Water footprint of German agricultural imports: Local impacts due to global trade flows in a fifteen-year perspective

Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products

A 5-scale label that relativizes the environmental impact of a given product referred to the impact of the European food basket is proposed. It was developed based on the Product Environmental Footprint methodology with the following stepwise approach. First, a set of normalization and weighting factors were defined to aggregate all the environmental impact categories into a single dimensionless index referred to as the European food basket, coined the European Food Environmental Footprint Single Index (EFSI). Next, the effectiveness of the EFSI index was evaluated by assessing the distribution of the EFSI results on 149 hypothetical food items and comparing it with the results obtained with EC Single Score. Finally, the thresholds to translate the EFSI index into the 5-scale Enviroscore (A, B, C, D, and E) were established and validated using the Delphi method. Results indicated that both, Enviroscore and EFSI, were able to account for impact variability between and within food products. Differences on the final score were observed due to the type of products (vegetables vs. animal products), the country of origin and the mean of transportation. Regarding country of origin, results indicated that differences in water stress impact category were better captured by the EFSI index (r = 0.624) than by the EC Single Score (r = 0.228). Finally, good agreement achieved with the Delphi method (weighted Kappa 0.642; p = 0.0025), ensures the acceptability of the Enviroscore. In conclusion, this study developed a method to communicate environmental impact assessment in a front-of-packaging label.

Savings and Losses of Scarce Virtual Water in the International Trade of Wheat, Maize, and Rice

The international cereal trade can mitigate global water stress by saving virtual scarce water (VSW). Based on bilateral trade data, this study assessed VSW savings and losses in the international trade of three major cereals (i.e., wheat, maize, and rice) from 2008 to 2017 by incorporating the water stress index (WSI) into a virtual water assessment. We found that the trade in wheat and maize saved a significant amount of VSW, while the rice trade led to increasingly severe losses of VSW. This study identified the top trades of VSW savings and losses for each cereal. Wheat and maize were primarily exported from the countries that are relatively abundant in water resources (e.g., United States, Brazil, Argentina, Russia) to water-scarce countries (e.g., Mexico and Egypt), whereas rice was exported mainly from India and Pakistan, two of the most water-stressed countries. We suggest that policy makers consider VSW savings and losses when making cereal trading decisions to alleviate global water stress.

Exploring the optimal crop planting structure to balance water saving, food security and incomes under the spatiotemporal heterogeneity of the agricultural climate

Crop planting provided foods, generated incomes, and consumed water resources to different extents under different spatiotemporal agroclimatic conditions. For balancing three aspects, targeting the rice, maize, wheat, and sorghum planted in Liaoning during the recent two decades, we established an integrated research framework consisting of water footprint (WF) accounting, clustering analysis, and fuzzy optimization programming to quantify the temporal trends and spatial distribution of water footprints, and optimized the planting structure under the different spatiotemporal agroclimatic conditions. Results showed that the maximum water footprint differences were 4166.73 m³/t and 4790.71 m³/t in spatial distribution and temporal series, respectively. Based on precipitation, we established 12 agroclimatic scenarios according to K-Means clustering. The fuzzy optimization result indicated that the planting area percent ranges of maize, wheat, rice, and sorghum in Liaoning province were 4.96%-98.62%, 0.00%-8.55%, 0.00%-18.18%, and 0.00%-95.04%, respectively under the different spatiotemporal conditions. This study's methods and results help make targeted decisions related to grain planting structure while considering the complex spatial-temporal conditions.

Life Cycle Blue and Grey Water in the Supply Chain of China’s Apparel Manufacturing

Apparel manufacturing involves high water consumption and heavy water pollution in its supply chain, e.g., planting cotton, producing chemical fibers, and dyeing. This study employs a multi-regional input–output (MRIO) model to (1) assess the life cycle of blue and grey water (chemical oxygen demand (COD) specific) of China’s apparel manufacturing; (2) reveal the hidden linkage among sectors and regions in the whole supply chain; and (3) identify the key regions and upstream sectors with the most water consumption and heaviest water pollution. We found that the agricultural sector (i.e., planting fiber crops) is responsible for primary water consumption and water pollution. In addition, different provinces assume different production roles. Guangdong is a major output province in apparel manufacturing. However, its economic output is contributed to by other regions, such as blue water from Xinjiang and Jiangsu and grey water from Hebei and Shandong. Our research reveals the significance of taking an inter-regional perspective on water resource issues throughout the supply chain in apparel manufacturing. The sustainable development of China’s apparel manufacturing relies on improving water-use efficiency and reasonable industrial layout. The results are of significance and informative for policymakers to build a water-sustainable apparel industry.

