Characterizing,Propagating, and Analyzing Uncertainty in Life‐Cycle Assessment: A Survey of Quantitative Approaches

Life‐cycle assessment (LCA) practitioners build models to quantify resource consumption, environmental releases, and potential environmental and human health impacts of product systems. Most often, practitioners define a model structure, assign a single value to each parameter, and build deterministic models to approximate environmental outcomes. This approach fails to capture the variability and uncertainty inherent in LCA. To make good decisions, decision makers need to understand the uncertainty in and divergence between LCA outcomes for different product systems. Several approaches for conducting LCA under uncertainty have been proposed and implemented. For example, Monte Carlo simulation and fuzzy set theory have been applied in a limited number of LCA studies. These approaches are well understood and are generally accepted in quantitative decision analysis. But they do not guarantee reliable outcomes. A survey of approaches used to incorporate quantitative uncertainty analysis into LCA is presented. The suitability of each approach for providing reliable outcomes and enabling better decisions is discussed. Approaches that may lead to overconfident or unreliable results are discussed and guidance for improving uncertainty analysis in LCA is provided.     

Fisheries stock assessment and decision analysis: the Bayesian approach

The Bayesian approach to stock assessment determines the probabilities of alternative hypotheses using information for the stock in question and from inferences for other stocks/species. These probabilities are essential if the consequences of alternative management actions are to be evaluated through a decision analysis. Using the Bayesian approach to stock assessment and decision analysis it becomes possible to admit the full range of uncertainty and use the collective historical experience of fisheries science when estimating the consequences of proposed management actions. Recent advances in computing algorithms and power have allowed methods based on the Bayesian approach to be used even for fairly complex stock assessment models and to be within the reach of most stock assessment scientists. However, to avoid coming to ill-founded conclusions, care must be taken when selecting prior distributions. In particular, selection of priors designed to be noninformative with respect to quantities of interest to management is problematic. The arguments of the paper are illustrated using New Zealand's western stock of hoki, Macruronus novaezelandiae (Merlucciidae) and the Bering--Chukchi--Beaufort Seas stock of bowhead whales as examples     

Scientific and societal considerations in selecting assessment endpoints for environmental decision making

It is sometimes argued that, from an ecological point of view, population-, community-, and ecosystem-level endpoints are more relevant than individual-level endpoints for assessing the risks posed by human activities to the sustainability of natural resources. Yet society values amenities provided by natural resources that are not necessarily evaluated or protected by assessment tools that focus on higher levels of biological organization. For example, human-caused stressors can adversely affect recreational opportunities that are valued by society even in the absence of detectable population-level reductions in biota. If protective measures are not initiated until effects at higher levels of biological organization are apparent, natural resources that are ecologically important or highly valued by the public may not be adequately protected. Thus, environmental decision makers should consider both scientific and societal factors in selecting endpoints for ecological risk assessments. At the same time, it is important to clearly distinguish the role of scientists, which is to evaluate ecological effects, from the role of policy makers, which is to determine how to address the uncertainty in scientific assessment in making environmental decisions and to judge what effects are adverse based on societal values and policy goals.     

Adequacy Conditions for Reporting Uncertainty in Chemical Risk Assessments

Uncertainty may influence decision-making. A prerequisite for a decision to be well founded is thus that scientific experts inform decision-makers about all decision relevant uncertainty. A set of conditions is provided for adequate characterization of scientific uncertainty for the purposes of regulatory decision-making. These conditions require specification of (1) the character and degree of uncertainty about the assessment variables, (2) the possibility of reducing the uncertainty, and (3) the degree of agreement among experts. Furthermore, it is required that (4) the information covered by the previous conditions is presented in a clear and comprehensible way. The point of departure is that characterizing scientific uncertainty conceptually means specifying all potentially important possibilities that are consistent with the state of scientific knowledge. The conditions are intended to be applied to human health risk assessment of chemicals. However, the basic approach, to consider potentially important possibilities, should be useful also to environmental, and site-specific risk assessment.     

