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Urban agriculture supports China’s vegetable supply without raising greenhouse gas emissions 都市农业在不增加温室气体排放的情况下支持了中国的蔬菜供应

IF 7.8 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-09-01 Epub Date: 2025-08-06 DOI: 10.1016/j.resenv.2025.100254

Yuanchao Hu , Prajal Pradhan , Haoran Zhang , Zhen Wang , Qianyuan Huang , Qiqi Jia , Xihong Lian , Chao Xu , Rui Yang , Yuxi Tian , Zhibang Xu , Limin Jiao , Jürgen P. Kropp

Measuring the production potential and environmental sustainability of urban agriculture in developing countries highlights the value of promoting it. We constructed a new dataset of urban productive spaces for 124 large Chinese cities, which includes indoor balconies, rooftops, urban open spaces, and courtyards. In particular, if moderately exploited, approximately 18% of the 13 million rooftops could be planted, considering factors such as building height, age, rooftop slope, occupation, and other restrictions. Applying both greenhouse and open-air cultivation techniques in all the spaces, about 30% (7%–198% across cities) of urban vegetable demand could be met. However, urban agriculture has little potential in greenhouse gas emission mitigation, with the average intensity (0.30 kgCO₂e/kg) being similar to traditional agriculture (0.31 kgCO₂e/kg), even if several system-wide benefits, such as reduced food miles, were considered. Despite the multiple benefits, conducting urban agriculture requires massive water, substrate, metal, and plastic inputs. We demonstrate that high-tech urban agriculture can have a lower GHG intensity, but it is essential to consider agroclimatic conditions and promote more sustainable practices.

衡量发展中国家城市农业的生产潜力和环境可持续性，凸显了促进城市农业的价值。我们为中国124个大城市构建了一个新的城市生产空间数据集，包括室内阳台、屋顶、城市开放空间和庭院。特别是，如果适度开发，考虑到建筑物高度、年龄、屋顶坡度、占用和其他限制等因素，1300万个屋顶中约有18%可以种植。在所有空间采用温室和露天栽培技术，可满足约30%（城市范围为7%-198%）的城市蔬菜需求。然而，城市农业在减缓温室气体排放方面几乎没有潜力，其平均强度（0.30千克二氧化碳当量/千克）与传统农业（0.31千克二氧化碳当量/千克）相似，即使考虑到减少食物里程等若干全系统效益。尽管有多种好处，但开展城市农业需要大量的水、基质、金属和塑料投入。我们证明高科技都市农业可以降低温室气体强度，但必须考虑农业气候条件并促进更可持续的做法。

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引用次数: 0

Integrative analysis of transboundary land use conflicts in the Aral Sea Basin: A multi-scale assessment of drivers and strategies for sustainable management 咸海盆地跨界土地利用冲突的综合分析：可持续管理驱动因素和策略的多尺度评估

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-09-01 Epub Date: 2025-06-04 DOI: 10.1016/j.resenv.2025.100240

Kaiyue Luo , Alim Samat , Peijun Du , Sicong Liu , Jiaxi Liang , Jilili Abuduwaili , Dana Shokparova , Mukhiddin Juliev

Addressing escalating land use conflicts (LUCs) is critical for sustainable development in resource-scarce, transboundary regions. The Aral Sea Basin (ASB), Central Asia’s largest transboundary basin characterized by arid conditions and vulnerable ecosystems, serves as a crucial case study. This research introduces an innovative framework, integrating multi-scale spatial assessments with interpretable machine learning (XGBoost-SHAP), to overcome limitations of previous fragmented analyses and provide deeper insights into LUCs dynamics. We systematically evaluated land suitability for ecological preservation, agriculture, and urban construction, quantified conflict intensity, and identified key drivers across the entire ASB, including its Amu Darya and Syr Darya sub-basins. Quantitative results reveal profound spatial heterogeneity in land use potential, with 56.29% of the basin suitable for ecological preservation, only 6.54% for agriculture, and 72.67% for urban construction—indicating dominant ecological value, limited agricultural suitability, and high urban development pressure. Conflicts were found to be pervasive and intense, driven by a complex interplay of natural factors and socio-economic pressures, with distinct upstream-downstream patterns across sub-basins. Crucially, this study provides spatially explicit evidence highlighting the urgent need for integrated, transboundary land management. The results offer actionable, data-driven insights essential for designing targeted strategies, fostering collaborative resource governance, and ultimately promoting sustainable development pathways that balance ecological integrity with human needs in the ASB and similar complex transboundary basins worldwide.

