A GIS based method to calculate regionalized land use characterization factors for life cycle impact assessment using LANCA®

Purpose Land is used and modified in its natural function for the cultivation of food and energy crops, for infrastructure and other production purposes. Despite their global significance, land use impacts are still rarely addressed, although methods for integrating land use into Life Cycle Assessment (LCA) have been developed recently. This paper describes the development and calculation of regionalized characterization factors based on the LANCA (R) (Land Use Indicator Value Calculation in Life Cycle Assessment) method to be integrated into LCA using a geo information system (GIS). Methods With the publication of the LANCA (R) characterization factors (Bos et al. 2016), land use impacts can be assessed at the country level. However, soil parameters as well as climatic conditions change on a small scale and are very site-specific. Therefore, there is a need for regionalized characterization factors. After a literature review, we describe the development of the five LANCA (R) indicators. Afterwards we present the conceptual framework for the calculation of GIS-based characterization factors and apply this framework to two examples, the indicators of mechanical filtration and physicochemical filtration. Finally, we apply the characterization factors in a case study. Results, application and discussion The region-specific characterization factors are calculated in a GIS environment yielding a map with values for mechanical filtration and physicochemical filtration per grid cell for various land use types. A case study shows that land use impacts fluctuate due to site-specific conditions such as pedological, topographical and climatic conditions. It can be shown that our calculation of regionalized characterization factors in global maps is feasible and facilitates an area's potential for causing lower environmental impacts for a certain land use compared to other areas. Remaining challenges are related to input data quality, the comprehensibility of the results to practitioners that are not land use experts and the technical restrictions of LCA database and software providers. Conclusions Through the presented regionalization of the LANCA (R) framework, a necessary prerequisite to method advancement is met as also region-specific characterization factors can now be calculated. In comparison to the published country-specific characterization factors in Bos et al. (2016), the developed regional GIS-based characterization factors are far more advantageous especially for large countries. Nevertheless, it has to be noted that an LCA including the evaluation of land use does not replace methods and tools like environmental impact assessment. When deciding on a preferable location for a specific land use nature conservation, geographical, geological and building law aspects must also be taken into account.