WHAT CAN META-ANALYSES TELL US ABOUT THE RELIABILITY OF LIFE CYCLE ASSESSMENT FOR DECISION SUPPORT?
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WHAT CAN META-ANALYSES TELL US ABOUT THE RELIABILITY OF LIFE CYCLE ASSESSMENT FOR DECISION SUPPORT?
WHAT CAN META-ANALYSES TELL US ABOUT THE RELIABILITY OF LIFE CYCLE ASSESSMENT FOR DECISION SUPPORT?
The body of life
cycle assessment (LCA) literature is vast and has grown over the last decade at
a dauntingly rapid rate. Many LCAs have been published on the same or very
similar technologies or products, in some cases leading to hundreds of
publications. One result is the impression among decision makers that LCAs are
inconclusive, owing to perceived and real variability in published estimates of
life cycle impacts. Despite the extensive available literature and policy need
formore conclusive assessments, only modest attempts have been made to
synthesize previous research. A significant challenge to doing so are
differences in characteristics of the considered technologies and inconsistencies
in methodological choices (e.g., system boundaries, coproduct allocation, and
impact assessment methods) among the studies that hamper easy comparisons and
related decision support. An emerging trend is meta-analysis of a set of
results from LCAs, which has the potential to clarify the impacts of a
particular technology, process, product, or material and produce more robust
and policy-relevant results. Meta-analysis in this context is defined here as
an analysis of a set of published LCA results to estimate a single or multiple
impacts for a single technology or a technology category, either in a
statisticalmore » sense (e.g., following the practice in the biomedical
sciences) or by quantitative adjustment of the underlying studies to make them
more methodologically consistent. One example of the latter approach was
published in Science by Farrell and colleagues (2006) clarifying the net energy
and greenhouse gas (GHG) emissions of ethanol, in which adjustments included
the addition of coproduct credit, the addition and subtraction of processes
within the system boundary, and a reconciliation of differences in the
definition of net energy metrics. Such adjustments therefore provide an even
playing field on which all studies can be considered and at the same time
specify the conditions of the playing field itself. Understanding the
conditions under which a meta-analysis was conducted is important for proper
interpretation of both the magnitude and variability in results. This special
supplemental issue of the Journal of Industrial Ecology includes 12
high-quality metaanalyses and critical reviews of LCAs that advance
understanding of the life cycle environmental impacts of different
technologies, processes, products, and materials. Also published are three contributions
on methodology and related discussions of the role of meta-analysis in LCA. The
goal of this special supplemental issue is to contribute to the state of the
science in LCA beyond the core practice of producing independent studies on
specific products or technologies by highlighting the ability of meta-analysis
of LCAs to advance understanding in areas of extensive existing literature. The
inspiration for the issue came from a series of meta-analyses of life cycle GHG
emissions from electricity generation technologies based on research from the
LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a
laboratory of the U.S. Department of Energy, which also provided financial
support for this special supplemental issue. (See the editorial from this
special supplemental issue [Lifset 2012], which introduces this supplemental
issue and discusses the origins, funding, peer review, and other aspects.) The
first article on reporting considerations for meta-analyses/critical reviews
for LCA is from Heath and Mann (2012), who describe the methods used and
experience gained in NREL’s LCA Harmonization Project, which produced six of
the studies in this special supplemental issue. Their harmonization approach
adapts key features of systematic review to identify and screen published LCAs
followed by a meta-analytical procedure to adjust published estimates to ones
based on a consistent set of methods and assumptions to allow interstudy
comparisons and conclusions to be made. In a second study on methods, Zumsteg
and colleagues (2012) propose a checklist for a standardized technique to
assist in conducting and reporting systematic reviews of LCAs, including
meta-analysis, that is based on a framework used in evidence-based medicine.
Widespread use of such a checklist would facilitate planning successful
reviews, improve the ability to identify systematic reviews in literature
searches, ease the ability to update content in future reviews, and allow more
transparency of methods to ease peer review and more appropriately generalize
findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired
by a meta-analysis, for categorizing main methodological topics, reconciling
diverging methodological developments, and identifying future research
directions in LCA.
WHAT CAN META-ANALYSES TELL US ABOUT THE RELIABILITY OF LIFE CYCLE ASSESSMENT FOR DECISION SUPPORT?
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The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One exa.. animal science project topics
WHAT CAN META-ANALYSES TELL US ABOUT THE RELIABILITY OF LIFE CYCLE ASSESSMENT FOR DECISION SUPPORT?