Can science justify regulatory decisions about the cultivation of transgenic crops?

Results of scientific studies are sometimes claimed to provide scientific justification for regulatory decisions about the cultivation of certain transgenic crops. A decision may be scientifically justified if objective analysis shows that the decision is more likely than alternatives to lead to the achievement of specific policy objectives. If policy objectives are not defined operationally, as is often the case, scientific justification for decisions is not possible. The search for scientific justification for decisions leads to concentration on reducing scientific uncertainty about the behaviour of transgenic crops instead of reducing uncertainty about the objectives of policies that regulate their use. Focusing on reducing scientific uncertainty at the expense of clarifying policy objectives may have detrimental effects on scientists, science and society.     

Probabilistic Environmental Risk Assessment for Dibutylphthalate (DBP)

In the risk assessment methods for new and existing chemicals in the European Union (EU), environmental “risk” is characterized by the deterministic quotient of exposure and effects (PEC/PNEC). From a scientific viewpoint, the uncertainty in the risk quotient should be accounted for explicitly in the decision making, which can be done in a probabilistic risk framework. To demonstrate the feasibility and benefits of such a framework, a sample risk assessment for an existing chemical (dibutylphthalate, DBP) is presented in this paper. The example shows a probabilistic framework to be feasible with relatively little extra effort; such a framework also provides more relevant information. The deterministic risk quotients turned out to be worst cases at generally higher than the 95th percentile of the probability distributions. Sensitivity analysis proves to be a powerful tool in identifying the main sources of uncertainty and thus will be effective for efficient further testing. The distributions assigned to the assess ment factors (derivation of the PNEC) dominate the total uncertainty in the risk assessment; uncertainties in the release estimates come second. Large uncertainties are an inherent part of risk assessment that we have to deal with quantitatively. However, the most appropriate way to characterise effects and risks requires further attention. Recommendations for further study are identified.     

Analysis and Portrayal of Uncertainty in a Food-Web Exposure Model

The results of quantitative risk assessments are key factors in a risk manager's decision of the necessity to implement actions to reduce risk. The extent of the uncertainty in the assessment will play a large part in the degree of confidence a risk manager has in the reported significance and probability of a given risk. The two main sources of uncertainty in such risk assessments are variability and incertitude. In this paper we use two methods, a second-order two-dimensional Monte Carlo analysis and probability bounds analysis, to investigate the impact of both types of uncertainty on the results of a food-web exposure model. We demonstrate how the full extent of uncertainty in a risk estimate can be fully portrayed in a way that is useful to risk managers. We show that probability bounds analysis is a useful tool for identifying the parameters that contribute the most to uncertainty in a risk estimate and how it can be used to complement established practices in risk assessment. We conclude by promoting the use of probability analysis in conjunction with Monte Carlo analyses as a method for checking how plausible Monte Carlo results are in the full context of uncertainty.     

Using and communicating uncertainty for the effective control of invasive non-native species

Estimates of quantities needed to plan invasive species control, such as population size, are always uncertain; this is an issue that can become a problem when mishandled in ecological science and its communication. The complexities of incorporating uncertainty into sophisticated decision-support tools may be a barrier to their use by decision makers, leading to decisions being made without due regard to uncertainty and risking misplaced certainty of predicted outcomes. We summarise ways in which uncertainty has been incorporated into and used to advise decisions on the management of invasive non-native species and other problem species, and offer a simple conceptual model for accommodating and using uncertainty at the planning stage. We also demonstrate how frequently uncertainty has been misused and miscommunicated in the wildlife management literature. We contend that uncertainty in estimates of natural quantities must be acknowledged, can inform decisions and can be made to derive decisions, and should not be ignored if invasive species policy is to be delivered effectively. Uncertainty must be communicated thoroughly and correctly by scientists if decision makers are to understand its consequences for planning and resourcing control programmes.     

