Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour- and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models. The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification" - IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions. The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment, greatly expediting workflows and making these computational benefits accessible to all users. Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties.

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Greenhouse gas emissions from beef production are a significant part of Australia's total contribution to climate change. For the first time an environmental life cycle assessment (LCA) hybridizing detailed on-site process modeling and input-output analysis is used to describe Australian red meat production. In this paper we report the carbon footprint and total energy consumption of three supply chains in three different regions in Australia over two years. The greenhouse gas (GHG) emissions and energy use data are compared to those from international studies on red meat production, and the Australian results are either average or below average. The increasing proportion of lot-fed beef in Australia is favorable, since this production system generates lower total GHG emissions than grass-fed production; the additional effort in producing and transporting feeds is effectively offset by the increased efficiency of meat production in feedlots. In addition to these two common LCA indicators, in this paper we also quantify solid waste generation and a soil erosion indicator on a common basis.

To fill a gap in the information available to nonmetropolitan policy makers, eight scenarios combining processing technologies and end-uses for biosolids products associated with a 40 000 equivalent-person town were modeled using environmental life cycle assessment (LCA). An uncertainty analysis examined several key assumptions. The results showed that the reuse of biosolids products can be environmentally beneficial but transportation distances can change the preferences between technologies, and drying biosolids using petrochemical methane rather than biogas (produced endogenously in the wastewater facility) significantly worsens environmental performance. System scale can also invert option preferences. This work demonstrates an application of LCA to a strategic engineering question. We also examine the methodological feasibility of considering carbon sequestration and water offsets beyond those typical of previous studies. As the development of scientific data regarding the benefits of biosolids recycling develops, there may be potential to reward agricultural businesses that choose to reduce their environmental burdens using biosolids. A life cycle management approach to this will be necessary.

Background, aim, and scope One barrier to the further implementation of LCA as a quantitative decision-support tool is the uncertainty created by the diversity of available analytical approaches. This paper compares conventional ('process analysis') and alternative ('input-output analysis') approaches to LCA, and presents a hybrid LCA model for Australia that overcomes the methodological limitations of process and input-output analysis and enables a comparison between the results achieved using each method. A case study from the water industry illustrates this comparison. Materials and methods We have developed a tiered hybrid model for calculating the life cycle impacts of a system. In so doing, we have developed a novel way of overcoming a key methodological issue associated with this method: avoiding double counting. We calculate 'system incompleteness factors' and use these to delete the lower-order burdens in the input-output inventory according to the depth of production taken into account in the process inventory. We apply this method to a case study of Sydney Water Corporation. The functional unit is the provision of water and sewerage services to residential, industrial, and commercial customers in the city of Sydney in the year 2002/03. Results and discussionWe analysed the case study using three methods: process analysis, input-output analysis, and hybrid analysis. In each case, we obtained results for eight impact categories: water use; primary energy use; global warming potential; carcinogenic and non-carcinogenic human toxicity potentials; and terrestrial, marine and freshwater ecotoxicity potentials. Although the process analysis has a relatively shallow investigative depth, it shows good system coverage (i.e. a small truncation error) for most indicators. The truncation errors for all of the indicators except marine aquatic ecotoxicity potential compare favourably with predicted truncation errors for the relevant industry sector. This suggests that the truncation error of a particular process analysis cannot be accurately predicted using generic system completeness curves, and implies that the truncation error of a typical process analysis may be less severe than is commonly generalised by the proponents of input-output analysis. Conclusions The case study supports the largely theoretical claims in the literature about the relative merits and drawbacks of process and input-output analysis. Each method has the potential to highlight different aspects of the system. By estimating the truncation error of the process analysis independently of the relationship between the results obtained using the other methods, our hybrid model enhances the ability to investigate the differences between results and thus adds considerable value to such a study. Recommendations and perspectives Input-output LCA has become more popular as computational tools have become more accessible. We directly compare input-output, process and hybrid LCA and recommend that, from an environmental analysis perspective, it would be be...