Water Footprint Research Articles

Optimal 4E design and innovative R-curve approach for a gas-solar- biological waste polygeneration system for power, freshwater, and methanol production

BackgroundCogeneration power plants traditionally rely on fossil fuels to produce stable power and heat. However, increasing energy demand and population growth have intensified the emission of biological pollutants due to fossil fuel use. The Global Alliance on Health and Pollution advocates for integrating renewable energy sources to mitigate these issues. ObjectivesThis study aims to evaluate the integration of a solar-biomass polygeneration system with a hybrid solar-waste-fossil fuel cogeneration system. The goal is to analyze the system from technical, economic, and environmental perspectives, focusing on optimizing energy demand and minimizing environmental impact. MethodsTo assess energy demand and supply, the R-curve methodology was applied to the hybrid cogeneration system, with a specific focus on solar and biomass renewable energies. Various scenarios were analyzed, including total annual costs, pollutant emissions, water footprint, and overall environmental impact based on life cycle assessment. The study examined and compared the performance of three types of biomass waste (Municipal solid waste, mixed paper waste, and date palm waste). Multi-objective optimization was performed using artificial intelligence and machine learning techniques, employing four meta-heuristic algorithms. The conditions generated by each algorithm were analyzed and compared. ResultsMunicipal solid waste, being the most readily available fuel, provided the most favorable economic conditions for the system. Environmentally, municipal solid waste ranked in the middle compared to other fuels. Among the optimization algorithms, the Salps swarm algorithm proved to be the most efficient in terms of calculation time and system efficiency improvements. The optimization improved net power generation by 5.25 %, overall energy efficiency by 16.27 %, total cost rate by 10.19 %, and total environmental impact rate by 14.02 %. ConclusionThe integrated system's performance was analyzed across different climatic change throughout the year. The multi-objective Salps swarm algorithm optimization demonstrated significant benefits in enhancing system efficiency and reducing costs and environmental impacts.

277 Estimating the potential effect of Mycoplasma hyopneumoniae infection on swine sustainability

Abstract Mycoplasma hyopneumoniae is the primary causative agent of enzootic pneumonia, one of the most common bacterial pathogens affecting pigs and the main contributor to respiratory comorbidities. Infection with M. hyopneumoniae, commonly observed in growing pigs, results in decreased feed intake and an increase in the number of days to reach market weight. Based on extended days to market, pigs infected with M. hyopneumoniae will have a greater life cycle carbon emissions and water usage than that of non-infected pigs. However, the magnitude of additional carbon footprint and water use in pigs infected with M. hyopneumoniae has never been calculated. Therefore, the objective of this study was to estimate the potential variation in carbon emissions and water footprint generated by M. hyopneumoniae infected pigs. This study was conducted using data from previous publications on M. hyopneumoniae infected pigs in experimental and commercial conditions. The carbon footprint and water usage of pork production was obtained from the literature and was used as a baseline (3,470 kg of CO2 eq and 1,678 m3 water eq; both per 1,000 kg of pork carcass weight). The change in average daily gain was estimated and additional days on feed to reach market weight were used to calculate potential carbon and water impact for pigs infected with M. hyopneumoniae. The estimated carbon emissions and water usage of M. hyopneumoniae infected pigs increased in a range of 84.69 to 142.93 kg of CO2 eq/1,000 kg of pork carcass weight and 40.95 to 69.12 m3 eq/1,000 kg of pork carcass weight respectively, compared with the carbon emissions of non-infected pigs (Table 1). Results of this study showed an increased carbon footprint for M. hyopneumoniae infected pigs by 2 to 4% and water usage increased by 2.5 to 4.1% suggesting that the sustainability of pork production was negatively affected by this bacterial infection. Previous literature on the impact of controlling vaccine-preventable diseases has shown similar results for other swine respiratory pathogens. In addition, these data only included M. hyopneumoniae infected pigs, thus the effect of respiratory co-infections was not estimated and the impact on sustainability metrics may be greater than currently calculated. The application of sustainable practices in animal production, including disease prevention, is key to ensuring a secure food supply for future generations. The carbon and water footprints of swine production are measurements of sustainability, with average daily gain being an important factor.