Expert Views on Regulatory Preparedness for Managing the Risks of Nanotechnologies

The potential and promise of nanotechnologies depends in large part on the ability for regulatory systems to assess and manage their benefits and risks. However, considerable uncertainty persists regarding the health and environmental implications of nanomaterials, hence the capacity for existing regulations to meet this challenge has been widely questioned. Here we draw from a survey (N=254) of US-based nano-scientists and engineers, environmental health and safety scientists, and regulatory scientists and decision-makers, to ask whether nano experts regard regulatory agencies as prepared for managing nanomaterial risks. We find that all three expert groups view regulatory agencies as unprepared. The effect is strongest for regulators themselves, and less so for scientists conducting basic, applied, or health and safety work on nanomaterials. Those who see nanotechnology risks as novel, uncertain, and difficult to assess are particularly likely to see agencies as unprepared. Trust in regulatory agencies, views of stakeholder responsibility regarding the management of risks, and socio-political values were also found to be small but significant drivers of perceived agency preparedness. These results underscore the need for new tools and methods to enable the assessment of nanomaterial risks, and to renew confidence in regulatory agencies’ ability to oversee their growing use and application in society.     

Life cycle assessment of emerging technologies: A review

In recent literature, prospective application of life cycle assessment (LCA) at low technology readiness levels (TRL) has gained immense interest for its potential to enable development of emerging technologies with improved environmental performances. However, limited data, uncertain functionality, scale up issues and uncertainties make it very challenging for the standard LCA guidelines to evaluate emerging technologies and requires methodological advances in the current LCA framework. In this paper, we review published literature to identify major methodological challenges and key research efforts to resolve these issues with a focus on recent developments in five major areas: cross‐study comparability, data availability and quality, scale‐up issues, uncertainty and uncertainty communication, and assessment time. We also provide a number of recommendations for future research to support the evaluation of emerging technologies at low technology readiness levels: (a) the development of a consistent framework and reporting methods for LCA of emerging technologies; (b) the integration of other tools with LCA, such as multicriteria decision analysis, risk analysis, technoeconomic analysis; and (c) the development of a data repository for emerging materials, processes, and technologies.     

Incorporating uncertainty and social values in managing invasive alien species: a deliberative multi-criteria evaluation approach

The management of Invasive Alien Species (IAS) is stymied by complex social values and severe levels of uncertainty. However, these two challenges are often hidden in the conventional model of management by “value-free” analyses and probability-based estimates of risk. As a result, diverse social values and wide margins of error in risk assessment carry zero weights in the decision-making process, leaving IAS risk decisions to be made in the wake of political pressure and the crisis atmosphere of incursion. We propose to use a Deliberative Multi-Criteria Evaluation (DMCE) to incorporate multiple social values and profound uncertainty into decision-making processes. The DMCE process combines the advantages of conventional multi-criteria decision analysis methods with the benefits of stakeholder participation to provide an analytical structure to assess complex multi-dimensional objectives. It, therefore, offers an opportunity for diverse views to enter the decision-making process, and for the negotiation of consensus positions. The DMCE process can also function as a platform for risk communication in which scientists, stakeholders, and decision-makers can interact and discuss the uncertainty associated with biological invasions. We examine two case studies that demonstrate how DMCE provides scientific rigor and transparency in the decision-making process of invasion risk management. The first case regards pre-border priority ranking for potential invasive species and the second relates to selecting the most desirable policy option for managing a post-border invader.     

Hybrid Framework for Managing Uncertainty in Life Cycle Inventories

Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input–output (I‐O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom‐up process model can be estimated via a top‐down approach such as the economic I‐O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long‐term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method.     

