397 research outputs found

    Functional, symbolic and societal frames for automobility: implications for sustainability transitions

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    Automobility refers to the continued, self-perpetuating dominance of privately-owned, gasoline-powered vehicles used primarily by single occupants—a system which clearly has broad environmental and societal impacts. Despite increasing societal interest in transitions to more sustainable transportation technologies, there has been little consideration of how such innovations might challenge, maintain or support different aspects of automobility, and what that means for technology deployment, transport policy, and user practices. To bring attention to the complexity and apparent durability of the automobility system, in this paper we develop a conceptual framework that explores automobility through a categorization of frames, or shared cultural meanings. This framework moves beyond the typical focus on private, functional considerations of user choice, financial costs and time use to also consider symbolic and societal frames of automobility that exist among users, non-users, industry, policymakers and other relevant social groups. We illustrate this framework with eight particular frames of automobility that fall into four broad categories: private-functional frames such as (1) cocooning and fortressing and (2) mobile digital offices; private-symbolic frames such as (3) gender identity and (4) social status; societal-functional frames such as (5) environmental stewardship and (6) suburbanization; and societal-symbolic frames such as (7) self-sufficiency and (8) innovative adopters. Finally, we start the process of discussing several transportation innovations in light of these automobility frames, namely electrified, autonomous and shared mobility—examining early evidence for which frames would be challenged or supported by such transitions. We believe that appreciation of the complex and varied frames of automobility can help to enrichen discussion of transitions and policy relating to sustainable transportation

    The roles of users in electric, shared and automated mobility transitions

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    This paper synthesizes insights from 19 peer-reviewed articles published in this Special Issue on the roles of users in shared, electric and automated mobility. While many researchers and stakeholders remain inspired by the potential low costs and societal benefits of these innovations, less is known about the real-world potential for uptake and usage. To better understand the likelihood and impacts of widespread uptake, we explore the perceptions of actual and potential users, including drivers, passengers, owners, and members, as well as other stakeholders such as pedestrians, planners, and policymakers. The Special Issue examines a range of cases, including plug-in electric vehicles, car-share and bike-share programs, ride-hailing and automated vehicles. For each innovation, we organize insights on user perceptions of benefits and drawbacks into four categories. Much of the research to date focuses on the first category, private-functional perceptions, mainly total cost of ownership (e.g., $/km), time use and comfort. Our synthesis however spans the other three categories for each innovation: private-symbolic perceptions include the potential for social signaling and communicating identity; societal-functional perceptions include GHG emissions, public safety and noise; and societal-symbolic perceptions include inspiring pro-societal behavior in others, and the potential to combat or reinforce the status quo system of “automobility”. Further, our synthesis demonstrates how different theories and methods can be more or less equipped to “see” different perception categories. We also summarize findings regarding the characteristics of early users, as well as practical insights for strategies and policies seeking societally-beneficial outcomes from mass deployment of these innovations

    An interdisciplinary assessment of climate engineering strategies

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    Author Posting. © Ecological Society of America, 2014. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Frontiers in Ecology and the Environment 12 (2014): 280–287, doi:10.1890/130030.Mitigating further anthropogenic changes to the global climate will require reducing greenhouse-gas emissions (“abatement”), or else removing carbon dioxide from the atmosphere and/or diminishing solar input (“climate engineering”). Here, we develop and apply criteria to measure technical, economic, ecological, institutional, and ethical dimensions of, and public acceptance for, climate engineering strategies; provide a relative rating for each dimension; and offer a new interdisciplinary framework for comparing abatement and climate engineering options. While abatement remains the most desirable policy, certain climate engineering strategies, including forest and soil management for carbon sequestration, merit broad-scale application. Other proposed strategies, such as biochar production and geological carbon capture and storage, are rated somewhat lower, but deserve further research and development. Iron fertilization of the oceans and solar radiation management, although cost-effective, received the lowest ratings on most criteria. We conclude that although abatement should remain the central climate-change response, some low-risk, cost-effective climate engineering approaches should be applied as complements. The framework presented here aims to guide and prioritize further research and analysis, leading to improvements in climate engineering strategies.NSF grant #1103575 supported KRMM

    Smart homes and their users:a systematic analysis and key challenges

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    Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home-functional, instrumental, socio-technical; (2) users and the use of the smart home-prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home-hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns-privacy and control-that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified

    Parameter estimation of an electrochemistry-based lithium-ion battery model

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    The final publication is available at Elsevier via http://doi.org/10.1016/j.jpowsour.2015.04.154" © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Parameters for an electrochemistry-based Lithium-ion battery model are estimated using the homotopy optimization approach. A high-fidelity model of the battery is presented based on chemical and electrical phenomena. Equations expressing the conservation of species and charge for the solid and electrolyte phases are combined with the kinetics of the electrodes to obtain a system of differential-algebraic equations (DAEs) governing the dynamic behavior of the battery. The presence of algebraic constraints in the governing dynamic equations makes the optimization problem challenging: a simulation is performed in each iteration of the optimization procedure to evaluate the objective function, and the initial conditions must be updated to satisfy the constraints as the parameter values change. The ε-embedding method is employed to convert the original DAEs into a singularly perturbed system of ordinary differential equations, which are then used to simulate the system efficiently. The proposed numerical procedure demonstrates excellent performance in the estimation of parameters for the Lithium-ion battery model, compared to direct methods that are either unstable or incapable of converging. The obtained results and estimated parameters demonstrate the efficacy of the proposed simulation approach and homotopy optimization procedure.The financial support of the NSERC/Toyota/Maplesoft Industrial Re-search Chair program is gratefully acknowledged

    Improving the behavioral realism of global integrated assessment models:An application to consumers’ vehicle choices

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    A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies
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