459 A new approach to measuring dry matter intake, from drylot to pasture: Activities of the alliance for regenerative livestock

Abstract The current state of feed intake measurement for cattle in confinement relies on expensive monitoring systems. There is no effective method for measuring feed intake in grazing animals. To address these limitations, our research aims to tap into the potential of passively collected data, such as data from the Internet of Things (IoT), to address practical challenges in animal agriculture. This includes improving livestock management, optimizing resource allocation, and reducing ecological footprints. The benefits of our research extend beyond improved livestock management to include reducing ecological footprints, such as water, carbon, and environmental footprints. Grazing livestock have a crucial role in nutrient cycling in grasslands and advancing more sustainable livestock production systems. This requires innovation of research methods for quantifying intakes of animals housed in a variety of systems including confinement facilities that lack expensive feed intake systems and for grazing animals. Currently, the industry standard for determining feed intake are equations published in the Nutrient Requirements of Beef Cattle (NASEM, 2016). Our recent efforts using machine learning approaches (Blake et al., 2023) dramatically outperforms the equations. Using the same dataset, the NASEM (2016) approach overestimates intake by 34%. We have developed a predictive algorithm utilizing data collected from animals in confinement where individual feed intake (ground truth) is known. We have developed machine learning models such as Repeated Measures Random Forests (RMRF) and Extreme Gradient Boosting (XGB) to better predict feed intake in confined cattle. We have also used these predictive algorithms to determine feed intake of grazing animals and animals in confinement without feed intake systems and validated the predictive value of the approach.

Strategic incentives and natural capital accounting for sustainable supply chain management: Measuring reputational impacts and consumers’ perceptions of the use of water through behavioural experimental studies

Within a sustainable supply chain management approach, this study investigates strategic issues that can either favour or impede the implementation of natural capital accounting. Among other things, the originality of such consists of the joint consideration of sustainability, operational, and reputational issues, forging the link between measuring the use of natural resources and preserving companies' intangible capital. More specifically, through two scenario-based behavioural experiments with a total sample of 252 consumers in the UK, we analyse how information regarding the use of water (i.e., water footprint) affects firms' reputation (i.e., trust, attitude towards the firm, word-of-mouth, brand avoidance). We also investigate consumers' perceptions when companies seek to (1) increase the transparency of their consumption of natural capital (i.e., a conceptual proxy for the adoption of natural capital accounting) and (2) rationalize this consumption (i.e., a goal aligned with the objectives of natural capital accounting). The method employed is adequate as it allows the detection and measurement of respondents' perceptions of specific issues presented in the different scenarios. The choice of the UK as the setting reflects the importance of the country in the fashion industry, as it has a solid consumer base and is home to several international fashion brands. The supply chain management scope refers to the link between water consumption (which often takes place in the production of raw materials (e.g., cotton) and in transformation processes (e.g., fabric dyeing, tanning) by suppliers), fashion brands' reputation, and consumers' perceptions, with the joint consideration of these four phases sustaining the delimitation. Building on the premises of the resource-based view and signalling theory, the study is contextualized in the fashion industry as its current production levels require a significant consumption of natural resources, particularly water. Results show that, while the publication of the water footprint may damage companies’ reputations, initiatives aimed at increasing transparency and reducing environmental impact can reverse these losses to a large extent. In this sense, the study advances the idea that, despite possibly presenting undesirable consequences at first, the adoption of natural capital accounting can be beneficial to firms later on, with reputational gains representing important strategic incentives. Further research in different countries and industries will be beneficial to assess the possible context impact on our results.