解决不断升级的土地利用冲突对资源稀缺的跨界地区的可持续发展至关重要。咸海盆地（ASB）是中亚最大的跨界盆地，其特点是干旱条件和脆弱的生态系统，是一个重要的案例研究。本研究引入了一个创新的框架，将多尺度空间评估与可解释性机器学习（XGBoost-SHAP）相结合，以克服以往碎片化分析的局限性，并为lucc动态提供更深入的见解。我们系统地评估了生态保护、农业和城市建设的土地适宜性，量化了冲突强度，并确定了整个ASB的关键驱动因素，包括阿姆河和锡尔河子流域。定量结果显示，流域土地利用潜力空间异质性较强，生态保护用地占56.29%，农业用地占6.54%，城市用地占72.67%，生态价值占主导地位，农业用地适宜性有限，城市发展压力较大。在自然因素和社会经济压力复杂的相互作用下，冲突普遍而激烈，各子盆地的上下游格局明显。至关重要的是，这项研究提供了空间上明确的证据，强调了综合跨境土地管理的迫切需要。研究结果提供了可操作的、数据驱动的见解，对于设计有针对性的战略、促进资源协作治理，并最终促进平衡ASB和全球类似复杂跨界流域的生态完整性与人类需求的可持续发展路径至关重要。

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引用次数: 0

Widening inequality: Diverging trends in CO2 and air pollutant emissions across Chinese cities 日益扩大的不平等：中国城市二氧化碳和空气污染物排放的不同趋势

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-09-01 Epub Date: 2025-04-17 DOI: 10.1016/j.resenv.2025.100227

Shuangzhi Li , Xiaoling Zhang , Zhongci Deng , Kang Liu , Jing Wang , Jin Fan

Chinese cities face escalating tensions between pollution mitigation and economic equity. Using an environmentally extended multi-regional input–output (EE-MRIO) model, we quantified the carbon and air pollutant footprints of 309 cities from 2012 to 2017 and applied structural decomposition analysis (SDA) to identify key emission drivers. The results indicate that inequality in air pollutant emissions, with a Gini coefficient of 0.31–0.53, is significantly higher than that of CO₂ (0.33–0.41). Developed cities generate 3.1 times more economic output per unit of CO₂ emissions than less developed cities, with the disparity widening over time. While intermediate input optimization contributed to a 1.94 Gt reduction in CO₂ emissions, its benefits were largely concentrated in developed regions and were accompanied by increased emissions of PM

_{2.5}

, BC, OC, and CO. Although reductions in emission intensity played a crucial role in mitigating pollutants, they paradoxically contributed to CO₂ growth in energy-intensive cities. Additionally, population growth and per capita final demand were the primary drivers of emission increases, and population growth had a greater impact on developed regions. These findings underscore the need for regionally differentiated policies, including carbon quota reallocation, industrial transformation in energy-dependent cities, and the promotion of green industries in less developed areas, to achieve a balance between environmental sustainability and economic development.

中国城市面临着污染缓解与经济公平之间日益紧张的局面。采用环境扩展的多区域投入产出（EE-MRIO）模型，对2012 - 2017年309个城市的碳足迹和空气污染物足迹进行量化，并应用结构分解分析（SDA）识别关键排放驱动因素。结果表明，大气污染物排放不平等的基尼系数为0.31 ~ 0.53，显著高于二氧化碳排放不平等的基尼系数（0.33 ~ 0.41）。发达城市每单位二氧化碳排放产生的经济产出是欠发达城市的3.1倍，而且差距随着时间的推移而扩大。虽然中间投入优化减少了1.94 Gt的二氧化碳排放量，但其效益主要集中在发达地区，并伴随着PM2.5、BC、OC和CO排放量的增加。尽管排放强度的降低在缓解污染物排放方面发挥了关键作用，但它们却矛盾地促进了能源密集型城市的二氧化碳排放量增长。此外，人口增长和人均最终需求是排放增加的主要驱动因素，人口增长对发达地区的影响更大。这些研究结果强调需要采取区域差别化政策，包括碳配额再分配、能源依赖型城市的产业转型和促进欠发达地区的绿色产业，以实现环境可持续性和经济发展之间的平衡。

