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Lise Laurin

Bio: Lise Laurin is an academic researcher. The author has contributed to research in topics: Impact assessment & Normalization (statistics). The author has an hindex of 9, co-authored 15 publications receiving 504 citations.

Papers
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Journal ArticleDOI
TL;DR: A novel framework for anticipatory LCA is introduced that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies.
Abstract: 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.

99 citations

Journal ArticleDOI
TL;DR: The goal of guiding innovation toward beneficial social and environmental outcomes referred to in the growing literature as responsible research and innovation (RRI) is intuitively worthwhile but lacks practicable tools for implementation One potentially useful tool is Life Cycle Assessment (LCA), which is a comprehensive framework used to evaluate the environmental impacts of products, processes, and technologies.
Abstract: The goal of guiding innovation toward beneficial social and environmental outcomes – referred to in the growing literature as responsible research and innovation (RRI) – is intuitively worthwhile but lacks practicable tools for implementation One potentially useful tool is life-cycle assessment (LCA), which is a comprehensive framework used to evaluate the environmental impacts of products, processes, and technologies However, LCA ineffectively promotes RRI for at least two reasons: (1) Codified approaches to LCA are largely retrospective, relying heavily on data collected from mature industries with existing supply chains and (2) LCA underemphasizes the importance of stakeholder engagement to inform critical modeling decisions which diminishes the social credibility and relevance of results LCA researchers have made piecemeal advances that address these shortcomings, yet there is no consensus regarding how to advance LCA to support RRI of emerging technologies This paper advocates for development of

86 citations

Journal ArticleDOI
TL;DR: In this article, a stochastic multi-attribute analysis for life-cycle impact assessment (SMAA-LCIA) is proposed to evaluate mutual differences and weights stochastically.
Abstract: Comparative life-cycle assessments (LCAs) today lack robust methods of interpretation that help decision makers understand and identify tradeoffs in the selection process. Truncating the analysis at characterization is misleading and existing practices for normalization and weighting may unwittingly oversimplify important aspects of a comparison. This paper introduces a novel approach based on a multi-criteria decision analytic method known as stochastic multi-attribute analysis for life-cycle impact assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces. To contrast different valuation methods, this study performs a comparative LCA of liquid and powder laundry detergents using three approaches to normalization and weighting: (1) characterization with internal normalization and equal weighting, (2) typical valuation consisting of external normalization and weights, and (3) SMAA-LCIA using outranking normalization and stochastic weighting. Characterized results are often represented by LCA software with respect to their relative impacts normalized to 100 %. Typical valuation approaches rely on normalization references, single value weights, and utilizes discrete numbers throughout the calculation process to generate single scores. Alternatively, SMAA-LCIA is capable of exploring high uncertainty in the input parameters, normalizes internally by pair-wise comparisons (outranking) and allows for the stochastic exploration of weights. SMAA-LCIA yields probabilistic, rather than discrete comparisons that reflect uncertainty in the relative performance of alternatives. All methods favored liquid over powder detergent. However, each method results in different conclusions regarding the environmental tradeoffs. Graphical outputs at characterization of comparative assessments portray results in a way that is insensitive to magnitude and thus can be easily misinterpreted. Typical valuation generates results that are oversimplified and unintentionally biased towards a few impact categories due to the use of normalization references. Alternatively, SMAA-LCIA avoids the bias introduced by external normalization references, includes uncertainty in the performance of alternatives and weights, and focuses the analysis on identifying the mutual differences most important to the eventual rank ordering. SMAA-LCIA is particularly appropriate for comparative LCAs because it evaluates mutual differences and weights stochastically. This allows for tradeoff identification and the ability to sample multiple perspectives simultaneously. SMAA-LCIA is a robust tool that can improve understanding of comparative LCA by decision or policy makers.

