Search

Abstract: Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle‐based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.

Complex networked systems ranging from ecosystems and the climate to economic, social, and infrastructure systems can exhibit a tipping point (a "point of no return") at which a total collapse of the system occurs. To understand the dynamical mechanism of a tipping point and to predict its occurrence as a system parameter varies are of uttermost importance, tasks that are hindered by the often extremely high dimensionality of the underlying system. Using complex mutualistic networks in ecology as a prototype class of systems, we carry out a dimension reduction process to arrive at an effective 2D system with the two dynamical variables corresponding to the average pollinator and plant abundances. We show, using 59 empirical mutualistic networks extracted from real data, that our 2D model can accurately predict the occurrence of a tipping point, even in the presence of stochastic disturbances. We also find that, because of the lack of sufficient randomness in the structure of the real networks, weighted averaging is necessary in the dimension reduction process. Our reduced model can serve as a paradigm for understanding and predicting the tipping point dynamics in real world mutualistic networks for safeguarding pollinators, and the general principle can be extended to a broad range of disciplines to address the issues of resilience and sustainability.

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis.We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts.

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis.We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts.

To be truly innovative, digital pedagogy has to do a better job of giving students the very thing that makes brick-and-mortar schooling so special: It must foster immersive learning communities that connect students to both their instructors and each other. Fortunately, there are ways that online education can do just that, as the authors have learned while team-teaching an ethics course that blends traditional classroom activities with an unusual online component. This is the second year they will teach "Sustainability Ethics" at their respective colleges, Arizona State University and the Rochester Institute of Technology. In the course, students play interactive games that the authors developed to explore theoretic problems relating to important issues in sustainability. While the students participate in the usual learning activities like reading, discussion, and writing assignments, they experience ethical issues personally through the games, in which they have an opportunity to advance their own grades at the expense of classmates' grades. To complicate matters, each game randomly positions students at different levels of privilege, so it is more difficult for some students to earn grade points than others. Finally, the authors link their two classes (using EthicsCore, an information-technology platform supported by the National Science Foundation) so that decisions made by one class affect grades earned by the other, 2,300 miles away. Students deliberate across universities exclusively online, in discussion rooms and chat windows. The authors' experience has several implications for online education generally, and for ethics education in particular. A common complaint in online education is that students study in isolation from one another. However, when they are joined online in collaborative and deliberative tasks, a learning community can form that transcends geographical and temporal distances. That is what happened with their students. Both student groups were more engaged in the ethical issues they confronted online than they would have been using more conventional approaches. While the two groups never met in person, they felt bound to one another in ways they might not have otherwise. In the end, peace prevailed, and the Arizona State students sent photos and gifts to the Rochester group.

Infrastructure is essential to provision of public health, safety, and well-being. Yet, even critical infrastructure systems cannot be designed, constructed, and operated to be robust to the myriad of surprising hazards they are likely to be subject to. As such, there has been increasing emphasis in Federal policy on enhancing infrastructure resilience. Nonetheless, existing research on infrastructure systems often overlooks the role of individual decision-making and team dynamics under the conditions of high ambiguity and uncertainty typically associated with surprise. Although evidence suggests that human factors correlating with resilience and adaptive capacity emerge in later stages of psychological development, there is an acute need for new knowledge about the human capacity to comprehend increasing levels of complexity in the context of rapidly evolving technological, ecological, and social stress conditions. Sometimes, it is this developmental capacity for meaning-making that is the difference between adaptive and maladaptive response. Thus, without a better understanding of the human capacity to develop and assign meaning to complex systems, unquestioned misconceptions about the human role may prevail. In this work, we examine the dynamic relationships between human and technological systems from a developmental perspective. We argue that knowledge of resilient human development can improve system resilience by aligning roles and responsibilities with the developmental capacities of individuals and groups responsible for the design, operation, and management of critical infrastructures. Taking a holistic approach that draws on both psychology and resilience engineering literature facilitates construction of an integrated model that lends itself to empirical verification of future research. [ABSTRACT FROM AUTHOR]