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Life cycle assessment and agriculture: challenges and prospects

                   volatilisation. Trash blanketing (as practiced in the Wet Tropics and state-average scenarios)   111
                 also increases nitrogen losses, by providing additional nitrogen and a carbon source, both of
                 which promote microbial and metabolic processes in the soil. The Burdekin region has the
                 lowest result since it is a drier environment and cane is grown without a trash blanket. Emis-
                 sions from sugar cane fields (ammonia and nitrogen oxides) generally make the most impor-
                 tant contribution to acidification potential with environmental conditions again providing an
                 important influence on the variation observed between different regions. Regarding water
                 impacts, sugar cane responds particularly well to high water availability and some 60% of the
                 Queensland crop is irrigated. This is an important environmental consideration in countries
                 with low rainfall and poor supplies of irrigation water.
                    Importantly, the sugar cane study highlights areas where data improvements can be made,
                 and notes three main factors found to influence variability in sugar cane environmental
                 performance:
                 1.  environmental conditions – climate, soil type, and topography
                 2. agronomic practices
                 3.  geographic location relative to supporting infrastructure.

                    Although greenhouse gas emissions are influenced by both the intensity of resource inputs
                 and environmental factors, there is considerable uncertainty around actual N O emissions
                                                                                  2
                 between scenarios, and that actual variability may be greater than that reported by the limited
                 data set used. Indeed, the results show the importance of field emissions in sugar cane produc-
                                                                              –
                 tion, particularly emissions of all nitrogen species (N O, NO , NH , NO ). Eutrophication
                                                             2      x   3    3
                 and acidification potentials appear to be influenced by environmental factors, but the reten-
                 tion of crop residues after harvest (trash) is also important. Regarding water impacts, not sur-
                 prisingly, the key factor is irrigation.
                    The essential conclusion of the work by Renouf (2006) is that variability should be consid-
                 ered carefully in LCAs of agricultural crop production, particularly in relation to environmen-
                 tal conditions, but also agronomic practices. An agricultural practice ‘mean’ average
                 performance assessment may therefore be less meaningful than an equivalent measure for a
                 product manufacturing plant-based system where the variables are fewer and the controls over
                 the system greater. This is a major challenge for ‘traditional’ LCA, which typically seeks to
                 identify and model some form of ‘standard’ performance.
                    Two reflections on Renouf’s sugar cane studies reveal further implications for LCA practice
                 and potential. First, where there is variability across the system, as in sugar cane growing in
                 Queensland, a series of LCA studies may be used to identify empirically a set of key variables
                 that exist in practice and have the potential to significantly alter results. Examples may be soil
                 moisture content, particular field practices and irrigation rates. From this, a tool may be envis-
                 aged where the implications of varying these factors can be quickly and with sufficient accuracy
                 modelled by a non-LCA specialist. This provides the potential to capture local variations in
                 practice and conditions in the modelling of performance, and where it is possible to vary
                 inputs, practice may be altered according to desired performance outcomes. This approach
                 holds out the possibility of bringing LCA forward temporally to become a field-scale tool that
                 can alter design and practice of activities in real time (for further discussion on ‘quick’ LCA
                 tools, see Chapter 11).
                    Second, as the essential issue is optimisation of the sugar cane industry, it is still open as to
                 whether the resources involved – land, water, labour and various inputs – are optimised in
                 sugar cane growing, or whether alternative practices are preferable. Often, LCA is conducted
                 in a propositional or planning setting, whereas here there is a sugar cane production industry
                 that has been well-established for over 100 years. Any change in sugar cane agricultural practice








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