Background, aim, and scope  

When dealing with system delimitation in environmental life cycle assessment (LCA), two methodologies are typically referred to: consequential LCA and attributional LCA. The consequential approach uses marginal data and avoids co-product allocation by system expansion. The attributional approach uses average or supplier-specific data and treats co-product allocation by applying allocation factors. Agricultural LCAs typically regard local production as affected and they only include the interventions related to the harvested area. However, as changes in demand and production may affect foreign production, yields and the displacement of other crops in regions where the agricultural area is constrained, there is a need for incorporating the actual affected processes in agricultural consequential LCA. This paper presents a framework for defining system boundaries in consequential agricultural LCA. The framework is applied to an illustrative case study; LCA of increased demand for wheat in Denmark. The aim of the LCA screening is to facilitate the application of the proposed methodology. A secondary aim of the LCA screening is to illustrate that there are different ways to meet increased demand for agricultural products and that the environmental impact from these different ways vary significantly.

Materials and methods  

The proposed framework mainly builds on the work of Ekvall T, Weidema BP (Int J Life Cycle Assess 9(3):pp. 161–171, 2004), agricultural statistics (FAOSTAT, FAOSTAT Agriculture Data, Food and Agriculture Organisation of the United Nations (2006), http://apps.fao.org/ (accessed June)), and agricultural outlook (FAPRI, US and world agricultural outlook, Food and Agriculture Research Institute, Iowa, 2006a). The framework and accompanying guidelines concern the suppliers affected, the achievement of increased production (area or yield), and the substitutions between crops. The framework, which is presented as a decision tree, proposes four possible systems that may be affected as a result of the increased demand of a certain crop in a certain area.

Results  

The core of the proposed methodology is a decision tree, which guides the identification of affected processes in consequential agricultural LCA. The application of the methodology is illustrated with a case study presenting an LCA screening of wheat in Denmark. Different scenarios of how increased demand for wheat can be met show significant differences in emission levels as well as land use.

Discussion  

The great differences in potential environmental impacts of the analysed results underpin the importance of system delimitation. The consequential approach is appointed as providing a more complete and accurate but also less precise result, while the attributional approach provides a more precise result but with inherent blind spots, i.e. a less accurate result.

Conclusions  

The main features of the proposed framework and case study are: (1) an identification of significant sensitivity on results of system delimitation, and (2) a formalised way of identifying blind spots in attributional agricultural LCAs.

Recommendations and perspectives  

It is recommended to include considerations on the basis of the framework presented in agricultural LCAs if relevant. This may be done either by full quantification or as qualitative identification of the most likely ways the agricultural product system will respond on changed demand. Hereby, it will be possible to make reservations to the conclusions drawn on the basis of an attributional LCA.