Resilience and sustainability: Similarities and differences in environmental management applications.

In recent years there have been many disparate uses of the terms sustainability and resilience, with some framing sustainability and resilience as the same concept, and others claiming them to be entirely different and unrelated. To investigate similarities, differences, and current management frameworks for increasing sustainability and resilience, a literature review was undertaken that focused on integrated use of sustainability and resilience in an environmental management context. Sustainability was defined through the triple bottom line of environmental, social and economic system considerations. Resilience was viewed as the ability of a system to prepare for threats, absorb impacts, recover and adapt following persistent stress or a disruptive event. Three generalized management frameworks for organizing sustainability and resilience were found to dominate the literature: (1) resilience as a component of sustainability, (2) sustainability as a component of resilience, and (3) resilience and sustainability as separate objectives. Implementations of these frameworks were found to have common goals of providing benefits to people and the environment under normal and extreme operating conditions, with the best examples building on similarities and minimizing conflicts between resilience and sustainability.

Emerging Technologies for Environmental Remediation: Integrating Data and Judgment.

Emerging technologies present significant challenges to researchers, decision-makers, industry professionals, and other stakeholder groups due to the lack of quantitative risk, benefit, and cost data associated with their use. Multi-criteria decision analysis (MCDA) can support early decisions for emerging technologies when data is too sparse or uncertain for traditional risk assessment. It does this by integrating expert judgment with available quantitative and qualitative inputs across multiple criteria to provide relative technology scores. Here, an MCDA framework provides preliminary insights on the suitability of emerging technologies for environmental remediation by comparing nanotechnology and synthetic biology to conventional remediation methods. Subject matter experts provided judgments regarding the importance of criteria used in the evaluations and scored the technologies with respect to those criteria. The results indicate that synthetic biology may be preferred over nanotechnology and conventional methods for high expected benefits and low deployment costs but that conventional technology may be preferred over emerging technologies for reduced risks and development costs. In the absence of field data regarding the risks, benefits, and costs of emerging technologies, structuring evidence-based expert judgment through a weighted hierarchy of topical questions may be helpful to inform preliminary risk governance and guide emerging technology development and policy.

Balancing research and funding using value of information and portfolio tools for nanomaterial risk classification.

Risk research for nanomaterials is currently prioritized by means of expert workshops and other deliberative processes. However, analytical techniques that quantify and compare alternative research investments are increasingly recommended. Here, we apply value of information and portfolio decision analysis-methods commonly applied in financial and operations management-to prioritize risk research for multiwalled carbon nanotubes and nanoparticulate silver and titanium dioxide. We modify the widely accepted CB Nanotool hazard evaluation framework, which combines nano- and bulk-material properties into a hazard score, to operate probabilistically with uncertain inputs. Literature is reviewed to develop uncertain estimates for each input parameter, and a Monte Carlo simulation is applied to assess how different research strategies can improve hazard classification. The relative cost of each research experiment is elicited from experts, which enables identification of efficient research portfolios-combinations of experiments that lead to the greatest improvement in hazard classification at the lowest cost. Nanoparticle shape, diameter, solubility and surface reactivity were most frequently identified within efficient portfolios in our results.

How decision analysis can further nanoinformatics.

The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges.

Life cycle assessment for dredged sediment placement strategies.

Dredging to maintain navigable waterways is important for supporting trade and economic sustainability. Dredged sediments are removed from the waterways and then must be managed in a way that meets regulatory standards and properly balances management costs and risks. Selection of a best management alternative often results in stakeholder conflict regarding tradeoffs between local environmental impacts associated with less expensive alternatives (e.g., open water placement), more expensive measures that require sediment disposal in constructed facilities far away (e.g., landfills), or beneficial uses that may be perceived as risky (e.g., beach nourishment or island creation). Current sediment-placement decisions often focus on local and immediate environmental effects from the sediment itself, ignoring a variety of distributed and long-term effects from transportation and placement activities. These extended effects have implications for climate change, resource consumption, and environmental and human health, which may be meaningful topics for many stakeholders not currently considered. Life-Cycle Assessment (LCA) provides a systematic and quantitative method for accounting for this wider range of impacts and benefits across all sediment management project stages and time horizons. This paper applies a cradle-to-use LCA to dredged-sediment placement through a comparative analysis of potential upland, open water, and containment-island placement alternatives in the Long Island Sound region of NY/CT. Results suggest that, in cases dealing with uncontaminated sediments, upland placement may be the most environmentally burdensome alternative, per ton-kilometer of placed material, due to the emissions associated with diesel fuel combustion and electricity production and consumption required for the extra handling and transportation. These results can be traded-off with the ecosystem impacts of the sediments themselves in a decision-making framework.

