Nitrogen and phosphorus control faces great challenges in small and medium-sized watersheds with both point and non-point source pollution, especially in data-scarce watersheds with obvious spatial heterogeneity. This study develops a high-resolution simulation framework to tackle this issue, which integrates multi-source data completion, SWAT-QUAL2K model coupling and spatiotemporally refined pollution source identification. We fuse multi-source information to build a point source pollution database with hourly temporal resolution and 500 m x 500 m grid spatial resolution, and then establish a high-resolution SWAT model on this basis. The model simulates hydrological and water quality processes, and identifies critical source areas as well as multi-scale spatiotemporal emission characteristics of nitrogen and phosphorus pollution. We further couple SWAT outputs with QUAL2K to quantify pollution source contributions at the watershed outlet. We select the Yanjin River Basin as the case study, a data-scarce small watershed with dense industrial point sources and severe agricultural non-point source pollution. The high-resolution database effectively captures hourly emission characteristics of different point sources at 500 m grid scale and greatly improves model input accuracy. The SWAT model reaches a Nash-Sutcliffe efficiency of 0.67 similar to 0.96 and an R-2 of 0.77 similar to 0.97, and the QUAL2K model shows a percent bias below 16%, reflecting good simulation performance. Overall, the proposed framework achieves accurate multi-scale simulation and source apportionment of nitrogen and phosphorus pollution, and provides a scientific basis for targeted pollution control in data-scarce small and medium-sized watersheds with dense point sources.

ABSTRACT Accurate daily pan evaporation (E pan ) records are needed to diagnose changes in atmospheric evaporative demand, but long‐term analyses can be confounded by instrument transitions and inconsistent treatment of missing or freezing‐period observations. We developed an observation‐aware framework that combined instrument homogenisation, sequence‐based daily reconstruction and interpretable attribution across China's climate gradients during 2000–2024. Historical D20 observations were converted to E601‐equivalent values with a meteorology‐dependent random forest model, producing a homogenised daily dataset for 1351 stations. A Transformer driven exclusively by meteorological forcing then reconstructed daily E pan , and SHAP analysis quantified the contributions of thermal, radiative, aerodynamic and moisture‐related variables. The Transformer achieved the highest performance among the evaluated models (NSE = 0.76; RMSE = 0.83 mm day −1 ). The reconstruction showed that the evaporation paradox was spatially heterogeneous rather than a uniform response to warming. E pan increased significantly in the Huaihe, Haihe and Yangtze River Basins, whereas it declined significantly in the Songliao River Basin (−0.74 mm a −1 , p < 0.01). There, declining shortwave radiation and moisture‐related constraints offset the positive contribution of temperature. In contrast with previous studies that variously emphasised land–atmosphere complementarity, declining wind speed, reduced solar input or rising vapour‐pressure deficit, the Chinese results showed that the controlling balance changed among hydroclimatic regimes. This workflow separated observing‐system discontinuities from climate signals before daily reconstruction and attribution, and can be adapted to other heterogeneous monitoring networks that require local data, recalibration and independent validation.

The New Energy Demonstration City(NEDC)policy is a crucial measure to promote energy transition and achieve the"dual carbon"goals.A systematic assessment of its impact on environmental welfare performance is essential for advancing sustainable energy development and enhancing residents'well-being.Economic development,environmental pollution,and residents'health factors were simultaneously incorporated into the measurement of environmental welfare performance.A two-stage network super-efficiency SBM model was applied to calculate this indicator,and the impact of the NEDC policy on environmental welfare performance is evaluated.The findings are as follows.First,the NEDC policy significantly improves environmental welfare performance,and this conclusion remains valid after a series of robustness tests.Second,environmental regulation and average temperature play positive moderating roles in the impact of the NEDC policy on environmental welfare performance,while average altitude exerts a negative moderating effect.The NEDC policy promotes the improvement of environmental welfare performance by enhancing energy utilization efficiency and new infrastructure construction.Third,in terms of geographical location,the impact of the NEDC policy on environmental welfare performance is more significant in eastern and southern China,and is significant in regions on both sides of the"Hu Huanyong Line".In terms of urban characteristics,the promotion effect is more pronounced in megacities,central cities,and cities with carbon trading platforms,while it has an inhibitory effect in large megacities.Fourth,the impact of the NEDC policy on environmental welfare performance has a positive spatial spillover effect.It provides policy implications for the government to optimize energy development and improve residents'well-being.