Unraveling impacts on carbon, water and energy exchange of Pinus plantations in South American temperate ecosystems

Tree plantations are expanding in southern South America and their effects on ecosystem services, particularly climate regulation, are still not well understood. Here, we used remote sensing techniques and a paired design to analyze ≈33,000 ha of Pinus plantations along a broad geographical and environmental gradient (26–43° South latitude, 54–72° West longitude). Radiation interception, surface temperature, evapotranspiration, and albedo were assessed both in tree plantations stands and in adjacent uncultivated areas. Additionally, the climatic impact of tree plantations was quantified by analyzing changes in atmospheric radiative forcing and its carbon (C) equivalent. Tree plantations intercepted more radiation when replacing steppes, grasslands, and shrublands but not when replacing forests. The control exerted on radiation interception by precipitation decreased in both space and time after tree plantation. Furthermore, evapotranspiration notably increased in tree plantations. The lower albedo of tree plantations compared to uncultivated adjacent areas induces global warming through the biophysical pathway. Thus, the climate benefits of afforestation through C sequestration can be counteracted by 18 to 83 % due to albedo changes. It is necessary to fully consider the biophysical effects and water footprint of tree plantations in public policies that promote them, as well as in international carbon accounting mechanisms.

Assessment of Agricultural Virtual Water Export of Türkiye

As the negative effects of climate change are amplified, the agriculture sector is becoming more fragile. Food security is under risk because agriculture is highly dependent on climatic conditions and availability of water resources all over the world. For this reason, the concepts of virtual water and water footprint have begun to gain importance as decision-support tools for the effective and efficient use of water. However, there is a gap in the literature, where few studies focus on virtual water trade. Given the increasing stress caused by reasons such as the scarcity of water resources and climate change, this concept is likely to gain serious attention in the coming years. Türkiye is a water-stressed country whose water resources are decreasing due to the impact of climate change. More effective water management is needed to meet the increasing demand. In this study, virtual water was determined for Türkiye's agricultural export, and it was observed that crops with high water footprint but low economic returns were also exported in large amounts. It was revealed that the virtual amount of water exported by the evaluated crops was 5.9 billion m3 annually. This value is high enough to meet the domestic water needs of a metropolitan city like Istanbul for seven years. It is evident that water footprint and virtual water concepts would help decision makers to support optimized water consumption and sustainable water management.

Sustainable millet-based ethanol production in India: a comprehensive analysis of water footprint and environmental impact

This research seeks to comprehensively assess the water footprint and environmental sustainability of millet-based ethanol production in India, responding to the growing interest in resilient and nutritious alternatives. Utilizing a life cycle assessment approach, the study will scrutinize water usage across the entire production process, from millet cultivation to ethanol extraction. The primary aim is to gain an in-depth understanding of water consumption at each stage, pinpointing areas for enhancement and efficiency. Rajasthan exhibited the highest total water footprint at 6596 m3/ton, primarily due to its substantial ETc value, while Andhra Pradesh showcased the lowest at 1906 m3/ton, owing to its high average yield. Haryana displayed significant water usage during crop production, with a water footprint of 5870 m3/ton, where WFgreen, WFblue, and WFgrey contributed 3730 m3/ton, 2010 m3/ton and 130 m3/ton respectively. Uttar Pradesh demonstrated a comparatively lower total water footprint of 2564 m3/ton. These findings are anticipated to offer valuable insights into the viability and sustainability of millet-derived ethanol as an eco-friendly biofuel option in India, guiding policymakers, researchers, and stakeholders in promoting its adoption and addressing environmental challenges linked with conventional fuel sources.

Multifunctional Scavenger Boosts Cathode Interfacial Stability with Reduced Water Footprint for Direct Recycling of Spent Lithium-Ion Batteries.

The burgeoning accumulation of spent lithium-ion batteries (LIBs), a byproduct from the widespread adoption of portable electronics and electric vehicles, necessitates efficient recycling strategies. Direct recycling represents a promising strategy to maximize the value of LIB waste and minimize harmful environmental outcomes. However, current efforts to large-scale direct recycling face challenges stemming from heterophase residues (e.g., Li2CO3, LiOH) in the recycled products and uncontrolled interfacial instability, often requiring repeated washing that generates significant wastewater. Here, a refined direct recycling process is proposed to improve cathode interface stability by leveraging in situ reaction between surface residual lithium species and a weak inorganic acid to form a conformal Li+ conductive coating that stabilizes the regenerated Ni-rich cathodes with significantly reduced water footprint. The findings reveal that the conductive coating also prevents direct contact between contaminants and the cathode surface, thus improving the ambient storage stability. By eliminating the need for extensive washing, this intensified recycling process offers a more sustainable approach with the potential to transition from laboratory to industrial-scale applications, improving both product quality and environmental sustainability.

