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Income group heterogeneity and transboundary food-related water footprints are essential for water resource management. Previous studies have not fully characterized the transboundary food-related water footprints by regional income groups. Taking Guangdong as an example, this study calculates the local and transboundary food-related water footprints by income groups and explores relevant socioeconomic factors during 2007-2017. Results show that the proportion of transboundary food-related water footprints by income groups has increased during 2007-2017. By 2017, nearly half of food-related water footprints of income groups happened in external regions. In particular, the high-income groups of Guangdong transferred large amounts of food-related water footprints to specific northern regions (e.g., Heilongjiang and Jilin). However, socioeconomic changes of these northern regions contributed to the increase of food-related water footprints by income groups. Fortunately, the transitions of food consumption structures of income groups helped to reduce the external food-related water footprints. We also observed that the effects of dietary behavior changes were group heterogeneous. The findings of this study can provide scientific foundations for group-targeted dietary behavior optimization to reduce water footprints, as well as interregional collaboration for sustainable food and water resource management.

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Food system is the main consumer of water resources, and the differences in urban and rural diets pose new challenges to the water sustainability and increase the uncertainty of food security in China. In this study, we quantified the dietary water footprint (DWF) of urban and rural residents at the city scale in four major urban agglomerations in China from 2015 to 2021, identified the key economic and educational factors of urban and rural DWF, and measured the inequality of urban and rural DWF driven by the main influencing factors. We found that there was a 27.17 % increase in urban DWF and a 23.18 % increase in rural DWF between 2015 and 2021. Cereals had the largest water footprint among the 12 food types, accounting for 20.27 % and 31.57 % of urban and rural DWF, respectively. Meanwhile, milk and dairy products contributed the most to the difference between urban and rural DWF, up to 57.89 m3 each year. The main economic factor of DWF was consumption expenditure. The number of primary school students and the number of primary schools are the most important educational factors of urban and rural DWF, respectively. The results show there is an inequality between DWF and major educational factors, with a decreasing trend in DWF inequality over time. This study revealed for the first time the difference between urban and rural DWF at the city scale, and clarified the impact of regional educational inequality on DWF. A greater focus should be placed on the primary education-related factors that influence DWF inequality, in order to better target sustainable DWF strategies for urban and rural residents.

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Quantitatively predicting the impacts of climate change on water demands of various crops is essential for developing measures to ensure food security, sustainable agriculture, and water resources management, especially in arid regions. This study explored the water footprints (WFs) of nine major crops in the middle and downstream areas of Shule River Basin, Northwest China, from 1989 to 2020 using the WF theory and CROPWAT model and predicted the future WFs of these crops under four emission and socio-economic pathway (SSPs-RCPs) scenarios, which provides scientific support for actively responding to the negative impacts of climate change in arid regions. Results indicated: (1) an increasing trend of the overall crop WF, with blue WF accounting for 80.31-99.33% of the total WF in the last 30 years. Owing to differences of planting structure, water-conservation technologies, and other factors, the multi-year average WF per unit area of crops was 0.75 × 104 m3 hm-2 in downstream area, which was higher than that in midstream area (0.57 × 104 m3 hm-2) in the last 30 years; therefore agricultural water use efficiency in the downstream area was lower than that in the midstream area, implying that the midstream area has more efficient agricultural water utilization. (2) an initial increase and then decrease of crop WFs in the study area under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios by the end of the century, reaching their peak in 2030s which was higher than that from 1989 to 2020; with the maximum growth rates in the midstream area ranging from -0.85% in SSP5-8.5 to 5.33% in SSP2-4.5 and 29.74% in SSP5-8.5 to 34.71% in SSP2-4.5 in the downstream area. The local agricultural water demand would continue to increase and water scarcity issues would be more severe in the next 10-20 years, affecting downstream areas more. Under the SSP3-7.0 scenario, crop WF values of the midstream and downstream regions will be 2.63 × 108 m3 and 4.22 × 108 m3 in 2030, respectively, which is significantly higher than those of other scenarios and show a long-term growth trend. The growth rate of the midstream and downstream regions will reach 44.71% and 81.12%, respectively, by the end of this century, so the local agricultural water use would be facing more strain if this scenario materializes in the future. Therefore, the Shule River Basin should encourage development of water-saving irrigation technologies, adjust the planting ratio of high water consuming crops, and identify other measures to improve water resource utilization efficiency to cope with future water resource pressures.

