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Purpose Past life cycle assessments (LCA) of sugarcane (Saccharum officinarum) production have commonly been based on limited datasets, and variability has not been well described. In this work, Australian sugarcane production was assessed more comprehensively in order to generate a robust set of LCA results for use in subsequent assessments of sugarcane products and also to investigate: (1) variability due to regional differences, (2) factors influencing variability, and (3) significance of the impacts. Methods An average scenario for Australian sugarcane production was modeled based on data for the state of Queensland (98% of Australian production). Life cycle impact assessment (LCIA) results were generated using Impact 2002+, modified to be more representative of Australian conditions, and with the inclusion of water use and land use indicators. A Monte Carlo uncertainty analysis, using minimum and maximum values for production data, was undertaken to evaluate variability. Different regional production practices were also modeled to identify factors that influence variability. Normalization aimed to show the significance of total Australian sugarcane production relative to total Australian impacts. Results and discussion Considerable variability was found in the LCIA results, with the key variables being yield, N use efficiency, the susceptibility of soils to N leakage, irrigation (water and energy intensity), and pre-harvest burning. N leakage was found to be an important issue that influences a range of impact categories. When normalized against total national impacts, water use and land use appear to be the most significant impacts (based on simple indicators of consumption), followed by eutrophication potential, acidification potential, and respiratory impacts, whereas non-renewable energy input and global warming are less significant. The results suggest that toxicity impacts are insignificant; however, this may not be supported by other observations that link pesticide loss from sugarcane to toxicity concerns in receiving waters and is a subject for further research. Conclusions and recommendationsThe potential for significant variability in the impacts from sugarcane growing suggests a need for LCAs of sugarcane systems to consider ranges for key variables. The key variables and significant impacts identified in this work can guide data collection priorities for future assessment of sugarcane and possibly other Australian cropping systems. To further develop LCA as a useful predictive tool for Australian agricultural systems, further development and testing of impact assessment models for eutrophication, toxicity, and land and water resource depletion appropriate for Australia and its subregions will be required.Sugarcane is grown over large areas in tropical regions of many countries around the world, mainly for sugar

The environmental benefi ts and trade-offs of automotive biofuels are well known, but less is known about aviation biofuels. We modeled the environmental impacts of three pathways for aviation biofuel in Australia (from microalgae, pongamia, and sugarcane molasses) using attributional life cycle assessments (LCAs), applying both economic allocation and system expansion. Based on economic allocation, sugarcane molasses has the better fossil energy ratio FER (1.7 MJ out/MJ in) and GHG abatement (73% less than aviation kerosene) of the three, but with trade-offs of higher water use and eutrophication potential. Microalgae and pongamia have lower FER and GHG abatement (1.0 and 1.1; 53% and 43%), but mostly avoid eutrophication and reduce water use trade-offs. All have similar and relatively low land use intensities. If produced on land where existing carbon stocks are not compromised, the sugarcane and microalgae pathways would currently meet a 50% GHG abatement requirement. Based on system expansion, microalgae and pongamia had lower impacts than sugarcane for all categories except energy input, highlighting the positive aspects of these next-generation feedstocks. The low fossil energy conservation potential of these pathways was found to be a drawback, and significant energy effi ciencies will be needed before they can affect fossil energy conservation. Energy recovery from processing residues (base case) was preferable over use as animal feed (variant case), and crucial for favorable energy and GHG conservation. However this fi nding is at odds with the economic 580

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Purpose This work generates attributional life cycle assessment (LCA) results for products produced from Australian sugarcane-raw sugar, molasses, electricity (from bagasse combustion), and ethanol (from molasses). It focuses on cane processing in sugar mills and is a companion to the work presented in (Renouf et al. 2010), where the focus is on cane growing. This work also examines the preferred approach for assigning impacts to the multiple products from cane processing, and the influence that variability in cane growing has on the results. Method Initially, global warming potentials were generated for a range of cane processing models, using economic allocation (EA), mass allocation (MA), and system expansion (SE). A preferred approach was identified and applied to generate results for a wider set of impact categories based on the Impact 2002+ method. Uncertainty in the results due to cane-growing variability was assessed using Monte Carlo analysis and compared with the results for substitute products to determine the significance of the variability. Results While the generation of results using SE was appealing for assessing the determining product (raw sugar), it was found to be less valid for the co-products (molasses, electricity, and ethanol). Results could be generated more consistently across all products using allocation. MA was found to be best suited to sugarcane products, whereas EA posed some problems. The uncertainty due to variability in sugarcane growing was found to be significantly higher than that of substitute products. Conclusions and recommendations LCA results for sugarcane products are influenced by (1) the nature of cane processing system, (2) variability in sugarcane growing, and (3) the approach taken for assigning impacts to the multiple products from sugarcane processing. The first two factors imply that results should be specific to the cane-growing region and the cane processing used to produce them. In relation to the latter issue, for generating attributional LCA results that are consistent across all sugarcane products, the recommended approach is to use mass allocation (with energy allocation for bagasse combustion and cogeneration).