Assessment of the water footprint of the brewery industry: The case of Heineken, Addis Ababa, Ethiopia

The brewery industry is among the most water-intensive sectors, typically consuming 4–6 L of water for every liter of beer produced, necessitating a strong focus on water sustainability. Therefore, this study aimed to quantify the water footprint (WF) of the Heineken Ethiopian beer industry in Addis Ababa (Kilinto) over five consecutive years to identify water-intensive processes and areas. A stepwise accumulative and bottom-up approach was used to measure this WF, including calculations for both the final beer product and the spent grain byproduct. In 2019 and 2020, a significant portion of water consumption was attributed to spent grain extraction. By 2023, although the blue water footprint of both products remained within sustainable limits, more water was used in producing the final beer than in extracting spent grain. This suggests rapid improvements in water efficiency within the brewery, likely driven by effective water management practices such as leak detection and the use of water-efficient equipment and processes. The WF assessments also evaluated four sections of the brewery: utility, brewing, packaging, and general services. While utility, brewing, and packaging sections demonstrated improved water efficiency over time, the general services section saw a decrease. Given that general services are the most water-intensive area, prioritizing water management strategies in this section is crucial for overall sustainability.

Water footprint: A chemical view on strategies for sustainable water use

Water footprint: A chemical view on strategies for sustainable water use

Emerging Issues in Energy Sustainability: A Systematic Review and Research Agenda

This research paper seeks to investigate and categorize previous studies to understand better the role of energy generation technology in promoting sustainable development of a country country. The primary aim of this review is to identify and emphasize key issues related to energy sustainability. The study employs a systematic review approach, drawing on academic publications from the Web of Science and Scopus database. The analysis reveals five key issues: the nexus between energy generation and greenhouse gas emissions, energy generation and employment, the impact of energy generation and land use intensity, the association between energy generation and water footprint, and the nexus between energy generation and human health. This study delves into the theoretical dimensions of research concerning the interplay between energy sustainability and various aspects of energy generation technologies. Furthermore, it contributes to the existing body of knowledge concerning Sustainable Development Goal 7, with the overarching goal of enhancing both human well-being and economic prosperity through advancements in energy generation technologies. The study comprehensively explores the subject matter, offering an in-depth analysis of energy sustainability. Its unique contribution lies in its extensive examination of multiple facets of energy sustainability, making it a significant addition to the field of research.

National water use of coal-fired power generation: Hybrid life cycle assessment in China

Previous studies of water use for coal-fired power generation may have overlooked inter-sectoral impacts in the supply chain. Indeed, to devise effective water conservation strategies during the ongoing energy transition, it is of utmost importance to analyze the sectoral water use structures and flows in the supply chain and identify the sources of water scarcity. Therefore, based on the power sector-split environmentally extended input‒output (EEIO) model and the life cycle assessment (LCA) idea, we comprehensively analyze the nexus between coal-fired power generation and water use from a sectoral perspective. Our findings reveal a complex and diverse water use structure in coal-fired power generation. The technology of production inherently determines the high intensity of water withdrawal, and the close intersectoral linkages, particularly with agriculture, construction, and some industrial sectors, in the production process result in an intricate web of indirect water withdrawal and blue water footprint (WF). Moreover, the grey WF, primarily sourced from coal mining and indirectly tied to tertiary industries, underscores critical areas for attention in water pollution management. Finally, water use in the coal-fired power sector is projected to remain at elevated levels in the short to medium term under various transition strategies. Following an in-depth exploration of the coal-fired power‒water use nexus, the findings can offer new perspectives and specific entry points for sustainable energy development and water resource management.