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Urbanization, climate change, and irresponsible resource management exacerbate the global water crisis. The necessity for water resilience, the capacity of systems and communities to adjust and flourish in the face of water shocks and pressures, has been brought to light by these critical issues. Water resilience enables Global Value Chains (GVCs) to survive scarcity, pollution, and flooding, ensuring sustainability and service delivery. Current service excellence models focus on stakeholder satisfaction, punctuality, and reliability over water resilience. This oversight may limit GVC growth and flexibility, reducing sector services. As recommended service excellence models focus on satisfaction, punctuality and reliability among stakeholders but water resilience is not considered. This can create issues for the growth and flexibility of GVCs which could cut back on services sector. This research is examined a complex relationship between service quality and water resilience to improve the GVCs in China regions especially Guangdong Province, Shanghai Municipality, and Beijing Municipality. By using multiple regression, GVCs service quality and water resilience is analyzed in the existence of Service Excellence Model. The study used 15 years (2009-2023) secondary data to measure how water resilience and GVCs services quality affect each other in Chinese regions. The results show that water resilience strategies can strengthen global production networks, optimize resource usage, and enhance service excellence. Chinese GVCs can produce a water-resilient service economy, enlightening service quality and preserving competitiveness in rapidly changing global markets.

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Stormwater management problems have been deteriorated with the high frequency and intensity of precipitation owing to rapid urbanization and climate variability, especially in urban highly built-up area. Nature-based solutions (NBS) have emerged as a powerful measure for rising these challenges due to their ability to mitigate urban waterlogging and increase carbon sequestration. Identifying optimal locations for NBS implementation remains a critical research focus. This study integrates carbon and water footprint accounting into NBS-based planning for sustainable urban development in central Guangzhou, China, to enhance urban flooding mitigation and carbon sequestration. Through carbon-water footprint analysis and weighting, we prioritized NBS planning. To achieve the objectives of increasing sequestered carbon and reducing urban runoff, three types of NBS-green roofs, permeable pavements, and bioretention systems-were optimized for a high-priority town street. The results showed that the implementation of green roof and permeable pavement reduced the surface runoff by 3.58 %, while the biological retention system reduced the runoff gray water by 27 %. Moreover, the application of green roof and biological retention increased the carbon sequestration by 2.57 million kg CO2-eq (life cycle). The findings of this study provide comprehensive insights into optimization of NBS planning based on carbon-water footprint accounting, facilitating to enhance mitigation of urban flooding vulnerability and carbon sequestration.

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Water scarcity is a significant constraint in agricultural ecosystems of arid regions, necessitating sustainable development of agricultural water resources. This study innovatively combines Bayesian theory and Water Footprint (WF) to construct a Bayesian Network (BN). Water quantity and quality data were evaluated comprehensively by WF in agricultural production. This evaluation integrates WF and local water resources to establish a sustainability assessment framework. Selected nodes are incorporated into a BN and continuously updated through structural and parameter learning, resulting in a robust model. Results reveal a nearly threefold increase of WF in the arid regions of Northwest China from 1989 to 2019, averaging 189.95 × 108 m3 annually. The region's agricultural scale is expanding, and economic development is rapid, but the unsustainability of agricultural water use is increasing. Blue WF predominates in this region, with cotton having the highest WF among crops. The BN indicates a 70.1 % probability of unsustainable water use. Sensitivity analysis identifies anthropogenic factors as primary drivers influencing water resource sustainability. Scenario analysis underscores the need to reduce WF production and increase agricultural water supply for sustainable development in arid regions. Proposed strategies include improving irrigation methods, implementing integrated water-fertilizer management, and selecting drought-resistant, economically viable crops to optimize crop planting structures and enhance water use efficiency in current agricultural practices in arid regions. This study not only offers insights into water management in arid regions but also provides practical guidance for similar agricultural contexts. The BN model serves as a flexible tool for informed decision-making in dynamic environments.