Rapid population and economic growth have led to an increased demand for water and food, thereby exacerbating the water scarcity crisis. Therefore, an objective assessment of water usage in crop production is crucial for ensuring national food security and alleviating water scarcity. However, the city-scale crop production water footprint (CWF) in China remains incomplete, while grid-scale CWF data are plagued by the limitations of coarse crop statistics. To fill this knowledge gap, we propose a novel methodology for developing a high-resolution inventory of CWFs. Based on this methodology, we quantified the city-scale water footprint (WF) of three major crops (rice, wheat, and maize) in China and allocated the CWFs of individual cities to 3 km × 3 km grids through a top-down downscaling approach to create a high-resolution CWF inventory. The results show that the average annual CWF of the three crops from 2000 to 2020 was in the order of rice (2.50 × 1012 m3), maize (1.55 × 1012 m3) , and wheat (1.21 × 1012 m3). During the study period, the dependence on green water resources for crop production in China increased, especially for maize, which showed a relative increase of 106.76% in green water demand, in addition to optimal water use efficiency, with the dual advantages of combining high yield and low irrigation dependence. At a grid scale of 3 km × 3 km, the CWFs of the three crops followed the same order as at the city scale. Furthermore, the green water footprint (GWF) of each of the three crops increased at different rates during the study period, with maize showing a particularly significant increase of 59.26%. Meanwhile, the blue water footprint (BWF) per unit area for rice and wheat increased, while the BWF for maize decreased by 0.94%. This finding implies that maize cultivation is more efficient in utilizing rainwater resources, thereby reducing dependence on blue water. The inventory established in this study can assist in optimizing crop production in various regions of China, thereby mitigating the effects of water scarcity and facilitating sustainable agricultural development.

The transition to renewable energy exacerbates direct land occupation by infrastructure, leading to habitat degradation and biodiversity loss. However, biodiversity loss driven by the production and consumption of different renewable energy deployment scenarios remains largely unquantified. Quantifying biodiversity loss associated with land occupation of renewable energy infrastructure is essential for a sustainable energy transition. Here, we developed a novel data set to evaluate renewable energy-related biodiversity loss by considering the current infrastructure setting and future development pathways. We found that the land occupation of renewable energy infrastructure resulted in global biodiversity loss equivalent amounting to 19 x 10-4 global pdf in 2015. Severe biodiversity loss was concentrated primarily in densely populated and economically advanced countries, such as China, the United States, Brazil, India, Australia, Russia, and countries across Western Europe. International trade accounted for 14% of the biodiversity loss. Future renewable energy transition scenarios will lead to a global cumulative biodiversity loss of 1.2 x 10-2-2.2 x 10-2 global pdf during 2015-2060. By 2060, ambitious energy transition policies are projected to increase the biodiversity loss by 1.7-1.8 times. The results underscore that while renewable energy could tackle climate change, its deployment should avoid encroaching on biodiversity hotspots.

Hydrogen fuel cell vehicles (HFCV) emerge as the promising alternative to internal combustion engine vehicles (ICEV). This study focuses on hydrogen fuel cell buses (HFCB) and assesses carbon footprint (CF) across the life cycle. During the production phase, the average carbon emissions of HFCB are 84055.91 kgCO2eq, significantly higher than the 43881.92 kgCO2eq of ICEV. During the usage phase, HFCB's emissions are significant, but the cleanliness of hydrogen production methods can significantly reduce the emissions. In the recycling phase, the average carbon reduction achieved by HFCB is 12897.11 kgCO2eq, surpassing the 10746.24 kgCO2eq reduction of ICEV. However, it is not sufficient to offset the carbon emissions generated throughout the life cycle of HFCB. The overall lifecycle CF of HFCB exceeds that of ICEV. Finally, with changes in power infrastructure and advancements in hydrogen production, HFCB will contribute positively to carbon neutrality, accelerating the achievement of the 2060 carbon neutrality target.

