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Input/Output analysis - Shortcuts to life cycle data?

8. Hybrid LCA

Anne Merete Nielsen, 2.-0 LCA Consultants

As pointed out by Manfred Lenzen in Chapter 4, process-based analyses, while accurate, are incomplete in framework and suffer from a truncation error of an unknown size. Therefore conventional Life Cycle Assessment (LCA) is likely to ignore processes connected to services, small inputs, and the manufacture of complex products from basic materials. Input-output analysis (IOA) methods, while comprehensive in framework, are subject to inherent errors due to the use of economic data to simulate physical flows and the aggregation of the whole economy into one relatively simple matrix.

Several attempts have been made to unite LCA and IOA. In such hybrid analysis, process analysis data and IO-data are combined, with the aim of reducing these errors. The hybrid analyses take starting point in either process-based or IO-based analysis.

8.1 Process-based hybrid analysis

The basis of all process-based hybrid analysis methods is the assumption that the errors in the IO-model for the sector which produces a particular product can be avoided or decreased by defining the inputs into the main process in terms of physical units. Inherent in IOA lies the assumption that within one production sector, environmental effects are proportional to the price of the product. Process-based hybrid analysis replaces the price-proportionality assumption with an assumption of proportionality according to physical units.

In a process-based hybrid analysis the product quantities for the individual product are collected as is done in a conventional LCA, but the environmental data are derived using IOA. Many researchers have demonstrated this method, (in Treloar (1998) the following are mentioned: Bullard et al. (1978), Oka et al. (1993), McArdle et al. (1993), Pullen (1995), and Fay (1998)).

Like conventional process-based LCA, also the process-based hybrid analyses suffer from the problem of incompleteness, although it is limited to the first stage of the inventory, i.e. the description of the product quantities. The truncation error remains, although diminished.

Another problem is that process-based hybrid analysis offers no method to estimate the incompleteness of the study, making the choice of which data to collect and improve subjective. The most time-consuming part of a process-based analysis is often the data collection; therefore it is a clear weakness if this time is likely to be spent inefficiently.

In summary, the hybrid version of process-based analyses offers the IO-tables as an additional source for data collection, but the problems concerning truncation and efficient data collection is only partly solved.

8.2 Input-output-based hybrid analysis

IO-based hybrid methods all take starting points in a conventional IOA of one or more environmental impacts. Single data in the IOA are substituted with process analysis data, or one or more groups of data in the IOA are substituted with process analysis data by adding a column to the IO-model. The products or processes considered most important may be split out to form individual "sectors" within the IO-model. (Cobas-Flores et al. 1996 cf. Treloar, 1998).

Substituting single data may introduce unwanted indirect effects, since all data, whether reflecting direct or indirect effects, are mixed. Treloar (1998) suggests that this is likely to exacerbate the effects of the homogeneity and proportionality assumptions inherent to the IO-model.

Furthermore it is likely that the selection of sectors for further investigation will involve a subjective decision-making process. Therefore a procedure is needed to identify the most important data to improve. Such a method is suggested by Treloar (1997): First, the assessment is carried out merely with IO-data. Secondly, the entire production system is decomposed into groups of processes, called paths. The chains are ranked according to the relative contribution to the total result. Finally, process data can be collected until the desired level of accuracy is reached. The clear force of this IO-based hybrid method is that it implies a data collection strategy, aiming at using time for data collection efficiently.

8.3 References

Cobas-Flores, E., Hendrickson, C.T., Lave, L.B. and McMichael, F.C. (1996) Life-Cycle Analysis of Batteries Using Input-Output Analysis, Proceedings: 1996 International Symposium on Electronics and the Environment, np.

Fay, R. (1998) Life-Cycle Energy: A Method of Assessing the Long-Term Environmental Impact of Buildings, Proceedings: Buildings and the Environment in Asia, Singapore, February 11-13, pp. 119-123.

McArdle, S.A., Moylan, S.J., Pedler, S.D.M. and Webb, G.J. (1993) Case Study Analysis of the Embodied Energy of Office Construction, Joint Final Year Bachelor of Architecture Thesis, Deakin University, Geelong.

Oka, T., Suzuki, M., and Konnya, T. (1993) The Estimation of Energy Consumption and Amounts of Pollutants due to the Construction of Buildings, Energy and Buildings, No. 19, pp. 303-311.

Pullen, S. (1995) Embodied Energy of Building Materials in Houses, Master of Building Science thesis, University of Adelaide, Adelaide, 184 p.

Suh, S and Huppes G. (2000). Environmentally extended Input-Output Analysis of the industrialised world for supporting the evaluation of technology changes. EnvIOA project description version 10. Netherland: Leiden University, CML.

Treloar, G.J. (1997). Extracting embodied energy paths from input-output tables: Towards an input-output-based hybrid energy analysis method. Economic Systems Research, vol.9, no.4.

Treloar, G.J. (1998). A Comprehensive Embodied Energy Analysis. Australia: Faculty of Science and Technology, Deakin University.

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