A bibliometric analysis of water footprint in China and abroad: research hotspots and frontiers

ABSTRACT The water footprint (WF) serves as a vital tool for quantifying human water resource consumption and is extensively utilized for water allocation analysis and management. This study employs CiteSpace to visualize literature from the Web of Science and the China National Knowledge Infrastructure from 2000 to 2023. Initially, quantitative analysis identified the characteristics of WF. Keyword analysis then elucidated the similarities, differences, and temporal-spatial changes in domestic and international research hot spots. Additionally, co-cited literature networks systematically explored research frontiers in the WF field. China and foreign countries share common research themes while maintaining distinct characteristics. Specifically, the research results show that: (1) Chinese researchers keep up with the pace of international research, and the research results in the field of WF are updated quickly; (2) environmental impact, water–food–energy nexus, and gray WF have attracted attention globally. The international research focus is on the renewal of WF methodology. In contrast, Chinese researchers are more inclined to use methods on water-saving strategies and driving factors. (3) The research frontier mainly focuses on the updating of WF assessment methods and sustainable water use.

Optimal resource reallocation can achieve water conservation, emissions reduction, and improve irrigated agricultural systems

CONTEXTCrop production consumes large volumes of fresh water and is a key contributor to anthropogenic greenhouse gas (GHG) emissions. Increasing crop output to ensure adequate food supplies under water and land scarcity relies excessively on intensive agricultural inputs (e.g., fertilizers, pesticides, and agricultural films), leading to irreparable environmental consequences (water scarcity and degradation and GHG emissions). Therefore, research on a nexus approach and resource optimization model were carried out. OBJECTIVETo fill the gap of objectives priority and optimal allocation of water resources at irrigation area scale, this study constructed a model to achieve optimal water conservation, GHG emissions reduction, and economic benefit improvement, covering the cumulative environmental burden of agricultural inputs, production processes, trade and consumption related to agricultural activities. METHODSBased on a resource-environmental-economic framework, we took the blue water footprint (WFblue) as a decision variable and developed an integrated water resource optimization model, which was solved by the non-dominated Sorting Genetic Algorithm-II in Matlab. Minimizing crop water footprint (WFcrop), minimizing crop carbon emissions (CEcrop) and maximizing crop economic benefits (EBcrop) were the objectives of the model, and blue water resource, food security, electric energy consumption and land security were the constraint conditions. In addition, three scenarios were tested based on the priority of the objective functions. RESULTS AND CONCLUSIONSAnnually, WFcrop was 1234.29 × 106 m3 and CEcrop was 522.45 Gg CO2 eq for food production in Lianshui Irrigation District from 2005 to 2019. Grain crops exhibited a greater WFcrop and contributed significantly more to CEcrop than oilseed crops. Virtual water and carbon flows increased with food transfer. By adjusting the WFblue of crops compared to the baseline scenario (BS), the average WFcrop decreased by 10.0 %, CEcrop decreased by 4.0 %, and EBcrop increased by 6.4 % under Scenario 2 (minimizing WFcrop and maximizing EBcrop), respectively. Similarly, there were average reductions of 9.2 % in WFcrop, 6.2 % in CEcrop, and EBcrop increased by 5.6 % under Scenario 3 (minimizing CEcrop and maximizing EBcrop) compared to the BS. Therefore, the integrated model achieved the optimization objectives. SIGNIFICANCEThis research not only broadens the scope of traditional environmental impact assessments in agricultural production, but also underscores the positive impact of scientifically and rationally redistributing resources for water conservation, GHG emissions reduction, and economic benefit improvement.

