Page 46 - Materials Chemistry, Second Edition
P. 46

Chapter 4


                 Life cycle assessment as decision support: a
                 systemic critique


                 Tim Grant and Fran Macdonald





                 It is often stated that LCA is a ‘decision-support tool’. Certainly it can be a powerful and sys-
                 tematic tool that provides useful data to facilitate decisions. But what is it about LCA that
                 contributes to decision-making, and can it do more than support the evaluation of a previ-
                 ously formed proposition, as the term ‘decision-support tool’ would suggest?


                 4.1  Introduction: the role of LCA in decision support
                 LCA and indeed all decision-support tools play a much deeper role in framing the questions
                 asked in order to make decisions and therefore in delimiting solutions. Fundamentally, this is
                 due to the reflexive nature of methods of analysis on the things they analyse. The result of any
                 analysis depends on the tool used. For example, an analysis that takes into account only quan-
                 tifiable data will produce quantifiable results; and an analysis that does not consider uncer-
                 tainty will not identify uncertainty in the results.
                    Tools that do not take into account their own reflexive nature (i.e. that they have a role in
                 shaping the results rather than just identifying them) can be referred to as ‘dualistic’ – exhibit-
                 ing ‘the capacity to see ourselves as actors in/on the environment’ and essentially separate
                 from it (Fisher 2006, p. 4). Dualistic approaches consider how to ‘fix’ or cure an already defined
                 and isolated problem. Fisher says:
                      These involve isolating some ‘causative’ agent in the phenomenon of concern and
                      ‘fixing’ it by altering the agent so that its outcome is not what concerned us, or by
                      breaking its chain of causation so that it immobilises in the sense we understood it
                      to be mobile’ (Fisher 2006, p. 6).
                    The fix or cure is limited by the initial definition of the problem or cause. The fix may also
                 have unintended and even undesirable consequences that are not taken into account because
                 the initial problem has been isolated from surrounding data. Consider the infamous example
                 of cane toads, deliberately introduced into Australia in 1935 to control infestations of beetles
                 that were destroying sugar cane crops. The problem, defined as ‘how to kill cane beetles’,
                 seemed to be readily answered by cane toads, which were native to Central and South America
                 where their habitat was reasonably confined. However, the introduced toads had no effect on
                 cane beetles in Australia, which persist as a problem for the sugar cane industry despite the
                 subsequent development of pesticides. Cane toads also quickly became a pest animal, breeding
                 unseasonably and spreading throughout the habitats of northern Australia, where they threaten
                 wildlife that has not evolved to resist them.

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