Using LCA to examine greenhouse gas abatement policy |
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Authors: | Email author" target="_blank">Stuart?RossEmail author David?Evans Michael?Webber |
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Institution: | (1) School of Anthropology, Geography and Environmental Studies (SAGES), University of Melbourne, 3010 Parkville, Victoria, Australia;(2) Faculty of Architecture, Building and Planning, University of Melbourne, 3010 Parkville, Victoria, Australia |
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Abstract: | The site-generic approach currently adopted by the Life Cycle Assessment (LCA) methodology introduces uncertainties into the
impact assessment phase of an LCA study. These uncertainties are greatest for localised and short-lived problems but are less
significant for long lasting, cumulative environmental effects. Indeed, the reliability of LCA results is high for problems
that manifest at a global scale. Nevertheless, even though these results are considered accurate, it is still often unclear
as to their relevance in terms of policy development and decision-making. Therefore, this paper demonstrates how LCA can be
used to determine the efficacy of policies aimed at reducing a product system’s contribution to global environmental problems.
We accomplish this aim by presenting a case study that evaluates the greenhouse gas contributions of each stage in the life
cycle of containerboard packaging and the potential impact on emissions of various policy options available to decision makers.
Our analysis showed that in general the most useful strategy was to recycle the used packaging. However, our analysis also
indicated that when measures are taken to eliminate sources of methane emissions and encourage the use of plantation timber
then recycling is no longer beneficial from a greenhouse perspective. This is because the process energy required in the form
of gas and electricity is substantially greater for containerboard manufactured from recycled material than it is for virgin
fibre. |
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Keywords: | Containerboard greenhouse gas abatement policy ISO 14040 life cycle assessment packaging pulp and paper uncertainty |
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