively, are the most sensitive parameters for the considered river stretch. Different combinations of variations in K ₁ and K ₂ also revealed similar results for better understanding of inter-dependability of K ₁ and K ₂. Also, among the pollution abatement methods, the change (perturbation) in wastewater treatment level at primary, secondary, tertiary, and advanced has the greatest effect on the uncertainty of the simulated dissolved oxygen and biochemical oxygen demand concentrations.