Water Footprint Assessment of Agricultural Production in Bilecik Province

The freshwater sources are under serious pressure both in terms of quality characteristics due to pollution and in terms of quantity due to the increase in parameters such as temperature and evaporation under the influence of global warming. To ensure sustainable use of these resources, it is necessary to employ high-efficiency pressurized irrigation systems and cultivate plant species that are resilient to various stress factors and highly productive. In determining the water usage characteristics of plants, rapid atmospheric effects brought by climate change, plant water and temperature stress, soil moisture should be monitored, and water production indicators should be determined. In the water-intensive agricultural sector, monitoring the water footprint has become one of the important indicators in terms of ensuring water-food-energy sustainability, efficient use and fair sharing of water resources. This study aims to determine the water footprint of agricultural production in Bilecik province and its districts located in the transitional zone. Accordingly, values of crop and livestock production throughout the province and using a volume-based approach, the water footprint of crop production is estimated at 0.6 billion cubic meters (BCM), while the water footprint of livestock production is 0.5 BCM, resulting in a total agricultural water footprint of 1.1 BCM. In crop production, green water footprint constitutes 33%, blue water footprint 59%, and grey water footprint 8% of the total water footprint. The data obtained will form the basis for developing strategies in sustainable water and food management, aligned with climate change scenarios, to achieve sectoral supply-demand balance.

Impact of Irrigation Management Decisions on the Water Footprint of Processing Tomatoes in Southern Spain

The water footprint is an increasingly demanded environmental sustainability indicator for certifications and labels in agricultural production. Processing tomatoes are highly water-intensive, and existing studies on water footprint have uncertainties and do not consider the impact of different irrigation configurations (e.g., surface drip irrigation (SDI) and subsurface drip irrigation (SSDI)) and irrigation strategies. This study presents a two-year experimental investigation to determine the water footprint of processing tomatoes grown in southern Spain (Andalusia) and the impact of SSDI and deficit irrigation. Five irrigation treatments were established: SDI1 (surface drip irrigation without water limitation), SDI2 (surface drip irrigation without water limitation adjusted by soil moisture readings), SSDI1 (subsurface drip irrigation without water limitation and a dripline depth of 15 cm), SSDI2 (similar to SSDI1 but with mild/moderate water deficit during the fruit ripening stage), and SSDI3 (subsurface drip irrigation without water limitation and a dripline depth of 35 cm (first year) and 25 cm (second year)). Measurements included crop vegetative growth, leaf water potential, leaf gas exchange, nitrate concentration in soil solution, and crop yield and quality. The soil water balance components (actual evaporation, actual transpiration, deep drainage), necessary for determining the total crop water footprint, were simulated on a daily scale using Hydrus 2D software. Results indicated that SSDI makes more efficient use of irrigation water than SDI. The water footprint of SSDI1 was 20–35% lower than that of SDI1. SSDI2 showed similar water footprint values to SDI1 under highly demanding environmental conditions and significantly lower values (≈40%) in a year with lower evaporative demand. The dripline depth in SSDI was critical to the water footprint. With a 35 cm installation depth, SSDI3 had a significantly higher water footprint than the other treatments, while the values were similar to SSDI1 when the depth was reduced to 25 cm.

Ecosystem Services’ Supply–Demand Assessment and Ecological Management Zoning in Northwest China: A Perspective of the Water–Food–Ecology Nexus

The coordinated development of the water–food–ecology (WFE) nexus is a practical issue that has to be addressed urgently for northwest China’s (WTL) sustainable development. Optimizing the linkage relationship and accomplishing the rational distribution of resources from the perspective of the supply and demand for ecosystem services (ESSD) are imperative. Thus, in this study, a numerical indicator system for ESSD from the perspective of the WFE nexus was constructed with the incorporation of the water and carbon footprint. Based on this premise, the ecological management zoning method was enhanced by integrating supply and demand risks, and optimization suggestions were proposed for various zones. The results showed that (1) carbon sequestration (CS), food production (FP), and water yield (WY) supply and demand significantly increased between 2000 and 2021. High ESSDs were concentrated in the west side of northwest China. Maize, wheat, cotton, vegetables, and garden fruits had a higher demand for ecosystem services (ESs). (2) The three ESSDs were bound in a synergistic relationship. The synergy between supply exhibited significant spatial heterogeneity, while the synergies between demand showed similar distribution patterns. (3) Regarding quantity matching, the supply for FP and CS surpassed demand, while the WY supply could not meet the demand. The three ESs’ supply and demand deficits rose. Ecological supply–demand ratio (ESDR) regional differentiation for the three ESs was apparent. Regarding spatial matching, FP and CS concentrated on low supply–low demand, while WY focused on high supply–high demand. FP risk was concentrated in Qaidam Basin, whereas WY risk was mostly in Hexi inland river basin (HX), the Yellow River Basin area (HH), and both sides of the “Qice line”. (4) The ecological management zones were formed by integrating WTL’s three dominant weak functional zones, four categorized strategy regions, and four governance models. This study can serve as a scientific benchmark for regional ecological management, which is significant in ensuring northwest China’s water, food, and ecological safety.

