Compiling and using input-output frameworks through collaborative virtual laboratories.

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.

Aggregating sustainability indicators: beyond the weighted sum.

Sustainability analysts and environmental decision makers often overcome the difficulty of interpreting comprehensive environmental profiles by aggregating the results using multi-criteria decision analysis (MCDA) methods. However, the wide variety of methodological approaches to weighting and aggregation introduces subjectivity and often uncertainty. It is important to select an approach that is consistent with the decision maker's information needs, but scant practical guidance is available to environmental managers on how to do this. In this paper, we aim to clarify the theoretical implications of an analyst's choice of MCDA method. By systematically examining the methodological decisions that must be made by the analyst at each stage of the assessment process, we aim to improve analysts' understanding of the relationship between MCDA theory and practice, and enable them to apply methods that are consistent with a decision maker's needs in any given problem context.

Red meat production in australia: life cycle assessment and comparison with overseas studies.

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.

Environmental comparison of biosolids management systems using life cycle assessment.

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 potentialto reward agricultural businesses that choose to reduce their environmental burdens using biosolids. A life cycle management approach to this will be necessary.