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Considering the importance of sustainable nutrition, it is important that hospitals' meal menus are planned to ensure the lowest possible environmental footprint. In this study, we aimed to evaluate the environmental effects of hospital menus and the changes that may occur when these menus are planned according to the Turkey Dietary Guidelines and Mediterranean diet recommendations. In this context, first, the yearly environmental footprints of the standard meal menus of the state university hospitals in Turkey (n = 42), including water footprint (WF) and greenhouse gas emission (GHGE) values, were determined. Second, changes in the environmental footprint as a result of arranging the standard meal menus of state university hospitals according to the Turkey Dietary Guidelines and Mediterranean nutritional models were evaluated. It was determined that the average WF and GHGE values of hospital menus were 137,280 ± 18537.2 L/month and 140.0 ± 18.4 kg CO2-eq/month, respectively. Adjusting state university hospitals' standard meal menus according to Turkey Dietary Guidelines and Mediterranean nutritional models reduced WF by 24.8% to 103206.7 L/month and 37.8% to 85420.5 L/month, and GHGEs by 31.7% to 95.5 kg CO2-eq/month and 49% to 71.3 kg CO2-eq/month, respectively. In addition, it was determined that hospital meal menus planned according to the Turkey Dietary Guidelines and the Mediterranean nutritional model contained lower saturated fat and cholesterol and higher dietary fiber. In conclusion, planning hospital menus according to the Turkey Dietary Guidelines and Mediterranean nutritional recommendations can reduce the environmental footprint of hospital food services.

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In the years 2021-2022 and 2022-2023, an experiment was carried out at the IFS Unit, College of Agriculture, PJTSAU, Rajendranagar in order to determine the best one-acre integrated farming system model for Telangana's small and marginal farmers. Seven farm models among which six models were developed by combining the various components i.e., cropping systems, fruit cropfodder crops and livestock components, in different proportions, and compared with rice-groundnut system which is a major farming approach in Telangana using randomized block design. The seven models were as follows: M1: Rice-Groundnut; M2: Rice-Groundnut, Pigeonpea + Sweetcorn (1:3)-Bajra, Bt cotton + Greengram (1:2)-Maize; M3: Rice-Groundnut, Pigeonpea + Sweetcorn (1:3)-Bajra, Pigeonpea + Maize (1:3)-Sunhemp; Napier grass, Sheep (5 + 1); M4: Rice-Groundnut, Pigeonpea + Sweetcorn (1:3)-Bajra, Bt cotton + Greengram (1:2)-Maize, Pigeonpea + Maize (1:3)-Sunhemp, Poultry unit; M5: Guava, Hedge Lucerne, Napier grass, Bt cotton + Greengram (1:2)-Maize, Sheep (5 + 1); M6: Guava, Bt cotton + Greengram (1:2)-Maize, Rice-Groundnut, Poultry; M7: Rice-Groundnut, Pigeonpea + Sweetcorn (1:3)-Bajra, Pigeonpea + Maize (1:3)-Sunhemp; Napier grass, Hedge lucerne, Poultry (100), Sheep (5 + 1). Based on a 2-year average, the Model M7 system produced 9980 Rice Grain Equivalent Yield(RGEY)kg of output per acre, with gross and net returns of ₹210,439 and ₹124,953 respectively, and recovered a B:C ratio of 2.46. It has recorded highest sustainable yield index (SYI) of 0.673 and value index of 0.772 with the lowest water footprint of 259.0 L/kg. This study reveals that adopting an integrated farming system is the optimal approach for effectively combining productive, financially rewarding, and diversified enterprises within a single acre of land.d. This system should be recommended for maximum benefits to smallto small and marginal farmers in Telangana's southern hills and plateau.

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When water supply restrictions increasingly escalate to water supply risks, developing strategies to minimize the water footprint of wet cooling systems becomes crucial. This study compares two water engineering approaches to minimize the water footprint of a recirculating evaporative cooling tower (CT): (1) reusing cooling tower blowdown and (2) producing demineralized water to increase the cycles of concentration (CoC) of the CT. Our techno-economic analysis across various scenarios and CT settings reveals that reusing blowdown (option 1) is the most feasible approach for an industrial cooling system currently operating at CoCs of > 3, discharging blowdown with a conductivity of 2 mS/cm and a total organic carbon (TOC) concentration of approximately 20 mg/L. Compared to enhanced make up treatment, blowdown reuse allows higher water savings (13 %) and involves lower implementation and operation costs. Pilot scale trials validated the feasibility of both approaches. Blowdown and enhanced make up treatment included biologically activated carbon filtration, ultrafiltration and reverse osmosis, producing high-quality permeate, suitable for (re)use as CT make up or within other processes. The blowdown treatment reached a product quality of 80 µS/cm conductivity and 70 µg/L TOC, make up treatment 20 µS/cm in conductivity and 60 µg/L TOC, respectively. The study's findings underscore the viability of blowdown reuse as a cost-effective and efficient strategy to minimize the water footprint of cooling systems under increasing water scarcity conditions.