Greenhouse gas, water, and economic implications of permeable pavements: Quantification for pilot sponge cities in China

Climate change has exacerbated the occurrence of extreme storms, resulting in urban flooding. However, rainwater is a potential source of water for various end uses of municipal water. In this context, permeable pavements are promising for mitigating floods and alleviating water stress in cities. Herein, a process-based life-cycle inventory modeling approach was used to quantify the life-cycle greenhouse gas (GHG) and water footprints of different road pavements in 28 pilot sponge cities in China. Three asphalt pavements were considered in this study: permeable-surface, permeable-base, and conventional nonpermeable pavements. Moreover, life-cycle cost analyses were performed to reveal the cost-effectiveness of these pavements. Results showed that permeable-base pavements exhibited the highest levelized GHG emissions (5.9 kg CO2e/m2/yr), followed by nonpermeable (5.5 kg CO2e/m2/yr) and permeable-surface pavements (3.8 kg CO2e/m2/yr). In terms of levelized water footprint, permeable-base and permeable-surface pavements enabled water savings (433.8 and 304.1 kg/m2/yr, respectively), while nonpermeable pavements consumed 30.6 kg/m2/yr of water. The levelized life-cycle costs of permeable-surface, permeable-base, and nonpermeable pavements were 32.8, 35.4, and 40.5 yuan/m2/yr, respectively. With regard to transitioning from nonpermeable to permeable pavements in urban road construction, Chongqing and Shenzhen presented favorable potential for GHG mitigation (22 and 26 kt CO2e/yr, respectively) and water savings (196 and 187 Mt/yr, respectively). Contrarily, Hebi, Yuxi, Sanya, Qianan, Chizhou, and Xining were not cost-effective in terms of GHG emission reduction. Moreover, in this study, GHG–water–cost tradeoffs were identified among different pavements, highlighting directions for unlocking the green benefits of installing permeable asphalt pavements in China.

Evaluation of water resource balance in the Urmia Lake Basin: Integrating carrying capacity and water footprint model for sustainable management

Given the scarcity of water resources and the ever-growing demand, effective water flow management becomes crucial. The Lake Urmia Basin, a critical region in Iran, faces severe water scarcity exacerbated by climatic changes, land use alterations, over-extraction of groundwater, and mismanagement. This study evaluates the water resource balance by integrating carrying capacity and water footprint models to assess sustainable water management practices. Utilizing the InVEST model, water provisioning ecosystem services have been estimated as the supply, while the ecological footprint method quantifies water demand across various sectors. Three scenarios are evaluated: continuation of the current situation, an ideal scenario with substantial reductions in water consumption and pollution, and implementation of operational programs. The findings reveal significant water deficits in certain sub-basins, highlighting the need for a fundamental revision of resource allocation based on each region’s ecological capacity. Lake Urmia, the central nucleus of the basin, has experienced a significant size reduction, approximately 10 % of its original size, from the early 1990s to 2018, due to climatic changes, land use alterations, over-extraction of groundwater, and mismanagement. The environmental deficit in some sub-basins raises serious concerns, even in the best scenario where ecological footprint reduction is considered. These results underscore the effectiveness of ecosystem-based comprehensive capacity analysis for sustainable watershed development. This research offers a unified spatial system for quantifying ecological footprints and land resilience, providing critical insights into addressing water scarcity and supporting holistic regional planning.

Investigating agricultural water sustainability in arid regions with Bayesian network and water footprint theories

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.