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Randolph E. Kirchain and Joel P. Clark. Rampuria, Abhishek Massachusetts Institute of Technology. Dept. of Materials Science and Engineering. Massachusetts Institute of Technology. Department of Materials Science and Engineering 2013-01-07T19:06:29Z 2013-01-07T19:06:29Z 2012 2012 http://hdl.handle.net/1721.1/75852 821214138 Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2012. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student submitted PDF version of thesis. Includes bibliographical references (p. 49-50). As environmental footprint considerations for companies gain greater importance, the need for quantitative impact assessment tools such as life cycle assessment (LCA) has become a higher priority. Currently, the cost and time burden associated with LCA has prevented it from becoming more prevalent. While several streamlining approaches have been suggested, questions regarding the effectiveness and efficiency of the streamlined results are still of concern. The streamlining method of probabilistic underspecification has shown initial success in its ability to reduce LCA efforts while simultaneously increasing certainty in the final impact assessment. Probabilistic underspecification streamlines LCA by prioritizing targets of more refined data collection and by implementing the use of underspecified surrogate data within LCI analysis. This thesis concentrates on further developing and improving the streamlining methodology of probabilistic underspecification through refinement of the materials classification systems for polymers and minerals and through additional case study analysis. The classification system allows for a better understanding of the relationship between the degree of materials specificity and the uncertainty in the resulting impact values. Additionally, the resulting polymer and mineral classifications were combined with existing materials classifications to conduct an alkaline battery case study in order to test the effectiveness of the streamlining method. The material classifications created through this research provide a logical and practical approach to underspecification while maintaining consistent and reasonable levels of uncertainty. Furthermore, the case study analysis showed that the streamlining methodology significantly lowered LCA burden by systematically reducing the number of product components requiring full specification. This research provides further evidence that probabilistic underspecification may provide a promising LCA streamlining method among a set of such strategies that can significantly reduce LCA efforts while maintaining the accuracy of the overall impact assessment. by Abhishek Rampuria. S.B. 58 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Materials Science and Engineering. Enabling streamlined life cycle assessment : materials-classification derived structured underspecification Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="9eed80ca-b5c0-4ef0-87bb-d0e5fb87cce9"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Enabling streamlined life cycle assessment : materials-classification derived structured underspecification</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Rampuria, Abhishek</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Materials Science and Engineering.</Keyword> <Abstract>As environmental footprint considerations for companies gain greater importance, the need for quantitative impact assessment tools such as life cycle assessment (LCA) has become a higher priority. Currently, the cost and time burden associated with LCA has prevented it from becoming more prevalent. While several streamlining approaches have been suggested, questions regarding the effectiveness and efficiency of the streamlined results are still of concern. The streamlining method of probabilistic underspecification has shown initial success in its ability to reduce LCA efforts while simultaneously increasing certainty in the final impact assessment. Probabilistic underspecification streamlines LCA by prioritizing targets of more refined data collection and by implementing the use of underspecified surrogate data within LCI analysis. This thesis concentrates on further developing and improving the streamlining methodology of probabilistic underspecification through refinement of the materials classification systems for polymers and minerals and through additional case study analysis. The classification system allows for a better understanding of the relationship between the degree of materials specificity and the uncertainty in the resulting impact values. Additionally, the resulting polymer and mineral classifications were combined with existing materials classifications to conduct an alkaline battery case study in order to test the effectiveness of the streamlining method. The material classifications created through this research provide a logical and practical approach to underspecification while maintaining consistent and reasonable levels of uncertainty. Furthermore, the case study analysis showed that the streamlining methodology significantly lowered LCA burden by systematically reducing the number of product components requiring full specification. This research provides further evidence that probabilistic underspecification may provide a promising LCA streamlining method among a set of such strategies that can significantly reduce LCA efforts while maintaining the accuracy of the overall impact assessment.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>