80 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a roadmap for capacity development in life cycle assessment (LCA), which identifies common needs for development in LCA, which can then be addressed by the broader LCA community.
Abstract: When life cycle assessment (LCA) results do not show a clear and certain environmental preference of one choice over one or several alternatives, current methods are limited in their ability to inform decision-makers. To address this and related cross-cutting issues, a group of LCA practitioners has been working on a roadmap for capacity development in LCA. The roadmap is identifying common needs for development in LCA, which can then be addressed by the broader LCA community. The roadmap document on decision-making support, having undergone a public comment period, outlines the current state as well as needs and milestones to ensure progress continues apace. The roadmap document, available for download, covers five main areas of development: (1) performance measures of confidence, which identify the acceptable uncertainty for study results, while minimizing expenditures; (2) selection of impact categories, an area with multiple existing methods. The roadmap suggests codifying these methods and identifying their suitability to various applications; (3) normalization; while several methods of normalization are in use, the method with the greatest acceptance in the LCA community (i.e., relying on total or per capita regional emissions/extractions) has a number of methodological drawbacks; (4) weighting, which is a form of multi-criteria decision analysis (MCDA). The broader MCDA field can enrich LCA by providing studied methods of assessing trade-offs; and (5) visualization of results. Many other LCA capacity needs would benefit from documentation. These include but are not limited to the following: addressing ill-characterized uncertainty, life cycle inventory data needs, data format needs, and tool capabilities. Other roadmapping groups are forming and are looking for practitioners to support the effort.

42 citations


Cited by
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Nancy Krieger1
TL;DR: This paper argues that the central question becomes: who and what is responsible for population patterns of health, disease, and well-being, as manifested in present, past and changing social inequalities in health?
Abstract: In social epidemiology, to speak of theory is simultaneously to speak of society and biology. It is, I will argue, to speak of embodiment. At issue is how we literally incorporate, biologically, the world around us, a world in which we simultaneously are but one biological species among many—and one whose labour and ideas literally have transformed the face of this earth. To conceptualize and elucidate the myriad social and biological processes resulting in embodiment and its manifestation in populations' epidemiological profiles, we need theory. This is because theory helps us structure our ideas, so as to explain causal connections between specified phenomena within and across specified domains by using interrelated sets of ideas whose plausibility can be tested by human action and thought.1–3 Grappling with notions of causation, in turn, raises not only complex philosophical issues but also, in the case of social epidemiology, issues of accountability and agency: simply invoking abstract notions of ‘society’ and disembodied ‘genes’ will not suffice. Instead, the central question becomes: who and what is responsible for population patterns of health, disease, and well-being, as manifested in present, past and changing social inequalities in health?

1,719 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the border crossing into the subculture of science and discuss the effects of science education on the culture of science in the United States, including the following:
Abstract: (1996). Science Education: Border Crossing into the Subculture of Science. Studies in Science Education: Vol. 27, No. 1, pp. 1-52.

973 citations

Journal ArticleDOI
TL;DR: A review of the published literature in English on the concept of scientific literacy can be found in this paper, where the net is cast wider than just the professional science education com- munity and the diverse works on scientific literacy are brought together in an interpretative synthesis of this literature.
Abstract: In this review of the published literature in English on the concept of scientific literacy, the net is cast wider than just the professional science education com- munity, and the diverse works on scientific literacy are brought together in an interpretative synthesis of this literature. Scientific literacy is first placed in an historical context, and a number of different factors that influence interpretations of this concept are discussed thereafter. These factors include the number of different interest groups that are concerned with scientific literacy, different conceptual definitions of the term, the relative or absolute nature of scientific literacy as a concept, different purposes for advocating scientific lit- eracy, and different ways of measuring it. The overview yields a fuller understanding of the various factors that contribute to the concept of scientific literacy, and makes clear the relationships between these factors. 2000 John Wiley & Sons, Inc. Sci. Ed 84:71- 94, 2000.

909 citations

Book
01 Aug 2003
TL;DR: The prehistory of science and technology studies can be traced back to the Kuhnian Revolution and the early 20th century as discussed by the authors, with a focus on the social construction of scientific and technical realities.
Abstract: Preface vii 1 The Prehistory of Science and Technology Studies 1 2 The Kuhnian Revolution 12 3 Questioning Functionalism in the Sociology of Science 23 4 Stratification and Discrimination 36 5 The Strong Programme and the Sociology of Knowledge 47 6 The Social Construction of Scientific and Technical Realities 57 7 Feminist Epistemologies of Science 72 8 Actor-Network Theory 81 9 Two Questions Concerning Technology 93 10 Studying Laboratories 106 11 Controversies 120 12 Standardization and Objectivity 136 13 Rhetoric and Discourse 148 14 The Unnaturalness of Science and Technology 157 15 The Public Understanding of Science 168 16 Expertise and Public Participation 180 17 Political Economies of Knowledge 189 References 205 Index 236

536 citations