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引用次数: 0

Guiding cultivar choice in smallholder agriculture: Identifying suitability hotspots for maturity groups of field crops 指导小农农业的栽培品种选择：确定大田作物成熟度组的适宜性热点

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-02-24 DOI: 10.1016/j.resenv.2025.100204

Uwe Grewer , Peter de Voil , Dilys S. MacCarthy , Daniel Rodriguez

The adoption of suitable crop cultivars is central to the sustainable intensification of smallholder cropping systems across Sub-Saharan Africa and plays a crucial role in improving smallholder incomes and food security. Breeding programmes have significantly increased the availability of early-, mid-, and late-maturing crop cultivars tailored to the Target Population of Environments in Sub-Saharan Africa. However, there is a substantial lack of data-driven maturity group recommendations at a detailed spatial scale. The absence of targeted guidance on the suitability of maturity groups limits the ability of smallholder farmers to make optimal cultivar adoption decisions. Here, we propose a framework using gridded crop modelling to identify locally relevant maturity group recommendations at a high spatial resolution for field crops. Implementing the framework for maize in Ghana, we employ the APSIM crop model across 3927 point locations and weather records for recent thirty years. We show that mid-maturing cultivars consistently provide the highest yields across all national production locations in the major growing season. In the minor growing season, we find that early- and mid-maturing cultivars provide the highest yields across distinct spatial suitability clusters. Specifically, in the minor growing season, mid-maturing cultivars provide the highest yields in high-yielding environments, while early-maturing varieties provide the highest yields in low-yielding environments. We identify specific environment-by-management combinations for which different maturity groups are optimal. The proposed framework enables the development of spatially and seasonally tailored maturity group recommendations that take advantage of prevailing genotype-by-environment-by-management interactions. The approach can readily be scaled to other crops and countries.

采用合适的作物品种是撒哈拉以南非洲地区小农种植制度可持续集约化的核心，在提高小农收入和粮食安全方面发挥着至关重要的作用。育种计划大大增加了针对撒哈拉以南非洲环境目标群体量身定制的早、中、晚熟作物品种的可得性。然而，在详细的空间尺度上，大量缺乏数据驱动的成熟度组建议。缺乏关于成熟度群体适宜性的有针对性的指导，限制了小农做出最佳品种采用决策的能力。在这里，我们提出了一个使用网格作物模型的框架，以高空间分辨率为大田作物确定当地相关的成熟度组建议。为了在加纳实施玉米框架，我们在3927个地点和近30年的天气记录中采用了APSIM作物模型。我们表明，在主要生长季节，在所有国家生产地点，中成熟品种始终提供最高的产量。在小生长期，在不同的空间适宜性集群中，早熟和早熟品种的产量最高。具体而言，在小生长期，中熟品种在高产环境下产量最高，而早熟品种在低产环境下产量最高。我们确定了特定的环境管理组合，不同的成熟度组是最优的。所提出的框架能够利用普遍存在的基因型-环境-管理相互作用，制定适合空间和季节的成熟度组建议。这种方法可以很容易地推广到其他作物和国家。

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引用次数: 0

Carbon footprint of global cotton production 全球棉花生产的碳足迹

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-03-07 DOI: 10.1016/j.resenv.2025.100214

Zhuhong Yu, Yi Yang

Cotton constitutes one-quarter of the global fiber market. With growing global attention to the carbon footprint and net-zero pathways of the fashion and textile industries, it is essential to quantify the life-cycle greenhouse gas (GHG) emissions, or carbon footprint, of cotton production and develop effective emission reduction strategies. Based on life-cycle assessment, we estimate that global GHG emissions from cotton production in 2020 amounts to approximately 63 Mt CO₂e, with substantial regional variability observed. Emissions intensity ranges from 0.3 to 1.4 t CO₂e per t of cotton produced, with an average of 0.9 t CO₂e per t or 1.9 t CO₂e per t of fiber produced. Across the countries evaluated, India has the most GHG emissions and, hence, the largest reduction potential, highlighting the need for prioritized localized strategies in that region. Nitrogen fertilizer is identified as the main driver of cotton’s carbon footprint, due to direct

