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Wind Power as a Case Study

SummaryMeta‐analyses of life cycle assessments (LCAs) have become increasingly important in the context of renewable energy technologies and the decisions and policies that influence their adoption. However, a lack of transparency in reporting modeling assumptions, data, and results precludes normalizing across incommensurate system boundaries or key assumptions. This normalization step is critical for conducting valid meta‐analyses.Thus it is necessary to establish clear methods for assessing transparency and to develop conventions for LCA reporting that promote future comparisons. While concerns over transparency in LCA have long been discussed in the literature, the methods proposed to address these concerns have not focused on the transparency and reporting characteristics required for performing meta‐analyses. In this study we identify guidelines for assessing reporting transparency that anticipate the needs of meta‐analyses of LCA applied to renewable energy technologies.These guidelines were developed after an attempt to perform a meta‐analysis on wind turbine LCAs of 1 megawatt and larger, with the goal of determining how life cycle performance, as measured by global warming intensity, might trend with turbine size. The objective was to normalize system boundaries and environmental conditions, and reinterpret global warming potential with new impact assessment methods. Previous wind LCAs were reviewed and assessed for reporting transparency. Only a small subset of studies proved to be sufficiently transparent for the normalization of system boundaries and modeling assumptions required for meta‐analyses.
- University of California, Davis United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).26 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
