Input/Output Analysis - Shortcuts to Life Cycle Data?


The report contains the papers presented to a workshop held in Copenhagen on the 29th of September 2000, as well as a résumé of the subsequent discussions, and a few additional papers on the topic.


Can Input-Output Analysis (IOA) data and methodologies be used to improve the performance of Life Cycle Assessment (LCA)? And if so, are there any specific initiatives that need to be taken for Danish LCAs to take advantage of this? These are the key questions that this report seeks to elucidate.

The workshop and this report has been financially supported by the Danish Environmental Protection Agency and has been followed by a supervisory group composed of the project manager Bo Weidema, 2.-0 LCA consultants, Erik Hansen, COWI, Mariane Hounum, The Danish EPA, Anders Schmidt, dk- TEKNIK, and Søren Varming, Elsamprojekt A/S.

The international nature of the workshop was only possible due to the in-kind contributions of the foreign participants (see also Annex B), for which we wish to express our special gratitude.

Outline of the Topic and the Content of the Report

LCA has traditionally been performed as a bottom-up process analysis, based on linking the specific processes in a supply chain. Exceptions to this approach may be found, especially in the early LCA work in Japan, which was often based on IOA. The process-based method is explained in more detail by Marianne Wesnæs in Chapter 3, who also points out its capability for detail as a significant advantage of this approach. However, a major problem in process-based LCA is the likelihood that important parts of the product systems are left out of the analysis, simply because it is a very difficult task to follow the entire supply chain in detail. As pointed out by Manfred Lenzen in Chapter 4, up to 50% of the environmental exchanges related to a product can be left out, thus possibly leading to erroneous conclusions.

IOA is a top-down approach in which the statistical data on production and consumption in individual industrial sectors allows a complete allocation of all activities to all products. By linking this with statistical information on environmental exchanges for the same sectors, an LCA-like result can be obtained. The procedures involved are described by Anne Merete Nielsen in Chapter 4 and an example is provided by Jesper Munksgaard in Chapter 6. The Danish IO-tables and their application to physical and environmental accounting are described by Ole Gravgård Pedersen in Chapter 7. IOA has the advantage of being complete with regard to inclusion of all relevant activities related to a product. However, the IOA is not very detailed, since it relies on a grouping of activities in a limited number of sectors (ranging from below 100 in Germany to around 800 in Japan). This makes it difficult to use for detailed LCA purposes, except for very homogenous sectors. Also, the necessary environmental statistics is not always available, which means that for some environmental exchanges, adequate information will be missing.

Combining process-based LCA and IOA in what has become known as “hybrid analysis” can yield a result that has the advantages of both methods (i.e. both detail and completeness). This is further elaborated by Manfred Lenzen in Chapter 4 and by Anne Merete Nielsen in Chapter 8. In the update of Dutch LCA methodology guide (Guinée et al. 2000), the use of a hybrid approach is also recommended as a procedure for filling data gaps.

Most often IOA has covered only energy related emissions, but the examples in Chapters 10, 11 and 12 clearly demonstrate that IOA and similar approaches can be expanded to include many diverse types of environmental exchanges and effects.

The basis of IOA in national production and consumption statistics is the cause of another limitation of IOA, namely the assumption that imports are produced in the same way as domestic production. This assumption is especially problematic in very small and open economies with large imports and exports. It is well known, also from process-based LCA, that production technologies vary significantly between geographical regions. A possible solution to the import assumption is a multi-regional IOA-model as suggested by Sangwon Suh and Gjalt Huppes in Chapter 13.

For process-based LCA, an important methodological improvement has been the introduction of prospective, market-based methods for identifying the processes and technologies to include in the studied systems (see e.g. Weidema 1999). This provides a more realistic modelling of the consequences of a change in product output as compared to the traditional use of average, historical data. IOA is also extensively used for prospective purposes (predicting the consequences of a suggested change) in spite of its clear basis in historical average data. Thus, an important improvement to the current IOA could be the development of IO-tables that take into account dynamic aspects such as technologies ability to change over time. In Chapter 14 Tom Gloria addresses part of this issue with his dynamic life cycle approach based on temporal IO-modelling.

The Main Conclusions

The discussions following the presentations in Chapters 2 to 14 were divided in two:

    Those taking place immediately on the workshop (and reported in Chapter 15) involving all workshop participants (see the participants list in Annex A).

    Those taking place mainly among the foreign experts on their separate meeting on the day after the workshop (and reported in Chapter 16).

Both discussions reached similar conclusions, which may be summarised as follows:

There was general agreement that product related questions could not be answered adequately by IOA alone. Thus, it is not a question of IOA or process-based LCA, but rather a question of improving process-based LCA by the addition of IO-based data or IOA methods, i.e. in the form of hybrid methods.

A very promising hybrid approach seems to be the one proposed by Treloar (1997). First, the assessment is carried out merely with IO-data. Secondly, the chains are ranked according to the relative contribution to the total result, thus implying a data collection strategy. Third and finally, process data can be collected until the desired level of accuracy is reached. The method may be especially useful if combined with (possibly estimated) uncertainties for each value in the IO-model.

To supply currently available environmental IO-data in a form suitable for LCAsoftware and -databases is a relatively simple task, and does not necessarily demand any particular software, although the use of hybrid approaches may be facilitated by such software as suggested by Greg Norris and Sangwon Suh.

A need was identified to inform those responsible for collecting statistics (both environmental and economic) about the requirements from the side of environmental product assessment.

There was general support for the idea of overcoming the import assumption in current IO-data through the development of a multi-regional IOA-model.

There was general agreement that the introduction of dynamic and market-based (marginal) modelling to IOA would be an important improvement for (prospective) decision support and a topic for future research. It was agreed that it is mainly a data problem to identify the constraints that the technologies are subject to.

As a follow-up of the expert meeting in Copenhagen, Greg Norris, Gjalt Huppes of Leiden University, and Bo Weidema held a meeting with Japanese researchers (Yuichi Moriguchi, Hiroki Hondo, Masanobu Ishikawa, and others) in Tsukuba on the 1st of November 2000. At this meeting Japanese support for the multi-regional model was obtained. Also in Japan, Greg Norris and Bo Weidema agreed with Dolf Gielen and Yuichi Moriguchi of the National Institute of Environmental Studies to start investigating the options for developing a dynamic, market-based, environmental IO-table.

Specifically for the Danish situation, the following initiatives may be proposed:

    Providing the available environmental IO-data in a form directly applicable in current Danish LCA software and LCA databases.

    Establishing procedures for updating and improving such data from the perspective of LCA practice, in cooperation with those responsible for collecting environmental and economic statistics.

    Using Danish environmental IO-data (possibly with the addition of estimated uncertainties) to test the approach of Treloar (1997) on a Danish LCA case study.

    Providing Danish input to the multi-regional IO-model under development by CML in Leiden.

    Providing Danish input to the development of a dynamic, market-based, environmental IO-table.

It should be noted that the above interpretation of the discussion and its conclusions are the sole responsibility of the authors of this report.

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