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Recent climate warming has significantly affected the sensitivity of Gross Primary Productivity (GPP) to precipitation within China's agricultural ecosystems. Nonetheless, the spatial and temporal nonlinear evolution patterns of GPP-precipitation sensitivity under climate change, as well as the underlying drivers and long-term trends of this sensitivity, are not well understood. This study employs correlation analysis to quantify the sensitivity between GPP and precipitation in China's agricultural ecosystems, and utilizes nonlinear detection algorithms to examine the long-term changes in this sensitivity. Advanced machine learning techniques and frameworks are subsequently applied to analyze the driving factors of GPP-precipitation sensitivity in China's agricultural ecosystems. The findings reveal that approximately 49.00 % of the analyzed pixels exhibit a significant positive correlation between GPP and precipitation. Nonlinear change analysis indicates spatial heterogeneity in GPP-precipitation sensitivity across China's agricultural ecosystems, with patterns showing initial increases followed by decreases accounting for 25.12 %, and patterns of initial decreases followed by increases at 13.27 %. Machine learning analysis identifies temperature, soil moisture, and crop water footprint as the primary factors influencing GPP-precipitation sensitivity in agricultural ecosystems. This study is the first to introduce crop water footprint as a significant factor in the analysis of GPP-precipitation sensitivity. It not only offers new insights into the temporal nonlinear changes and driving factors of GPP-precipitation sensitivity but also underscores the importance of enhancing agricultural water efficiency to maintain agricultural ecosystem health and ensure food security under climate change.

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Background: Food plays a dual role in promoting human health and environmental sustainability. Yet, current food systems jeopardize both. Food waste poses a major global challenge due to its significant economic, social, and environmental impacts. Healthcare facilities generate the largest amounts of food waste compared to other forms of catering provision. Food waste correlates with environmental unsustainability and diminished patient satisfaction, compounding the prevalent challenge of hospital malnutrition and contributing to suboptimal patient outcomes. Materials and methods: In a three-year interventional study (2020-2022) at a psychiatric tertiary care center, we assessed and mitigated food waste using evidence-based measures. We conducted systematic food wastage audits over three years (2020-2022) in May and June, each lasting four weeks. Costs were analyzed comprehensively, covering food, staff, infrastructure, and disposal. Environmental impact was assessed using Umweltbelastungspunkte (UBP) and CO2e/kg emissions, alongside water usage (H2O - l/kg). Results: Economic losses due to food wastage were substantial, primarily from untouched plates and partially consumed dinners, prompting meal planning adjustments. Despite a >3% increase in meals served, both food waste mass and costs decreased by nearly 6%. Environmental impact indicators showed a reduction >20%. Vegetables, salad, and fruits constituted a significant portion of waste. Overproduction minimally contributed to waste, validating portion control efficacy. Conclusion: Our study highlights significant economic and environmental losses due to hospital food waste, emphasizing the importance of resource efficiency. The strategies outlined offer promising avenues for enhanced efficiency. The decrease in food waste observed over the three-year period underscores the potential for improvement.