Risk communication and decision tools for children's health protection

Scientific discovery linking the environment to beneficial and adverse health children's health outcomes is rapidly expanding, leading scientists and health professionals to call for timely action to prevent harm and secure benefits. A robust method to synthesize what is known about the environmental drivers of health is a foundational step to making the science actionable by individuals and decision‐makers. To meet this need, a methodology called the Navigation Guide was crafted by a collaboration of 22 clinical and environmental health scientists. The Navigation Guide proceeds from methods of research synthesis used in clinical settings but accounts for differences between environmental and clinical health sciences related to the evidence‐base and decision‐context. The methodology can be used to develop evidence profiles that provide simple, transparent summaries, such as practice guidelines or other evidence‐based recommendations for prevention. Establishing proof‐of‐concept of the method is underway. Development of the Navigation Guide is extremely timely as it coincides with growing recognition of the need for updated methods in risk assessment. The costs in 2008 to the US healthcare system for treatment of childhood illnesses linked to toxic environmental exposures is conservatively estimated to be over $76 billion, and it is anticipated that US healthcare policy decisions will increasingly rely on systematic reviews of the evidence. The Navigation Guide is poised to provide a methodological bridge to link healthcare decision‐making to efforts to reduce toxic environmental exposures. The institutionalization of the Navigation Guide would provide a concrete mechanism for linking science to action to protect children's health. Birth Defects Research (Part C) 99:45–49, 2013. © 2013 Wiley Periodicals, Inc.     

Fed‐batch and perfusion culture processes: Economic,environmental, and operational feasibility under uncertainty

This article evaluates the current and future potential of batch and continuous cell culture technologies via a case study based on the commercial manufacture of monoclonal antibodies. The case study compares fed‐batch culture to two perfusion technologies: spin‐filter perfusion and an emerging perfusion technology utilizing alternating tangential flow (ATF) perfusion. The operational, economic, and environmental feasibility of whole bioprocesses based on these systems was evaluated using a prototype dynamic decision‐support tool built at UCL encompassing process economics, discrete‐event simulation and uncertainty analysis, and combined with a multi‐attribute decision‐making technique so as to enable a holistic assessment. The strategies were compared across a range of scales and titres so as to visualize how their ranking changes in different industry scenarios. The deterministic analysis indicated that the ATF perfusion strategy has the potential to offer cost of goods savings of 20% when compared to conventional fed‐batch manufacturing processes when a fivefold increase in maximum viable cell densities was assumed. Savings were also seen when the ATF cell density dropped to a threefold increase over the fed‐batch strategy for most combinations of titres and production scales. In contrast, the fed‐batch strategy performed better in terms of environmental sustainability with a lower water and consumable usage profile. The impact of uncertainty and failure rates on the feasibility of the strategies was explored using Monte Carlo simulation. The risk analysis results demonstrated the enhanced robustness of the fed‐batch process but also highlighted that the ATF process was still the most cost‐effective option even under uncertainty. The multi‐attribute decision‐making analysis provided insight into the limited use of spin‐filter perfusion strategies in industry. The resulting sensitivity spider plots enabled identification of the critical ratio of weightings of economic and operational benefits that affect the choice between ATF perfusion and fed‐batch strategies. Biotechnol. Bioeng. 2013; 110: 206–219. © 2012 Wiley Periodicals, Inc.     

Comprehensive Realism's Weight-of-Evidence Based Distributional Dose-Response Characterization

Challenges to low-dose linearity and other default assumptions in cancer risk assessment and the limitations associated with NOAELs, LOAELs, and constant uncertainty factor values in the evaluation of noncancer health effects have stimulated the continued evolution of risk assessment methodologies. The increasing need for more realistic estimates of the dose-response relationship, better uncertainty characterization, and greater utilization of cost-benefit analyses have also contributed to this evolution. “Comprehensive Realism” is an emerging quantitative weight-of-evidence based risk assessment methodology for both cancer and noncancer health effects which utilizes probability distributions and decision analysis techniques to reflect more of the relevant human exposure data, more of the available and pertinent human and animal dose-response data, and the current state of knowledge about the relative plausibility of alternative dose-response analyses. A tree (like a decision tree and a probability tree) is used to decompose the dose-response assessment into component factors, to provide a structure for explicitly considering multiple alternatives for each factor, and to explicitly incorporate the current state of knowledge about the relative plausibility of these alternatives. Groundbreaking work has demonstrated the feasibility of weight-of-evidence based distributional characterizations, and provided initial examples. Computer software implementations are also available.     

