A variety of methods can be used to compile a life cycle inventory (LCI) as part of a life cycle assessment (LCA) study. Hybrid LCI methods attempt to address the limitations inherent in more traditional process and input-output (IO) LCI methods. This paper provides an overview of the different hybrid LCI methods currently in use in an attempt to provide greater clarity around how each method is applied and their specific strengths and weaknesses. A search of publications quoting the use of hybrid LCI was undertaken for the period from 2010 to 2015, identifying 97 peer-reviewed publications referencing the use of a hybrid LCI. In over one third of the literature analysed, authors only refer to their analysis as a hybrid LCI, without naming the actual method used, making it difficult to fully understand the method used and any potential limitations. Based on the way in which the various hybrid methods are applied and their existing use, the authors propose a set of clear definitions for existing hybrid LCI methods. This assists in creating a better understanding of, 2 and confidence in applying hybrid LCI methods amongst LCA practitioners, potentially leading to a greater uptake of hybrid LCI. KeywordsLife cycle assessment; life cycle inventory analysis; input-output analysis; process analysis; hybrid analysis.

Purpose Life cycle Assessment (LCA) is inherently complex and time consuming. The compilation of life cycle inventories (LCI) using a traditional process analysis typically involves the collection of data for dozens to hundreds of individual processes. More comprehensive LCI methods, such as input-output analysis and hybrid analysis can include data for billions of individual transactions, or transactions/processes, respectively. While these two methods are known to provide a much more comprehensive overview of a product's supply chain and related environmental flows, they further compound the complex and timeconsuming nature of an LCA. This has limited the uptake of more comprehensive LCI methods, potentially leading to ill-informed environmental decision-making. A more accessible approach for compiling a hybrid LCI is needed to facilitate its wider use. Methods This study develops a model for streamlining a hybrid LCI by automating various components of the approach. The model is based on the Path Exchange hybrid analysis method and includes a series of interrelated modules developed using object-oriented programming in Python. Individual modules have been developed for each task involved in compiling a hybrid LCI, including data processing, Structural Path Analysis, and path exchange or hybridisation. Results and discussion 2/35 The production of plasterboard is used as a case study to demonstrate the application of the automated hybrid model. Australian process and input-output data are used to determine a hybrid embodied greenhouse gas emissions value. Full automation of the node correspondence process, where nodes relating to identical processes across process and input-output data are identified, remains a challenge. This is due to varied dataset coverage, different levels of disaggregation between data sources, and lack of detail of activities and coverage for specific processes. However, by automating other aspects of the compilation of a hybrid LCI, the comprehensive supply chain coverage afforded by hybrid analysis is able to be made more accessible to the broader LCA community. Conclusions This study shows that it is possible to automate various aspects of a hybrid LCI in order to address traditional barriers to its uptake. The object-oriented approach used enables the data or other aspects of the model to be easily updated to contextualise an analysis in order to calculate hybrid values for any environmental flow for any variety of products in any region of the world. This will improve environmental decision-making, critical for addressing the pressing global environmental issues of our time.

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As global population and urbanization increase, so do the direct and indirect environmental impacts of construction around the world. Low-impact products, buildings, precincts and cities are needed to mitigate the effects of building construction and use. Analysis of embodied energy and greenhouse gas (GHG) emissions across these scales is becoming more important to support this direction. The calculation of embodied impacts requires rigorous, flexible and comprehensive assessment tools. Firstly, we present the Australian Industrial Ecology Virtual Laboratory (IELab) as one such tool discussing its structure, function and wide scope of application. Secondly, we demonstrate its potential high level of resolution in a case study: assessing embodied GHG emissions in an aluminium-framed window by combining productspecific life-cycle inventory data. The input-output analysis at the core of the IELab is mathematically comprehensive in the assessment of direct and indirect impacts and the tool can be applied at a range of scales from building component, to precincts and cities, or to the entire construction industry. IELab uses a flexible formalism that enables consistent harmonisation of diverse datasets and tractable updating of input data. The emissions and energy database supporting IELab has detailed data, aligning with economic accounts and data on labour, water, materials and waste that enrich assessment across other dimensions of sustainability. IELab is a comprehensive, flexible and robust assessment tool well positioned to respond to the challenge of assessing and aiding the design of a low-impact built environment.

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