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National water footprint accounts: The green, blue and grey water footprint of production and consumption
Abstract
This study quantifies and maps the water footprints of nations from both a production and consumption perspective and estimates international virtual water flows and national and global water savings as a result of trade. The entire estimate includes a breakdown of water footprints, virtual water flows and water savings into their green, blue and grey components.
... Water use in the food industry varies greatly depending on the specific sector, with some industries being much more water-intensive than others [66]. For example, the meatprocessing industry requires significantly more water than grain or vegetable production. ...
... For instance, shifting toward dietary patterns aligned with recommended guidelines will potentially decrease China's water footprint by 15% by the year 2050 [80]. Hoekstra, Mekonnen et al. [66,81] highlighted that the adoption of plant-based diets as a substitute for meat-centered options could decrease the total water footprint by 36-40%. Additionally, the literature [82] indicated that vegetarian diets with modest quantities of low-trophic-level animals (e.g., forage fish and insects) exhibit a lower WF than strictly vegan solutions. ...
This review paper examines the critical intersection of energy consumption and environmental impacts within the global food system, emphasizing the substantial footprint (including land usage, costs, food loss and waste, and carbon and water footprints) associated with current practices. The study delineates the high energy demands and ecological burdens of food production, trade, and consumption through a comprehensive bibliographic analysis of high-impact research papers, authoritative reports, and databases. The paper systematically analyzes and synthesizes data to characterize the food industry’s current energy use patterns and environmental impacts. The results underscore a pressing need for strategic interventions to enhance food system efficiency and reduce the footprint. In light of the projected population growth and increasing food demand, the study advocates for a paradigm shift towards more sustainable and resilient food production practices, adopting energy-efficient technologies, promoting sustainable dietary habits, and strengthening global cooperation among stakeholders to achieve the Sustainable Development Goals. Investigations have revealed that the food system is highly energy-intensive, accounting for approximately 30% of total energy consumption (200 EJ per year). The sector remains heavily reliant on fossil fuels. Associated greenhouse gas (GHG) emissions, which constitute 26% of all anthropogenic emissions, have shown a linear growth trend, reaching 16.6 GtCO2eq in 2015 and projected to approach 18.6 GtCO2eq in the coming years. Notably, 6% of these emissions result from food never consumed. While the water footprint has slightly decreased recently, its demand is expected to increase by 20% to 30%, potentially reaching between 5500 and 6000 km3 annually by 2050. Energy efficiency interventions are estimated to save up to 20%, with a favorable payback period, as evidenced by several practical implementations.
... Approximately one-third of the total water footprint of agriculture in the world is generated by the production of animal products. It is reported that the water footprint of any animal product is more than the water footprint of plant products with equivalent nutritional value [13]. ...
It is important that mass catering services in hospitals adhere to health quality standards and are carried out sustainably and reliably, aligning with the planning of patients’ nutritional treatments in clinical services. This study aims to analyze the carbon and water footprints of menus used in hospital catering services. The research was conducted across all four seasons, with 31-day months included to standardize the number of days in the selection of seasonal menus. Among the menus, one of the most frequently prepared meals using traditional production methods was selected separately for lunch and dinner. In the study, carbon and water footprint calculations were performed for pre-selected meals used in hospital catering services. During spring, summer, autumn, and winter, the carbon footprint levels of the first meal group were significantly higher than those of the second and third meal groups (p
... We considered crop farming, husbandry and other sectors separately. Blue-water consumption coefficients were adopted from ref. 72, and 2017 crop production data of 161 crops from the Food and Agriculture Organization were used to calculate blue-water consumption in crop farming. The results were allocated across the eight agricultural sectors defined in GTAP. ...
The disparity in environmental impacts across different countries has been widely acknowledged1,2. However, ascertaining the specific responsibility within the complex interactions of economies and consumption groups remains a challenging endeavour3–5. Here, using an expenditure database that includes up to 201 consumption groups across 168 countries, we investigate the distribution of 6 environmental footprint indicators and assess the impact of specific consumption expenditures on planetary boundary transgressions. We show that 31–67% and 51–91% of the planetary boundary breaching responsibility could be attributed to the global top 10% and top 20% of consumers, respectively, from both developed and developing countries. By following an effective mitigation pathway, the global top 20% of consumers could adopt the consumption levels and patterns that have the lowest environmental impacts within their quintile, yielding a reduction of 25–53% in environmental pressure. In this scenario, actions focused solely on the food and services sectors would reduce environmental pressure enough to bring land-system change and biosphere integrity back within their respective planetary boundaries. Our study highlights the critical need to focus on high-expenditure consumers for effectively addressing planetary boundary transgressions.
... 1. Conduct bibliographic research for footprint (I/O) data for each planetary boundary and for each country [68][69][70][71][72][73] (see Table SI1). ...