Types of Integration in Risk Assessment and Management,And Why They Are Needed

Risk-based decision making requires that the decision makers and stakeholders are informed of all risks that are potentially significant and relevant to the decision. The International Programme on Chemical Safety of the World Health Organization has developed a framework for integrating the assessment of human health and ecological risks. However, other types of integration are needed to support particular environmental decisions. They are integration of exposure and effects, of multiple chemicals and other hazardous agents, of multiple routes of exposure, of multiple endpoints, multiple receptors, multiple spatial and temporal scales, a product's life cycle, management alternatives, and socioeconomics with risk assessment. Inclusion of all these factors in an integrated assessment could lead to paralysis by analysis. Therefore, it is important that assessors be cognizant of the decision process and that decision makers and those who will influence the decision (stakeholders) be involved in planning the assessment to ensure that the degree of integration is necessary and sufficient.     

Harmonizing the Incorporation of Uncertainty and Variability Into Risk Assessment: An International Approach

International harmonization of risk assessment approaches affords a number of opportunities and advantages. Overall, harmonization will lead to more efficient use of resources, but also will lead to better understanding amongst scientists and regulators worldwide. It is with these goals in mind that in 1994 the International Programme on Chemical Safety (IPCS) initiated its Project on the Harmonization of Approaches to the Assessment of Risk from Exposure to Chemicals (Harmonization Project). An ongoing activity under this project addresses uncertainty and variability in risk assessment. The goal of the overall activity is to promote harmonization of risk assessment methodologies for noncancer endpoints. However, given the common links in uncertainty and variability that apply across a range of end-point-specific activities, these links are identified wherever possible. This paper provides an overview of the IPCS Harmonization Project and reviews the activity and future plans related to uncertainty and variability.     

Application typologies for life cycle assessment

Different lists of application areas for life cycle assessment are reviewed together with some suggestions for a typology of these application areas. It is concluded that the scope of a life cycle assessment is determined by the area of validity of the decision with respect to time, space, and interest groups affected. On this basis, six application areas are distinguished. It is further concluded that the application area has limited influence on the inventory analysis and impact assessment phases, although these may be influenced significantly by the decision-maker and the complexity of the trade-offs between the involved environmental impacts. The reporting format for a life cycle assessment depends on the socio-economic importance of the decision, the intended audience, and the time available for decision making.     

Critical Components of Uncertainty Communication in Life Cycle Assessments of Emerging Technologies

Because of their recognition as a comprehensive tool of environmental assessments and their increasing use by governments and industries, life cycle assessments (LCAs) are positioned to be prominent sources of mass media information on new products and technologies. The LCA studies underlying media reports are often viewed by nonexperts after the initial reporting. However, uncertainty is rife in early assessments of emerging technologies, and LCA's ability to inform environmental opinions and decisions is limited without the accompanying communication on uncertainty. Though approaches to the technical aspects of uncertainty analysis in LCA are available in the literature, those on communicating that uncertainty, in ways that are cognitively accessible to the nonexperts, are still lacking despite their highlighted importance across various disciplines. With the focus on communication, this article uses the existing literature to derive five criteria for making uncertainty communication accessible to a nonexpert audience. Then, LCAs on engineered nanomaterial (ENM) and ENM‐enabled products, as a case study of emerging technologies where uncertainties abound, are reviewed for whether they meet these five criteria. The study concludes with recommendations for communicating uncertainty in LCAs in order to enhance their role as decision‐ and public opinion–informing assessments.