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Water scarcity, land pollution, and global warming are serious challenges and crises facing the development of sustainable or green agriculture and need to be addressed using efficient and environmentally friendly management strategies. This paper proposed an integrated framework appropriate for agricultural green total factor productivity (AGTFP) assessment coupled with microscopic and mesoscopic perspectives under water-energy-food (WEF) nexus, which generated scientific and reasonable strategies for green and low-carbon agriculture from internal core factors and peripheral environmental impacts to improve green agricultural production sustainability. Taking the Lianshui irrigation district (LID) with three sub-areas as the object, internal core factors were explored by partial least squares regression (PLSR) and the external impact path through partial least squares structural equation modeling (PLS-SEM). Results indicated that AGTFP in LID was the smallest (0.818) compared to the three sub-areas and was in a fluctuating state. Meanwhile, AGTFP which was calculated considering undesirable outputs, was closer to tangible productivity. Resource endowments and technical facilities will promote agricultural production, desirable outputs will stimulate green production, and undesirable outputs can inhibit green production. The external influence pathway was shown to be primary environment - > secondary environment - > economic aspects - > social aspects - > AGTFP. The innovative perspectives presented in this study can facilitate preferable decisions and avoid unintended consequences for human-natural systems.

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Climate change has exacerbated the contradiction between water scarcity and sustainable agricultural development. Assessing the crop water use efficiency and its influencing factors could provide a decision-making reference to realize Sustainable Development Goal 2. By analyzing the temporal and spatial evolution characteristics of the crop water footprint, the blue water footprint, green water footprint, and grey water footprint were introduced into the super efficiency slack-based measure model to evaluate the crop water use efficiency in basins. The influence of the driving factors was examined by using the geographic detector model. The situation in the provinces along the Yellow River Basin from 2005 to 2020 was used as a verification case. The results indicated that (1) during the study period, crop water use in the basin was mainly based on the blue water footprint, accounting for approximately 55% of the total water footprint, the grey water footprint, accounting for approximately 30% of the total water footprint, and the green water footprint, accounting for the lowest proportion, at approximately 15%. (2) The crop water use efficiency exhibited a spatial distribution pattern of high values in the east and low values in the west, with obvious upstream provinces disposable income of rural residents (0.71) > population urbanization rate (0.65) > degree of agricultural mechanization (0.63) > agricultural disaster rate (0.61). Furthermore, the interaction effects between the driving factors were greater than the effects of the single factors. The study provides an important reference for understanding the changes, driving mechanisms, and impacts of crop water use efficiency in basin areas. It promotes green agricultural transformation and development to address climate change and alleviate the pressure on water resources.

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The rapidly growing demand for food in human societies has led to the extensive use of fertilizers, significantly contributing to water pollution. Grey water footprints (GWF) serve as a crucial method for measuring Non-point Source (NPS) pollution, particularly in agriculture. Traditional assessments of agricultural GWF neglect biologically fixed nitrogen and the use of organic fertilizers. This research proposed a modified method to assess the GWF of Chinese agriculture from 2000 to 2020, considering the impact of Nitrogen fixation in crops and the use of organic fertilizer. We also analyzed the determinants of Agricultural Nitrogen Fixation Intensity (ANFI) using the Logarithmic Mean Divisia Index (LMDI) method to better understand factors influencing agricultural GWF. Our findings include (1) Grain cereals (e.g., maize, rice, and wheat) significantly contribute to nitrogen fixation in crop organs, accounting for 87.7%, whereas the other six economic crops contribute the rest of 12.3%. Human wastes account for Nitrogen emissions for 1.40%, and emissions by livestock product, red meat contributes 16.26%, while white meat, eggs, and milk collectively contribute 82.34%. (2) Across China, there is an overestimation of GWF by 22.4 hundred million m3 per year, about 5.13% of the total GWF measured by traditional methods. It appears that the overestimation of GWF in plain regions with more arable land tends to be somewhat more pronounced compared to plateau and coastal municipalities. Biotechnological advancements in the capacity of nitrogen fixation for key crops (e.g., maize, wheat, rice) can alleviate agricultural water pollution. The modified methodology provides a robust scientific basis for a more precise application of GWF assessments, highlighting the substantial overestimation by traditional methods in China.

