Increasing needs for decision support and advances in scientific knowledge within life cycle assessment (LCA) led to substantial efforts to provide global guidance on environmental life cycle impact assessment (LCIA) indicators under the auspices of the UNEP-SETAC Life Cycle Initiative. As part of these efforts, a dedicated task force focused on addressing several LCIA cross-cutting issues as aspects spanning several impact categories, including spatiotemporal aspects, reference states, normalization and weighting, and uncertainty assessment. Here, findings of the cross-cutting issues task force are presented along with an update of the existing UNEP-SETAC LCIA emission-to-damage framework. Specific recommendations are provided with respect to metrics for human health (Disability Adjusted Life Years, DALY) and ecosystem quality (Potentially Disappeared Fraction of species, PDF). Additionally, we stress the importance of transparent reporting of characterization models, reference states, and assumptions, in order to facilitate cross-comparison between chosen methods and indicators. We recommend developing spatially regionalized characterization models, whenever the nature of impacts shows spatial variability and related spatial data are available. Standard formats should be used for reporting spatially differentiated models, and choices regarding spatiotemporal scales should be clearly communicated. For normalization, we recommend using external normalization references. Over the next two years, the task force will continue its effort with a focus on providing guidance for LCA practitioners on how to use the UNEP-SETAC LCIA framework as well as for method developers on how to consistently extend and further improve this framework

Purpose Geospatial details about land use are necessary to assess its potential impacts on biodiversity. Geographic information systems (GIS) are adept at modeling land use in a spatially explicit manner, while life cycle assessment (LCA) does not conventionally utilize geospatial information. This study presents a proof-of-concept approach for coupling GIS and LCA for biodiversity assessments of land use and applies it to a case study of ethanol production from agricultural crops in California. Materials and methods GIS modeling was used to generate crop production scenarios for corn and sugar beets that met a range of ethanol production targets. The selected study area was a four-county region in the southern San Joaquin Valley of California, USA. The resulting land use maps were translated into maps of habitat types. From these maps, vectors were created that contained the total areas for each habitat type in the study region. These habitat compositions are treated as elementary input flows and used to calculate different biodiversity impact indicators in a second paper (Geyer et al., submitted). Results and discussion Ten ethanol production scenarios were developed with GIS modeling. Current land use is added as baseline scenario. The parcels selected for corn and sugar beet production were generally in different locations. Moreover, corn and sugar beets are classified as different habitat types. Consequently, the scenarios differed in both the habitat types converted and in the habitat types expanded. Importantly, land use increased nonlinearly with increasing ethanol production targets. The GIS modeling for this study used spatial data that are commonly available in most developed countries and only required functions that are provided in virtually any commercial or opensource GIS software package. Conclusions This study has demonstrated that GIS-based inventory modeling of land use allows important refinements in LCA theory and practice. Using GIS, land use can be modeled as a geospatial and nonlinear function of output. For each spatially explicit process, land use can be expressed within the conventional structure of LCA methodology as a set of elementary input flows of habitat types.