N_{2}

O emissions and indirect GHG emissions from production. In some regions, phosphorus (

P_{2}

O₅) fertilizer and diesel use are also important sources of emissions. Scenario analysis indicates that cotton’s carbon footprint can be reduced by

\sim

37% through improving nitrogen use efficiency and increasing manure application, and an additional

\sim

12% reduction is possible by powering farm equipment with renewable energy. Our study provides important information for decision makers regarding how to make global cotton production more sustainable and climate friendly.

棉花占全球纤维市场的四分之一。随着全球对时尚和纺织行业碳足迹和净零排放途径的关注日益增加，量化棉花生产的生命周期温室气体（GHG）排放或碳足迹并制定有效的减排战略至关重要。基于生命周期评估，我们估计2020年棉花生产产生的全球温室气体排放量约为6300万吨二氧化碳当量，存在显著的区域差异。每生产1吨棉花，排放强度为0.3至1.4吨二氧化碳当量，每生产1吨纤维，排放强度平均为0.9吨二氧化碳当量或1.9吨二氧化碳当量。在评估的所有国家中，印度的温室气体排放量最多，因此减排潜力最大，突出表明该地区需要优先制定本地化战略。氮肥被认为是棉花碳足迹的主要驱动因素，因为生产过程中直接排放一氧化二氮和间接排放温室气体。在一些地区，磷（P2O5）肥料和柴油的使用也是重要的排放源。情景分析表明，通过提高氮利用效率和增加肥料施用，棉花的碳足迹可以减少~ 37%，通过使用可再生能源为农业设备供电，还可以减少~ 12%。我们的研究为决策者提供了关于如何使全球棉花生产更加可持续和气候友好的重要信息。

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引用次数: 0

Graph-based machine learning for high-resolution assessment of pedestrian-weighted exposure to air pollution 基于图形的机器学习，用于行人加权空气污染暴露的高分辨率评估

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-04-01 DOI: 10.1016/j.resenv.2025.100219

Feifeng Jiang , Jun Ma

Pedestrians are particularly vulnerable to air pollution due to their proximity to pollutant sources and elevated respiratory rates during physical activity, amplifying cumulative health risks. However, existing studies focus on concentration- or residence-based exposure assessment, overlooking the dynamic interaction between pollution patterns and pedestrian activity. This study therefore introduces a novel methodological framework to assess pedestrian-specific exposure to PM2.5 in diverse urban environments. Applied to New York City, the framework leverages graph-based machine learning to predict street-level PM2.5 concentrations from vehicle-sensed pollution data, while estimating high-resolution pedestrian volume derived from street view imagery and ground-truth count data. The results reveal significant divergences between traditional exposure assessments and pedestrian-specific exposure patterns, uncovering previously overlooked high-risk zones. High-exposure hotspots are not limited to areas with elevated pollution levels but also include locations where moderate pollution coincides with high pedestrian activity. This study also explores the spatial relationship between exposure patterns and urban vegetation coverage, providing actionable insights for targeted interventions. By bridging the gap between pollution dynamics and pedestrian activity, this research provides urban planners and policymakers with new insights for developing pedestrian-centered air quality management strategies, contributing to healthier and more sustainable urban environments.

行人特别容易受到空气污染的影响，因为他们靠近污染源，而且在身体活动期间呼吸频率升高，从而加大了累积的健康风险。然而，现有的研究侧重于以浓度或居住地为基础的暴露评估，忽视了污染模式与行人活动之间的动态相互作用。因此，本研究引入了一种新的方法框架来评估不同城市环境中行人对PM2.5的特定暴露。该框架应用于纽约市，利用基于图形的机器学习，从车辆感知的污染数据中预测街道PM2.5浓度，同时从街景图像和地面真实计数数据中估计高分辨率行人量。结果揭示了传统暴露评估和行人特定暴露模式之间的显著差异，揭示了以前被忽视的高风险区域。高暴露热点不仅限于污染水平高的地区，还包括中度污染与行人活动频繁的地区。本研究还探讨了暴露模式与城市植被覆盖之间的空间关系，为有针对性的干预措施提供了可操作的见解。通过弥合污染动态和行人活动之间的差距，本研究为城市规划者和决策者提供了新的见解，以制定以行人为中心的空气质量管理策略，为更健康、更可持续的城市环境做出贡献。