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This study investigated the feasibility of integrating hydroponic barley forage (HBF) production into dairy ruminant production, focusing on its effect on milk yield and components, energy and water footprints, and economic implications. Maize silage (MS) was used as a benchmark for comparison. The research was conducted on a water buffalo dairy farm equipped with a fully automated hydroponic system producing approximately 6,000 kg/d of HBF as fed (up 1,000 kg/d on DM basis). Thirty-three lactating water buffaloes were assigned to 3 dietary treatments based on the level of MS or HBF in the diet: D0 (100% MS), D50 (50% MS and 50% HBF), and D100 (100% HBF). The feeding trial lasted 5 weeks plus a 2-week adaptation period during which each cow underwent a weighing, BCS scoring, recording of milk yield and components, including somatic cell count and coagulation characteristics. Based on the data obtained from the in vivo study, the water and energy footprints for the production of MS and HBF and buffalo milk, as well as income over feed cost, were evaluated. Complete replacement of MS with HBF resulted in a slight increase in milk yield without significant impact on milk component. The resource footprint analysis showed potential benefits associated with HBF in terms of water consumption. However, the energy footprint assessment showed that the energy ratio of HBF was less than 1 (0.88) compared with 11.89 for MS. This affected the energy efficiency of milk yield in the 3 diets, with the D50 diet showing poorer performance due to similar milk yield compared with D0, but higher energy costs due to the inclusion of HBF. The production cost of HBF was about 4 times higher than that of farm-produced MS, making feed costs for milk yield more expensive. Nevertheless, HBF can potentially improve income over feed costs if it increases milk yield enough to offset its higher production costs. Overall, the results suggest that the current practice of using HBF to replace high quality feedstuffs as concentrates is likely to result in energy and economic losses.

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Green hydrogen generated via water electrolysis using photovoltaics or wind has begun to scale up in the process of achieving the global net-zero goal, but there is a lack of research on its impact on the scarcity of water resources and water saving potential. A water resources impact assessment framework for green hydrogen scale-up development is established, integrating the product water footprint and regional water footprint scarcity impacts and advancing the study of the water resources impacts on green hydrogen from water conservation as well as from a sustainable context. The research framework specifies the cradle-to-gate life cycle water consumption of hydrogen production, establishes the water scarcity footprint based on the available water remaining (AWARE) model, quantifies the water saving intensity and potential of the green hydrogen alternative to traditional hydrogen production, and proposes quantitative indicators of the water saving benefit. Taking the regions of 31 provinces in China as a case study, the wind-to­hydrogen scenario and the solar-to­hydrogen scenario will generate approximately 68.86×108 m3 and 126.10×108 m3 water scarcity footprints, respectively. Under the coal-to­hydrogen baseline scenario, approximately 1.68×108 m3 and - 0.57×108 m3 of water saving potential will be generated. In addition, the water saving intensity decreases from west to east. According to the adjusted quantitative indicators of water saving benefits, the wind-to­hydrogen scenario in China can reach 40.22×108 m3eq and the water saving benefit is more obvious in northern regions such as Hebei, Ningxia and Inner Mongolia. The methodological framework can be applied to other countries or regions to assess the sustainable impacts of green hydrogen production on water resources in a given region.

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There are studies on the effect of general nutrition education on diet quality and anthropometric measurements, while studies showing the effectiveness of sustainable nutrition education, which also addresses the effect of food on the environment, are quite limited. This study aimed to investigate the effects of sustainable nutrition education on diet quality, anthropometric measurements, and the carbon footprint (CFP) and water footprint (WFP) of diet. A total of 160 university students received 1 h of sustainable nutrition education for 6 weeks. Before, at the end of, and 2 months after the courses, 24 h food consumption records were taken to assess diet quality and CFP and WFP values of diet, and Mediterranean diet (MedDiet) and Healthy Eating Index (HEI)-2020 scores were evaluated. The results of the study showed that sustainable nutrition education increased MedDiet score by 1.86 points and HEI-2020 score by 7.38 points. This education program also decreased body weight, body mass index (BMI), fat mass, and neck circumference. Sustainability education has a positive impact on calcium, potassium, and magnesium intakes, a negative impact on vitamin B12 and zinc intakes, and no effect on total protein intake. Education resulted in a 22% reduction in CFP and a 10% reduction in WFP.

