A method for assessing the environmental impacts of freshwater consumption was developed. This method considers damages to three areas of protection: human health, ecosystem quality, and resources. The method can be used within most existing life-cycle impact assessment (LCIA) methods. The relative importance of water consumption was analyzed by integrating the method into the Eco-indicator-99 LCIA method. The relative impact of water consumption in LCIA was analyzed with a case study on worldwide cotton production. The importance of regionalized characterization factors for water use was also examined in the case study. In arid regions, water consumption may dominate the aggregated life-cycle impacts of cotton-textile production. Therefore, the consideration of water consumption is crucial in life-cycle assessment (LCA) studies that include water-intensive products, such as agricultural goods. A regionalized assessment is necessary, since the impacts of water use vary greatly as a function of location. The presented method is useful for environmental decision-support in the production of water-intensive products as well as for environmentally responsible value-chain management.

Water scarcity has become a major constraint to socio‐economic development and a threat to livelihood in increasing parts of the world. Since the late 1980s, water scarcity research has attracted much political and public attention. We here review a variety of indicators that have been developed to capture different characteristics of water scarcity. Population, water availability, and water use are the key elements of these indicators. Most of the progress made in the last few decades has been on the quantification of water availability and use by applying spatially explicit models. However, challenges remain on appropriate incorporation of green water (soil moisture), water quality, environmental flow requirements, globalization, and virtual water trade in water scarcity assessment. Meanwhile, inter‐ and intra‐annual variability of water availability and use also calls for assessing the temporal dimension of water scarcity. It requires concerted efforts of hydrologists, economists, social scientists, and environmental scientists to develop integrated approaches to capture the multi‐faceted nature of water scarcity.

Life cycle assessment (LCA) has been used to assess freshwater-related impacts according to a new water footprint framework formalized in the ISO 14046 standard. To date, no consensus-based approach exists for applying this standard and results are not always comparable when different scarcity or stress indicators are used for characterization of impacts. This paper presents the outcome of a 2-year consensus building process by the Water Use in Life Cycle Assessment (WULCA), a working group of the UNEP-SETAC Life Cycle Initiative, on a water scarcity midpoint method for use in LCA and for water scarcity footprint assessments.

Research on the environmental impacts from the global value chain of plastics has typically focused on the disposal phase, considered most harmful to the environment and human health. However, the production of plastics is also responsible for substantial environmental, health and socioeconomic impacts. We show that the carbon and particulate-matter-related health footprint of plastics has doubled since 1995, due mainly to growth in plastics production in coal-based economies. Coal-based emissions have quadrupled since 1995, causing almost half of the plastics-related carbon and particulate-matter-related health footprint in 2015. Plastics-related carbon footprints of China’s transportation, Indonesia’s electronics industry and India’s construction sector have increased more than 50-fold since 1995. In 2015, plastics caused 4.5% of global greenhouse gas emissions. Moreover, 6% of global coal electricity is used for plastics production. The European Union and the United States have increasingly consumed plastics produced in coal-based economies. In 2015, 85% of the workforce required for plastics consumed by the European Union and the United States was employed abroad, but 80% of the related value added was generated domestically. As high-income regions have outsourced the energy-intensive steps of plastics production to coal-based economies, renewable energy investments throughout the plastics value chain are critical for sustainable production and consumption of plastics.

The water footprint has been introduced as a potential sustainability indicator for human-induced water consumption, and has frequently been studied at local, national and international scales during the last decade. While water footprints are sometimes understood as a measure that includes environmental impact assessment, the water footprint as used in this paper refers to volumes of water consumed, without including weighting procedures to allow for the assessment of impacts. Two types of approaches have been applied to calculate the water footprint in the literature: bottom-up and top-down approaches. This study compares and discusses advantages and limitations of the water footprint of nations based on two input–output top-down approaches (Water Embodied in Bilateral Trade (WEBT) and Multi-regional Input–Output Analysis (MRIO)) and of the existing national water footprint accounts from the literature based on the bottom-up approach. The differences in the bottom-up and WEBT approaches are caused by inter-sectoral cut-off, because bottom-up approaches do not consider the entire industrial supply chains, while the WEBT method covers the water footprint by tracing the whole domestic supply chain of each country. The differences in the WEBT and MRIO approaches are due to an inter-regional cut-off effect, as the WEBT approach only traces domestic supply chains whereas the MRIO approach traces entire global supply chains. We found that both bottom-up and top-down approaches are heavily dependent on the quality of existing datasets, and differ substantially. The total water footprints of nations based on different approaches vary by up to 48%, and this variation is even larger at the sector level.