Purpose Geospatial details about land use are necessary to assess its potential impacts on biodiversity. Geographic information systems (GIS) are adept at modeling land use in a spatially explicit manner, while life cycle assessment (LCA) does not conventionally utilize geospatial information. This study presents a proof-of-concept approach for coupling GIS and LCA for biodiversity assessments of land use and applies it to a case study of ethanol production from agricultural crops in California. Materials and methods In Part 2 of this paper series, four biodiversity impact indicators are presented and discussed, which use the inventory data on habitat composition and sizes from the GIS-based inventory modeling in Part 1 (Geyer et al. 2010). The concepts used to develop characterization models are hemeroby, species richness, species abundance, and species evenness. The biodiversity assessments based on species richness, abundance, and evenness use a species-habitat suitability matrix which relates 443 terrestrial vertebrate species native to California to the 29 habitat types that occur in the study area. Results and discussion The structural similarities and differences of all four characterization models are discussed in some detail. Characterization factors and indicator results are calculated for each of the four characterization models and the 11 different land use scenarios from Part 1 of this paper series. For the sugar beet production scenarios, the indicator results are in fairly good agreement. For the corn production scenarios, however, they come to fundamentally different results. The overall approach of using GIS-based inventory data on land use together with information on species-habitat relationships is not only feasible but also grounded in ecological science and well connected with existing life cycle impact assessment efforts. Conclusions Excluding biodiversity impacts from land use significantly limits the scope of LCA. Accounting for land use in inventory modeling is dramatically enhanced if LCA is coupled with GIS. The resulting inventory data are a sound basis for biodiversity impact assessments, in particular if coupled with information on species-habitat relationships. However, much more case studies and structural analysis of indicators is required, together with an evaluation framework that enables comparisons and ranking of indicators. Responsible editor: Llorenc Milà i CanalsPreamble The present paper is the second in a series of two that demonstrate the potential of coupling geographic information system (GIS) technology with LCA for assessing biodiversity impacts of land use. This first paper demonstrated the use of GIS-based inventory modeling to generate elementary input flows of habitat types. This second paper presents four different characterization models that are applied to the habitat flows to calculate biodiversity impact indicators.

Purpose: In the light of anthropogenic resource depletion and the resulting influences on the greenhouse effect as well as globally occurring famine, food waste has garnered increased public interest in recent years. The aim of this study is to analyze the environmental impacts of food waste and to determine to what extent consumers' behavior influences the environmental burden of food consumption in households. Methods: A life cycle assessment (LCA) study of three food products is conducted, following the ISO 14040/44 life cycle assessment guidelines. This study addresses the impact categories climate change (GWP100), eutrophication (EP), and acidification (AP). Primary energy demand (PED) is also calculated. For adequate representation of consumer behavior, scenarios based on various consumer types are generated in the customer stage. The customer stage includes the food-related activities: shopping, storage, preparation, and disposal of food products as well as the disposal of the sales packaging. Results and discussion: If the consumer acts careless towards the environment, the customer stage appears as the main hotspot in the LCA of food products. The environmental impact of food products can be reduced in the customer stage by an environmentally conscious consumer. Shopping has the highest effect on the evaluated impact categories and the PED. Additionally, consumers can reduce the resulting emissions by decreasing the electric energy demand, particularly concerning food storage or preparation. Moreover, results show that the avoidance of wasting unconsumed food can reduce the environmental impact significantly. Conclusions: Results of this study show that the influence of consumer behavior on the LCA results is important. The customer stage of food products should not be overlooked in LCA studies. To enable comparison among results of other LCA studies, the LCA community needs to develop a common methodology for modeling consumer behavior

Land use and land use change are among the main drivers of the ongoing loss of biodiversity at a global-scale. Although there are already Life Cycle Impact Assessment (LCIA) methods to measure this impact, they are still rarely used by companies and municipalities in the life cycle assessment of products and processes. Therefore, this paper highlights four main requirements for a biodiversity methodological framework within LCIA in order to facilitate biodiversity assessments: first, to consider the global uneven distribution of biodiversity and its risks with respect to vulnerability and irreplaceability; second, to account for the need to regionalize the impacts of land use; third, to consider the specific impacts that different land use types have on biodiversity; and fourth, to analyze the biodiversity impacts of different land use management parameters and their influence on the intensity of land use. To this end, we provided a review of existing methods in respect to conformity and research gaps. The present publication describes the development of a new methodological framework that builds on these requirements in a three-level hierarchical framework, which enables the assessment of biodiversity in LCA at a global-scale. This publication reveals research gaps regarding the inclusion of proactive and reactive conservation concepts as well as methods of land management into LCIA methodology. The main objective of this concept paper is therefore to describe a new methodological framework for the assessment of biodiversity in the LCA that could fill some of the research gaps, including compilation and suggestion of suitable data sets. The conclusion discusses both the benefits and limitations of this framework.