Benefits and risks of emerging technologies: integrating life cycle assessment and decision analysis to assess lumber treatment alternatives.

Assessing the best options among emerging technologies (e.g., new chemicals, nanotechnologies) is complicated because of trade-offs across benefits and risks that are difficult to quantify given limited and fragmented availability of information. This study demonstrates the integration of multicriteria decision analysis (MCDA) and life cycle assessment (LCA) to address technology alternative selection decisions. As a case study, prioritization of six lumber treatment alternatives [micronized copper quaternary (MCQ); alkaline copper quaternary (ACQ); water-borne copper naphthenate (CN); oil-borne copper naphthenate (CNo); water-borne copper quinolate (CQ); and water-borne zinc naphthenate (ZN)] for military use are considered. Multiattribute value theory (MAVT) is used to derive risk and benefit scores. Risk scores are calculated using a cradle-to-gate LCA. Benefit scores are calculated by scoring of cost, durability, and corrosiveness criteria. Three weighting schemes are used, representing Environmental, Military and Balanced stakeholder perspectives. Aggregated scores from all three perspectives show CQ to be the least favorable alterative. MCQ is identified as the most favorable alternative from the Environmental stakeholder perspective. From the Military stakeholder perspective, ZN is determined to be the most favorable alternative, followed closely by MCQ. This type of scoring and ranking of multiple heterogeneous criteria in a systematic and transparent way facilitates better justification of technology selection and regulation.

Illustrating anticipatory life cycle assessment for emerging photovoltaic technologies.

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Stakeholder engagement in dredged material management decisions.

Dredging and disposal issues often become controversial with local stakeholders because of their competing interests. These interests tend to manifest themselves in stakeholders holding onto entrenched positions, and deadlock can result without a methodology to move the stakeholder group past the status quo. However, these situations can be represented as multi-stakeholder, multi-criteria decision problems. In this paper, we describe a case study in which multi-criteria decision analysis was implemented in a multi-stakeholder setting in order to generate recommendations on dredged material placement for Long Island Sound's Dredged Material Management Plan. A working-group of representatives from various stakeholder organizations was formed and consulted to help prioritize sediment placement sites for each dredging center in the region by collaboratively building a multi-criteria decision model. The resulting model framed the problem as several alternatives, criteria, sub-criteria, and metrics relevant to stakeholder interests in the Long Island Sound region. An elicitation of values, represented as criteria weights, was then conducted. Results show that in general, stakeholders tended to agree that all criteria were at least somewhat important, and on average there was strong agreement on the order of preferences among the diverse groups of stakeholders. By developing the decision model iteratively with stakeholders as a group and soliciting their preferences, the process sought to increase stakeholder involvement at the front-end of the prioritization process and lead to increased knowledge and consensus regarding the importance of site-specific criteria.

The value of information for managing contaminated sediments.

Effective management of contaminated sediments is important for long-term human and environmental health, but site-management decisions are often made under high uncertainty and without the help of structured decision support tools. Potential trade-offs between remedial costs, environmental effects, human health risks, and societal benefits, as well as fundamental differences in stakeholder priorities, complicate decision making. Formal decision-analytic tools such as multicriteria decision analysis (MCDA) move beyond ad hoc decision support to quantitatively and holistically rank management alternatives and add transparency and replicability to the evaluation process. However, even the best decisions made under uncertainty may be found suboptimal in hindsight, once additional scientific, social, economic, or other details become known. Value of information (VoI) analysis extends MCDA by systematically evaluating the impact of uncertainty on a decision. VoI prioritizes future research in terms of expected decision relevance by helping decision makers estimate the likelihood that additional information will improve decision confidence or change their selection of a management plan. In this study, VoI analysis evaluates uncertainty, estimates decision confidence, and prioritizes research to inform selection of a sediment capping strategy for the dibenzo-p-dioxin and -furan contaminated Grenland fjord system in southern Norway. The VoI model extends stochastic MCDA to model decisions with and without simulated new information and compares decision confidence across scenarios with different degrees of remaining uncertainty. Results highlight opportunities for decision makers to benefit from additional information by anticipating the improved decision confidence (or lack thereof) expected from reducing uncertainties for each criterion or combination of criteria. This case study demonstrates the usefulness of VoI analysis for environmental decisions by predicting when decisions can be made confidently, for prioritizing areas of research to pursue to improve decision confidence, and for differentiating between decision-relevant and decision-irrelevant differences in evaluation perspectives, all of which help guide meaningful deliberation toward effective consensus solutions.