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Northern Africa has become the first region in the world to exhaust its water resources, with a 40 % decrease in per capita water availability south of the Sahara over the past decade. While adjusting production structures and consumption can regulate the supply-demand dynamics of water resources, the extent of the impact of virtual water-induced pressure on both the regional and national levels in Africa remains largely understudied. Applying the standard Penman formula, this research calculates the water footprint of eight cereal crops in 54 African countries from 1990 to 2021. By integrating corresponding data on cereal trade, the study analyzes changes in virtual water stress. The findings indicate a decline in the per-unit production and consumption water footprints for African cereals. However, the continuous expansion of cultivation areas contributes to a rising water stress. In comparison to 1990, the water stress for soybeans, sorghum, rice, maize, and cassava increased by 149.72 %, 146.88 %, 133.89 %, 123.30 %, and 90.8 %, respectively, in 2021. Only barley showed a reduction in water stress by 23.22 %. The study underscores the growing interconnectedness of virtual water trade (VWT) among African nations from 1990 to 2021, leading to a more balanced trade distribution. VWT has reduced water stress by 7.65 %, 2.08 %, and 1.8 % in Western, Central, and Northern Africa, respectively, while increasing pressure in Southern and Eastern Africa by 10.51 % and 1.01 %. The flow of virtual water in Africa is most influenced by spatial proximity, primarily occurring between adjacent countries or regions. Forecasts for water stress under the five scenarios of SSPs-RCP8.5 have been conducted, revealing a continuous increase in water stress across Africa. Furthermore, analysis of the SSP2-RCP8.5 scenario indicates that by 2030 and 2040, African cereal crops are projected to face virtual water resource stress increases of 7 % and 18.76 %, respectively, compared to 2020 levels. During the same period, Sierra Leone is anticipated to experience a growth rate in virtual water stress of approximately 1903.38 %. Consequently, altering crop cultivation structures and enhancing VWT are poised to alleviate water resource pressure, promoting the scientific management of agricultural water resources in Africa.

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Carbon offset frameworks like the UN Clean Development Mechanism (CDM) have largely overlooked interventions involving food, health, and care systems, including breastfeeding. The innovative Green Feeding Climate Action Tool (GFT) assesses the environmental impact of commercial milk formula (CMF) use, and advocates for breastfeeding support interventions as legitimate carbon offsets. This paper provides an overview of the GFT's development, key features, and potential uses. The offline and online GFT were developed using the DMADV methodology (Define, Measure, Analyze, Design, Verify). The GFT reveals that the production and use of CMF by infants under 6 months results in annual global greenhouse gas (GHG) emissions of between 5.9 and 7.5 billion kg CO2 eq. and consumes 2,562.5 billion liters of water. As a national example, in India, one of the world's most populous countries, CMF consumption requires 250.6 billion liters of water and results in GHG emissions ranging from 579 to 737 million kg CO2 eq. annually, despite the country's high breastfeeding prevalence among infants under 6 months. The GFT mainly draws on data for low- and middle-income countries (LMICs), as many high-income countries (HICs) do not collect suitable data for such calculations. Despite poor official data on breastfeeding practices in HICs, GFT users can input their own data from smaller-scale surveys or their best estimates. The GFT also offers the capability to estimate and compare baseline with counterfactual scenarios, such as for interventions or policy changes that improve breastfeeding practices. In conclusion, the GFT is an important innovation to quantify CMF's environmental impact and highlight the significance of breastfeeding for planetary as well as human health. Women's contributions to environmental preservation through breastfeeding should be recognized, and breastfeeding interventions and policies should be funded as legitimate carbon offsets. The GFT quantifies CMF's carbon and water footprints and facilitates financing breastfeeding support as a carbon offset initiative under CDM funding facilities.

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Examining the pollution rates generated by horticultural crops and discerning their impact on water consumption are pivotal considerations for fostering sustainable production of these valuable crops. This study focuses on investigating the environmental consequences and water footprint associated with cultivating diverse horticultural crops in northern Iran. The research employs the life cycle assessment method to gauge environmental impacts by using IMPACT 2002+ and the Water Scarcity Indicator (WSI) to assess water footprints. Notably, the results indicate that walnuts exhibit the highest environmental index, surpassing other crops by sevenfold, and the greatest WSI at 2652.78 m3/ton. Nitrogen fertilizer and on-farm emissions emerged as the primary contributors to pollution among consumed inputs. The assessment underscores human health as a critical concern in the environmental impact of horticultural crop production, likely attributed to elevated chemical input consumption and associated emissions. The findings emphasize the substantial challenges faced by orchard management in Mazandaran province, the primary horticultural crop producer in Iran, grappling with chemical usage and water scarcity.

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