Blue water footprint linked to national consumption and international trade is unsustainable

Increasing pressure on the world's freshwater resources raises serious concerns about global food security and the sustainability of water use in agriculture. Here we quantify and map at a 5-arcmin spatial resolution the blue water footprint of each country's national consumption and where they infringe sustainable environmental flows as defined by the presumptive environmental flow standard or the 80% rule, in which runoff depletion by more than 20% will pose risk to ecosystems. We find that 52% of the blue water footprint of global consumption and 43% of international blue virtual water flows come from places where the sustainable environmental flow is violated. About 22% of the environmental flow infringement of the blue water footprint of global consumption lies outside the specific countries of consumption, indicating that a number of them have externalized their impacts. By establishing a link between the consumption of a product in one place and water scarcity in places far from the place of consumption, our assessment may aid a dialogue on how to assign and share responsibilities concerning water use.

The Water Footprint of Global Food Production

Agricultural production is the main consumer of water. Future population growth, income growth, and dietary shifts are expected to increase demand for water. The paper presents a brief review of the water footprint of crop production and the sustainability of the blue water footprint. The estimated global consumptive (green plus blue) water footprint ranges from 5938 to 8508 km3/year. The water footprint is projected to increase by as much as 22% due to climate change and land use change by 2090. Approximately 57% of the global blue water footprint is shown to violate the environmental flow requirements. This calls for action to improve the sustainability of water and protect ecosystems that depend on it. Some of the measures include increasing water productivity, setting benchmarks, setting caps on the water footprint per river basin, shifting the diets to food items with low water requirements, and reducing food waste.

Spatial-temporal assessment of agricultural virtual water and uncertainty analysis: The case of Kazakhstan (2000-2016)

In this study, a fuzzy-vertex-based virtual-water analysis method (FVAM) is developed for assessing the virtual water content (VWC) of main agricultural products, imports, and exports at a national scale. FVAM has advantages in quantifying state-level VWC with a bottom-up approach and reflecting uncertain parameters based on vertex analysis technique. FVAM is applied to a real case of Kazakhstan in Central Asia. Results reveal that (i) the VWC of Kazakhstan's agricultural products is between 55.61 and 83.98 billion m³/yr in 2000-2016, where wheat is the largest water consumer and the Kostanay state has the largest VWC; (ii) Kazakhstan is a net exporter of virtual water, most of which flows to neighboring countries such as Russia and Azerbaijan; (iii) uncertainties in crop coefficient (Kc), feed water requirement (FWR), drinking water requirement (DWR) and service water requirement (SWR) can affect the VWC assessment; (iv) the massive export of water-intensive products makes the water resources more severe in Kazakhstan, which further squeezes the local ecological water use. Therefore, reducing the export of virtual water should be the focus of future agricultural policies. The findings are useful for decision makers to optimize Kazakhstan's agricultural structure, mitigate the national water scarcity, and facilitate the regional sustainable development.

Carbon and Water Footprints of Tibet: Spatial Pattern and Trend Analysis

Tibet in China has extremely a fragile natural ecosystem, which is under a great pressure from global changes. The carbon footprint (CF) and water footprint (WF), reflecting the pressures of regional development on the natural environment, represent a lacuna in the field of study in Tibet due to missing data. In this paper, the 2012 multi-regional input–output table of China was employed to quantify the CF and WF of Tibet and the relationship between Tibet and other provinces of China. Spatial pattern and key sectors were also studied to demonstrate the current characters and the future trend of footprints. Tibet’s carbon emission was 4.0 Mt, 32.7% of CF, indicating that Tibet was a net importing region of carbon emission. Tibet received embodied carbon emission by trade from other regions, especially from Hebei, Inner Mongolia and Henan provinces, but played a complex role in virtual water allocation by transferring to most provinces and receiving from some provinces. The CF of Tibet will increase under different scenarios of 2030, but the WF can be restricted to 2.5 Gt in the slow scenario. In the future, imports of virtual resources will benefit the fragile ecosystem of Tibet and moreover, it is vital to restrict the local resource-intensive sectors and improve resource-use efficiency.