Addressing water scarcity requires significant attention to reducing water footprint (WF) related to food consumption. Since individuals' dietary behavior is largely influenced by their demographic and anthropometric attributes, it is crucial to identify individuals who have a high dietary WF and prioritize them as the focus of policies. Several studies analyzing the driving factors behind dietary WF exist but have multiple limitations. These include the statistical models with rather modest performances, lack of rigorous sensitivity analysis/feature importance (FI) analysis, and lack of generalization ability. Here, we developed a novel ML-based framework for analyzing the driving forces behind dietary WF. The framework incorporated three machine learning (ML) models (Extra-Trees (ET), Histogram-based Gradient Boosting (HGB), and eXtreme Gradient Boosting (XGB)) and an ML explanation approach Shapley Additive exPlanations (SHAP). This framework was applied to a case study on Chinese inhabitants. The derived results validated the proposed framework and demonstrated ML's superiority over conventional statistical methods. XGB was identified as the optimal model as it effectively captured the variability in the data and showed good generalization performance. The FI analysis for XGB revealed the most influential features on dietary WF, with income level, urbanization level, education level, and gender emerging as the top four features in descending order. Through the subsequent SHAP dependence analysis, the priority groups for dietary WF reduction interventions were identified as high-income residents, urban residents, highly educated residents, and male residents. In light of these findings and their underlying causes, the paper concluded with a set of policy recommendations.

Overexploiting ecosystems to meet growing food demands threatens global agricultural sustainability and food security. Addressing these challenges requires solutions tailored to regional agro-ecological boundaries (AEBs) and overall agro-ecological risks. Here, we propose a globally consistent and regionally adapted approach for quantifying regional AEBs. Based on this approach, we develop a region-specific integrated Footprint-AEB framework that combines six environmental footprints (EFs) with AEBs to capture the overall environmental impacts on China's regional agro-ecosystems. Results indicate that individual EFs cannot reliably reveal the complexity of agro-ecological stressors without comprehensive assessment relative to regionally determined boundaries. For example, Northwest China faces higher water boundary stress despite lower water footprints compared to Central China, and regions such as Qinghai and Ningxia exhibit higher integrated AEB stress driven by combined water, land, and biodiversity stresses. Additionally, imbalanced integrated AEB stress transfer via trade, mainly from industrialized eastern to vulnerable western regions, is identified as a key driver of AEB exceedance in Northwest China. This fosters a nuanced understanding of environmental responsibility and equity. The integrated Footprint-AEB framework provides new insights into agro-ecosystem dynamics and supports targeted interventions to avoid shifting environmental stressors. These challenges confront agro-ecosystems worldwide.

Ensuring food security while mitigating environmental degradation remains a critical challenge for global sustainability. Food systems, encompassing production, transportation, consumption, and waste, exert significant environmental pressures, such as greenhouse gas emissions, excessive water and land use, and nutrient losses. This study systematically reviews the environmental footprints of food systems from a life cycle perspective, analyzing research trends, and hot issues. The results reveal a sharp increase in publications on carbon and water footprints, while nitrogen, phosphorus, biodiversity, and chemical footprints remain comparatively underexplored. Keyword co-occurrence analysis further illustrates this imbalance by identifying six key research hotspots, with "carbon footprint" and "water footprint" most frequently studied. The findings underscore the strong interconnection between agriculture, dietary choices, and environmental impacts, emphasizing the pivotal role of sustainable diets and green agricultural practices in advancing food system sustainability. Future research should prioritize expanding the footprint diversity and increasing the representation of studies in less developed regions to support a more comprehensive understanding of sustainability challenges. The safe operating space of the food system also needs to be redefined to better align with achieving food security within planetary boundaries. In addition, future research should establish a food-environment-society-economic nexus framework to integrate food systems with the SDGs and capture the complex interlinkages and trade-offs between different systems. This review provides new insights into future research and policy directions for sustainable food system transformation.

