Developing Product Environmental Footprint Category Rules (PEFCR) for shampoos: The basis for comparable life cycle assessment.

In 2013, the European Commission launched the Environmental Footprint Rules pilot phase. This initiative aims at setting specific rules for life cycle assessment (LCA: raw material sourcing, production, logistics, use, and disposal phase) studies within 1 product category, called product environmental footprint category rules (PEFCR), and for organizations, called organizational environmental footprint sector rules (OEFSR). Such specific rules for measuring environmental performance throughout the life cycle should facilitate the comparability between LCA studies and provide principles for communicating environmental performance, such as transparency, reliability, completeness, and clarity. Cosmetics Europe, the association representing the cosmetics industry in the European Union, completed a voluntary study into the development of PEFCR for shampoo, generally following the guidelines and methodology developed by the European Commission for its own pilot projects. The study assessed the feasibility and relevance of establishing PEFCR for shampoo. Specifically, the study defines a large number of modeling assumptions and default values relevant for shampoo (e.g., for the functional unit, the system boundaries, default transport distances, rinsing water volumes, temperature differences, life cycle inventory data sources) that can be modified as appropriate, according to the specificities of individual products, manufacturing companies, and countries. The results of the study may be used to support internal decision making (e.g., to identify "hotspots" with high environmental impact and opportunities for improvement) or to meet information requests from commercial partners, consumers, media, or authorities on product environmental characteristics. In addition, the shampoo study also highlighted many of the challenges and limitations of the current product environmental footprint (PEF) methodology, namely its complexity and resource intensiveness. It highlighted 2 areas where improvements are much needed: (1) data quality and availability, and (2) impact assessment methodologies and robustness. Many of the findings are applicable to other rinse-off cosmetic products, such as shower gels, liquid soaps, bath products, and hair conditioners. Integr Environ Assess Manag 2018;14:649-659. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Spatial Variability and Uncertainty of Water Use Impacts from U.S. Feed and Milk Production.

This paper addresses water use impacts of agriculture, developing a spatially explicit approach tracing the location of water use and water scarcity related to feed production, transport, and livestock, tracking uncertainties and illustrating the approach with a case study on dairy production in the United States. This approach was developed as a step to bring spatially variable production and impacts into a process-based life cycle assessment (LCA) context. As water resources and demands are spatially variable, it is critical to take into account the location of activities to properly understand the impacts of water use, accounting for each of the main feeds for milk production. At the crop production level, the example of corn grain shows that 59% of water stress associated with corn grain production in the United States is located in Nebraska, a state with moderate water stress and moderate corn production (11%). At the level of milk production, four watersheds account for 78% of the national water stress impact, as these areas have high milk production and relatively high water stress; it is the production of local silage and hay crops that drives water consumption in these areas. By considering uncertainty in both inventory data and impact characterization factors, we demonstrate that spatial variability may be larger than uncertainty, and that not systematically accounting for the two can lead to artificially high uncertainty. Using a nonspatial approach in a spatially variable setting can result in a significant underestimation or overestimation of water impacts. The approach demonstrated here could be applied to other spatially variable processes.