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引用次数: 0

Evaluation of cotton planting suitability in Xinjiang based on climate change and soil fertility factors simulated by coupled machine learning model 基于气候变化和土壤肥力因子的耦合机器学习模型模拟新疆棉花适宜性评价

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-03-06 DOI: 10.1016/j.resenv.2025.100200

Yonglin Jia , Yi Li , Asim Biswas , Jiayin Pang , Xiaoyan Song , Guang Yang , Zhen’an Hou , Honghai Luo , Xiangwen Xie , Javlonbek Ishchanov , Ji Chen , Juanli Ju , Kadambot H.M. Siddique

Cotton is the world’s most widely cultivated fiber crop and holds great significance in Xinjiang. However, unsuitable planting environments can hinder farmer income and result in a substantial waste of agricultural resources.This study explores suitability of cotton planting areas in Xinjiang to reduce agricultural inputs and pollution. The goal is to promote sustainable agricultural development by considering both climate change and soil fertility, factors often overlooked in previous research. We analyzed climate change trends in Xinjiang and used machine learning-transfer component analysis to build a transferable coupling model for total nitrogen (TN) and soil organic carbon (SOC) indicators, resulting in a cotton suitability zoning that accounts for climate and soil fertility factors. Xinjiang has seen an overall increase in cumulative temperature and rainfall, with southern Xinjiang showing the most significant rise (4.02% in temperature and 16.26% in rainfall). The random forest model (RF) outperformed multivariate linear regression (MLR) and support vector machines (SVM) in predicting soil fertility indicators (TN: R

^{2} = 0.80

, SOC: R

^{2} = 0.77

). The RF-TCA coupling model enhanced adaptability, with better performance in TN prediction compared to SOC. The Xinjiang cotton suitability zoning, based on meteorological and soil data, indicates a northward shift in suitable cotton planting areas in northern Xinjiang, while southern Xinjiang continues to maintain a substantial number of suitable planting zones. Notably, the disparity in suitability between the two regions has been narrowing over time. The research offers valuable insights for optimizing cotton planting locations, enhancing resource efficiency, and promoting sustainable development in Xinjiang.

棉花是世界上种植最广泛的纤维作物，在新疆具有重要意义。然而，不适宜的种植环境会阻碍农民的收入，并导致农业资源的大量浪费。本研究探讨了新疆棉花种植区在减少农业投入和污染方面的适宜性。目标是通过考虑气候变化和土壤肥力来促进可持续农业发展，这两个因素在以前的研究中经常被忽视。通过对新疆气候变化趋势的分析，利用机器学习-迁移成分分析，建立了全氮（TN）和土壤有机碳（SOC）指标的可迁移耦合模型，得到了考虑气候和土壤肥力因素的棉花适宜性分区。新疆累计气温和降雨量总体上升，其中南疆增幅最大，累计气温上升4.02%，累计降雨量上升16.26%。随机森林模型（RF）对土壤肥力指标的预测效果优于多元线性回归（MLR）和支持向量机（SVM）（TN: R2=0.80, SOC: R2=0.77）。RF-TCA耦合模型增强了自适应能力，在TN预测方面优于SOC。基于气象和土壤资料的新疆棉花适宜性区划表明，北疆适宜种植面积向北转移，南疆适宜种植面积继续保持较大数量。值得注意的是，随着时间的推移，两个地区在适宜性方面的差距一直在缩小。该研究为优化棉花种植区位、提高资源利用效率、促进新疆可持续发展提供了有价值的见解。

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引用次数: 0

A life cycle thinking-based environmental risk framework for screening sustainable feedstocks in early-stage bioeconomy projects 基于生命周期思维的早期生物经济项目可持续原料筛选环境风险框架

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-02-20 DOI: 10.1016/j.resenv.2025.100201

George Bishop , Carmen Girón-Domínguez , James Gaffey , Maeve Henchion , Réamonn Fealy , Jesko Zimmermann , Wriju Kargupta , David Styles