Lake Taihu, a large, shallow freshwater lake in China, has experienced severe eutrophication for decades under intense human activities occurring around cities. Through long-term water quality management since 1995, the eutrophication of Lake Taihu has been controlled. This review examines the eutrophication characteristics, source identification methods, and control measures in Lake Taihu. Phosphorus is a primary driver of eutrophication, correlating strongly with chlorophyll a. The lake exhibits significant temporal and spatial variability in nutrient dynamics, influenced by human activities and the climate. Historical data show fluctuating nutrient levels and persistent algal blooms despite government efforts. A critical assessment of various source apportionment methods, including statistical analysis, physical modeling, and empirical models, is presented to elucidate the relative contributions of different nutrient sources. These methods identify agricultural non-point and urban point sources as major external contributors, with sediment nutrient release as a significant internal source. Implemented controls, including wastewater treatment plants and non-point-source management, have had limited success. Increased sewage and sediment nutrients necessitate integrated watershed management. Future research should prioritize advanced source tracking, sediment dynamics, climate impacts, and integrated ecological models. Sustainable eutrophication management in Lake Taihu requires integrated science, policy, and public engagement to ensure ecosystem health.

This study aims to reasonably measure the level of scientific and technological innovation. The evaluation index system of scientific and technological innovation level in China is constructed from four aspects: input, effectiveness, environment, and output of scientific and technological innovation. The panel data of 30 provinces in China from 2010 to 2022 were selected, and the improved CRITIC method and fuzzy matter-element analysis method were used to comprehensively measure the scientific and technological innovation level in China. Then, the Dagum Gini coefficient, kernel density estimation, and exploratory spatial data analysis are used to explore the regional differences and spatial dynamic evolution process of China's scientific and technological innovation level. The results show that during the sample observation period, the overall level of scientific and technological innovation in China shows an upward trend, with an average annual growth rate of 4.51%. However, the overall level is still low, with only one-third of the provinces reaching the national average level, showing "low in the west and high in the east" characteristics. From the perspective of regional differences, the overall difference in scientific and technological innovation level showed a downward trend, and regional differences were the most important source, with an average contribution rate of 62.82%. From the perspective of dynamic evolution trends, the center position and variation interval of the overall distribution curve of the country gradually moved to the right. The curve had a right-trailing phenomenon, indicating that each region's scientific and technological innovation level was gradually improving. Still, the overall gap was narrowing, and scientific and technological innovation development showed a two-level differentiation pattern and spatial imbalance.

Agricultural and food security cooperation has emerged as a cornerstone of the current Belt and Road Initiative (BRI). However, most BRI countries are facing the twin challenges of ecological degradation and food insecurity. Here, we developed a Boundary-Impact-Coupling framework by integrating Doughnut Economics, Multi-regional Input-Output Models, and the Coupling Coordination Degree Model. Within this framework, we delineated the dual boundaries of agri-food systems, namely the ecological ceilings and food security thresholds, and identified the food security and environmental performance of BRI countries in 2020, along with their interactions. Results indicate that most BRI countries face dual crises of environmental boundaries transgressions and food insecurity. Trade-offs between food security and environmental performance are widespread, underscoring the necessity for sustainable agricultural transitions. These findings offer valuable insights to support policies that balance food security and environmental sustainability, thereby promoting a green transformation in agriculture within the BRI.

Soil erosion threatens global agricultural and environmental sustainability. Previous studies connected soil erosion to supply chains by using national aggregates, but this approach lacks crop-specific and spatially precise responsibility allocation. Here, we integrate 0.05 degrees gridded cropland soil erosion data, crop distributions, and a physical-unit Food and Agriculture Biomass Input-Output (FABIO) model to trace soil erosion footprints across 123 crop sectors and 187 economies in 2019. We found that similar to 30% of hotspots (southern Brazil, southwestern China, and the central United States) contribute >90% of total soil erosion. Furthermore, global supply chains shape convergent consumption among major economies, with agricultural imports predominantly sourced from neighboring regions and Brazil. We showcase the hotspots driven specifically by international trade. Our study provides the first subnational-scale quantification of the consumption drivers of cropland soil erosion hotspots, highlighting the imperative for multi-scale governance frameworks spanning local to global scales to regulate production-consumption dynamics effectively.