Integrating legal liabilities in nanomanufacturing risk management.

Among other things, the wide-scale development and use of nanomaterials is expected to produce costly regulatory and civil liabilities for nanomanufacturers due to lingering uncertainties, unanticipated effects, and potential toxicity. The life-cycle environmental, health, and safety (EHS) risks of nanomaterials are currently being studied, but the corresponding legal risks have not been systematically addressed. With the aid of a systematic approach that holistically evaluates and accounts for uncertainties about the inherent properties of nanomaterials, it is possible to provide an order of magnitude estimate of liability risks from regulatory and litigious sources based on current knowledge. In this work, we present a conceptual framework for integrating estimated legal liabilities with EHS risks across nanomaterial life-cycle stages using empirical knowledge in the field, scientific and legal judgment, probabilistic risk assessment, and multicriteria decision analysis. Such estimates will provide investors and operators with a basis to compare different technologies and practices and will also inform regulatory and legislative bodies in determining standards that balance risks with technical advancement. We illustrate the framework through the hypothetical case of a manufacturer of nanoscale titanium dioxide and use the resulting expected legal costs to evaluate alternative risk-management actions.

A decision-directed approach for prioritizing research into the impact of nanomaterials on the environment and human health.

The emergence of nanotechnology has coincided with an increased recognition of the need for new approaches to understand and manage the impact of emerging technologies on the environment and human health. Important elements in these new approaches include life-cycle thinking, public participation and adaptive management of the risks associated with emerging technologies and new materials. However, there is a clear need to develop a framework for linking research on the risks associated with nanotechnology to the decision-making needs of manufacturers, regulators, consumers and other stakeholder groups. Given the very high uncertainties associated with nanomaterials and their impact on the environment and human health, research resources should be directed towards creating the knowledge that is most meaningful to these groups. Here, we present a model (based on multi-criteria decision analysis and a value of information approach) for prioritizing research strategies in a way that is responsive to the recommendations of recent reports on the management of the risk and impact of nanomaterials on the environment and human health.

Environmental radiation: risk benchmarks or benchmarking risk assessment.

In the wake of the compound March 2011 nuclear disaster at the Fukushima I nuclear power plant in Japan, international public dialogue has repeatedly turned to questions of the accuracy of current risk assessment processes to assess nuclear risks and the adequacy of existing regulatory risk thresholds to protect us from nuclear harm. We confront these issues with an emphasis on learning from the incident in Japan for future US policy discussions. Without delving into a broader philosophical discussion of the general social acceptance of the risk, the relative adequacy of existing US Nuclear Regulatory Commission (NRC) risk thresholds is assessed in comparison with the risk thresholds of federal agencies not currently under heightened public scrutiny. Existing NRC thresholds are found to be among the most conservative in the comparison, suggesting that the agency's current regulatory framework is consistent with larger societal ideals. In turning to risk assessment methodologies, the disaster in Japan does indicate room for growth. Emerging lessons seem to indicate an opportunity to enhance resilience through systemic levels of risk aggregation. Specifically, we believe bringing systemic reasoning to the risk management process requires a framework that (i) is able to represent risk-based knowledge and information about a panoply of threats; (ii) provides a systemic understanding (and representation) of the natural and built environments of interest and their dependencies; and (iii) allows for the rational and coherent valuation of a range of outcome variables of interest, both tangible and intangible. Rather than revisiting the thresholds themselves, we see the goal of future nuclear risk management in adopting and implementing risk assessment techniques that systemically evaluate large-scale socio-technical systems with a view toward enhancing resilience and minimizing the potential for surprise.