Current aviation roadmaps predominantly rely on the replacement of fossil kerosene by alternative jet fuels to mitigate climate change, but the systemic impact of such energy transitions on other planetary boundaries remains unexplored. Here we fill this gap by integrating prospective life-cycle inventories within absolute environmental sustainability assessment. We find that the core climate change and biosphere integrity planetary boundaries are systematically transgressed, making these roadmaps unsustainable toward 2050. Lower energy demand brings aviation closer to its share of safe operating space, but air traffic needs to degrow by 8.6% yr ⁻¹ for additional planetary boundaries to be respected. Associated demand in energy, land, freshwater and CO 2 capture is significant, with clear implication on the feasibility of these scenarios. Our results therefore show that, in order to achieve absolute sustainability, a rethinking of aviation governance is needed toward a systemic approach combining energy transition and demand-side measures.
No study has been found examining the contribution of gray water footprint input per unit yield to reducing blue and green water footprint output in silage maize irrigated with different levels of wastewater under different tillage practices. Therefore, this 2-year silage maize field study examined the effect of three different levels of recycled wastewater (100, 67, and 33% of irrigation need in W100, W67, and W33) and 100% irrigation with freshwater on water footprint under conventional and zero tillage. Under zero tillage, W100 had the lowest blue, green, and total water footprint per unit yield of 2.8, 6.1, and 47 m3 ton−1 for fresh biomass, respectively, and 9.2, 20.1, and 155.3 m3 ton−1 for dry biomass. Among the wastewater treatments, the W33 resulted in the highest water footprints per unit yield under conventional tillage. Blue, green, gray, and total water footprints per unit fresh yield under zero tillage were 9.8, 5.9, 13.1, and 10.3% lower than conventional tillage, while the values for dry biomass were 15, 14.3, 18.6, and 16.6% lower. In conclusion, W100 under zero tillage can be an effective way to protect freshwater resources by reducing blue, green, and total water footprint outputs with less gray water footprint input per unit yield.
The Eastern Nile Basin (ENB) countries of Egypt, Sudan, South Sudan, and Ethiopia are subject to pronounced water, energy, and food (WEF) insecurity. There is a need to manage the WEF nexus to meet rapidly increasing demands, but this is extremely challenging due to resource scarcity and climate change. If countries that rely on shared transboundary water resources have contradictory WEF plans, that could diminish the expected outcomes, both nationally and regionally. Egypt as the most downstream Nile country is concerned about ongoing and future developments upstream, which could exacerbate Egypt's water scarcity and affect its ability to meet its WEF objectives. In this context, we introduce a multi‐model WEF framework that simulates the ENB water resources, food production, and hydropower generation systems. The models were calibrated and validated for the period 1983–2016, then utilized to project a wide range of future development plans, up to 2050, using four performance measures to evaluate the WEF nexus. A thematic pathway for regional development that shows high potential for mutual benefits is identified. However, the WEF planning outcomes for the region are sensitive to climate change, but, if social drivers could be managed (e.g., by lowering population growth rates) despite the difficulties involved, climate change impacts on WEF security could be less severe.
Reducing blue and total water footprint outputs in irrigated agriculture with greywater footprint input from irrigation with recycled wastewater is an issue that needs to be investigated in protecting freshwater resources by increasing water availability. Therefore, the effect of three different irrigation levels of recycled wastewater and freshwater in the subsurface irrigation (SSDI), surface drip irrigation (SDI), and furrow irrigation (FI) methods on the blue, green, grey, and total water footprints per unit yield of silage maize, which is widely produced worldwide and has high water consumption, was investigated with a 2-year field study. The blue and total water footprints per unit fresh and dry biomass yields in the SSDI were 1.20–1.23-fold lower than that in the SDI and 1.69–1.76-fold lower than that in the FI. Full wastewater irrigation provided the lowest blue, green, and total water footprints per unit yield across all methods. Full wastewater irrigation under SSDI provided the lowest total water footprint per unit fresh biomass yield, similar to the 33% deficit irrigation practice with wastewater. It was concluded that full irrigation with recycled wastewater as a greywater resource under SSDI may be the most suitable application for the sustainable management of scarce blue water resources.
The aim of this research is to develop and compare single, hybrid, and stacking ensemble machine learning models under spatial and temporal climate variations in the Nile Delta regarding the estimation of the blue and green water footprint (BWFP and GWFP) for wheat. Thus, four single machine learning models (XGB, RF, LASSO, and CatBoost) and eight hybrid machine learning models (XGB-RF, XGB-LASSO, XGB-CatBoost, RF-LASSO, CatBoost-LASSO, CatBoost-RF, XGB-RF-LASSO, and XGB-CatBoost-LASSO) were used, along with stacking ensembles, with five scenarios including climate and crop parameters and remote sensing-based indices. The highest R² value for predicting wheat BWFP was achieved with XGB-LASSO under scenario 4 at 100%, while the minimum was 0.16 with LASSO under scenario 3 (remote sensing indices). To predict wheat GWFP, the highest R² value of 100% was achieved with RF-LASSO across scenario 1 (all parameters), scenario 2 (climate parameters), scenario 4 (Peeff, Tmax, Tmin, and SA), and scenario 5 (Peeff and Tmax). The lowest value was recorded with LASSO and scenario 3. The use of individual and hybrid machine learning models showed high efficiency in predicting the blue and green water footprint of wheat, with high ratings according to statistical performance standards. However, the hybrid programs, whether binary or triple, outperformed both the single models and stacking ensemble.
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