With the global push toward carbon neutrality, reducing greenhouse gas emissions in the transportation sector has become increasingly urgent. Electric buses represent a promising solution; however, their full life cycle carbon footprint remains underexplored. This study aims to address this gap by quantifying and comparing the life cycle carbon emissions of pure electric buses. A life cycle assessment (LCA) approach is applied to evaluate emissions across the production, usage, and recycling stages. Scenario analyses are conducted to assess the impact of carbon fiber reinforced polymer (CFRP) as a material substitute, variations in electricity generation mix, coal consumption rates, and the extent of recycled material utilization. Results show that buses using nickel manganese cobalt (NMC) battery type C have the lowest life cycle emissions at 55,814.89 kg CO2-eq, while those with lithium iron phosphate (LFP) battery type A have the highest, reaching 59,364.10 kg CO2-eq. During the production stage, the primary emission sources are the body, chassis, battery system, and electricity consumption. Substituting steel and aluminum with CFRP increases production emissions by up to 108.6%. However, in the operational phase, CFRP significantly reduces bus weight by 41.99% and cuts operational carbon emissions by 36.49%. In the recycling stage, NMC battery type C yields the highest emission reduction, achieving 14,943.86 kg CO2-eq, mainly due to the recovery of nickel and lithium compounds. These findings offer valuable insights for optimizing material choices, energy structures, and recycling strategies to support the low-carbon development of electric buses.

With the rise of global value chain (GVC), traditional accounting methods for virtual water (VW) trade have failed to reflect the inherent VW flow generated by the production of intermediate goods in shared production processes. Here, we reassess China's VW consumption in 2020 based on a new GVC framework, and propose the concept of VW consumption embodied in forward and backward GVC activities (VWF/VWB). We clarify China's role in GVC activities and reveal VWF/VWB inequalities under multiple scenarios. Our results show that the maximum share of VWF and VWB reaches 64.4% and 86.1%, respectively, far exceeding the traditional trade share. China's VWB primarily sources from developing countries in Asia, while VWF primarily serves the United States. VWF/VWB inequalities are exacerbated by China's GVC activities and exhibit considerable variation under multiple scenarios. Our findings provide new insights into reconciling China's GVC participation and narrowing regional disparities in VW consumption.

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.

The disclosure of global value chain (GVC) division and cooperation is essential for the rational allocation of water resources and the achievement of trade equality, particularly as the global division of labor becomes more pronounced. Currently, there are limited studies on the global value chain at the sub-national level, with most focusing on virtual water trade (VWT) characteristics between two trading partners, without integrating VWT into the global value chain and overlooking significant cooperation among participants. Here, we characterize the international division of GVC and VWT patterns covering 194 regions (31 regions in China and 163 countries) around the world in 2020, and then examine the inequality between virtual water (VW) and value-added (VA) transfer from both environmental and economic perspectives, focusing on the sub-national scale of China. Our results show that in terms of water consumption responsibilities, considerable heterogeneity can be seen in different regions across China. Furthermore, relying solely on the export of primary products for economic development will lead to inequality in trade between countries. In this study, we trace the characteristics of VWT, taking into account the participation and contribution of regions in numerous GVC linkages. In addition, to make our policy implications more targeted, we refine the study resolution to the sub-national scale. Our results suggest that countries should prioritize consumer responsibility in GVC, reduce the drawbacks of trade barriers, and dispassionately exploit the economic and environmental advantages of water resources.

Planetary boundaries have received considerable attention since they were first proposed, but applying various downscaling methods to the regional scale has certain limitations due to regional heterogeneity. The concept of ecological boundaries (EB) extends and complements planetary boundaries at a regional scale. However, previous studies have not considered the EB of multiple regions and the impact of interregional ecosystem service value (ESV) flows on EB. In this study, we optimized the EB accounting method and quantified the EB of 30 provinces in China from 2002 to 2017, then assessed the ecosystem unsustainability, and determined the impact of demand for goods and services on the consumption of local natural resources by each province in China using an ESV-extended multiregional input-output model. We found that EB increased in all provinces of China. The ecological unsustainability index of all 30 provinces was larger than 1, indicating a serious environmental unsustainability, but the magnitude of the index tends to decrease. Furthermore, the regions that have the greatest impact on exceeding EB in each province were concentrated in Guangdong and Henan. Guangdong had the highest total net imports in 2012 and 2015 (665.08 and 641.70 billion yuan, respectively), while Henan had the highest total net imports in 2017 (611.58 billion yuan). For the role of net exports, the rankings of the provinces differed in terms of the direct ESV and the boundary-exceeding ESV indicators. Our results reveal EB across provinces in China, underscoring the importance of considering the flow of ESV between regions in assessing the impact of exceeding EB. This study can assist policymakers in better allocating ecological resources within EB, which is critical for alleviating ecological pressures.