Understanding the environmental impacts of bio-based feedstock production is essential for sustainable bioeconomy development. Consequential life cycle assessment (LCA) evaluates environmental sustainability, often identifying “hidden” impacts incurred through market displacements. However, it is often impractical to screen multiple bioeconomy feedstocks and value chains using full consequential LCA early in project conceptualisation, owing to high requirements in terms of time, data, and expertise. As a result, critical environmental risks may not be discovered until too late in project development to redirect investment towards more sustainable options. This paper introduces the Bio-based feedstock Environmental Risk Assessment (Bio-ERA) Framework, designed to support early screening of potential upstream environmental risks associated with increased demand for bio-based feedstocks. The Bio-ERA Framework comprises a decision tree that systematically guides stakeholders through consequential life cycle thinking, elucidating sometimes hidden (indirect) pathways of impact among feedstock sourcing decisions. Seven important environmental aspects are addressed: Finite Resource Inputs, Greenhouse Gas (GHG) Emissions, Air Quality, Water Quality, Ecosystem Diversity, Terrestrial Carbon Storage, and Indirect Land Use Change. Criteria are proposed to structure evaluation of (i) probability and (ii) severity of environmental impact, in relation to four categories of feedstock: primary (determining product), high-value by-product, low-value by-product, and waste. Example applications demonstrate how the framework can generate an environmental risk profile for specific feedstocks sourced in specific contexts. Bio-ERA does not avoid the need for detailed LCA evaluation of full bioeconomy value chains, but promotes deeper interrogation and awareness of potential environmental risks associated with feedstock sourcing, in a manner that is accessible to all stakeholders. This could support earlier screening of strategic investment decisions necessary to develop a sustainable bioeconomy.

了解生物基原料生产对环境的影响对可持续生物经济发展至关重要。后续生命周期评估（LCA）评估环境的可持续性，通常识别由市场置换引起的“隐藏”影响。然而，由于在时间、数据和专业知识方面的高要求，在项目概念化的早期使用完整的相应LCA筛选多种生物经济原料和价值链通常是不切实际的。因此，在项目开发过程中发现严重的环境风险可能为时已晚，无法将投资转向更可持续的选择。本文介绍了生物基原料环境风险评估（Bio-ERA）框架，旨在支持早期筛选与生物基原料需求增加相关的潜在上游环境风险。Bio-ERA框架包括一个决策树，系统地指导利益相关者通过相应的生命周期思维，阐明原料采购决策中有时隐藏的（间接的）影响途径。七个重要的环境方面：有限资源投入、温室气体（GHG）排放、空气质量、水质、生态系统多样性、陆地碳储量和间接土地利用变化。针对四类原料（主要（决定产品）、高价值副产品、低价值副产品和废物），提出了对(i)环境影响的可能性和（ii）严重程度进行结构评估的标准。示例应用程序演示了该框架如何为来自特定环境的特定原料生成环境风险概况。Bio-ERA并没有避免对整个生物经济价值链进行详细的LCA评估的需要，而是以所有利益相关者都可以访问的方式，促进对与原料采购相关的潜在环境风险的更深入的询问和认识。这可以支持早期筛选发展可持续生物经济所需的战略投资决策。

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引用次数: 0

Enhancement joint fertilization efficacy of straw and nitrogen fertilizer on soil quality and seedcotton yield for sustainable cotton farming 提高秸秆与氮肥联合施肥对土壤质量和籽棉产量的影响，实现棉花可持续种植

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-03-30 DOI: 10.1016/j.resenv.2025.100218

Qiang Li , Zhitao Liu , Li’an Wang, Ying Zhang, Mengyao Guo, Wen Jin, Wei Hu, Yali Meng, Haishui Yang, Zhiguo Zhou

Straw return with optimizing nitrogen fertilizer is an important way to achieve sustainable cotton farming. However, quantitative analysis of joint fertilization efficacy (JFE) of straw return and nitrogen fertilizer on soil quality and seedcotton yield remains uncertain. Herein, based on a 7-year field experiment, we evaluated the dynamic characteristics of JFE of straw return and nitrogen rates (75, 150 and 300 kg N ha⁻¹, denote as N75, N150 and N300, respectively) on soil quality index (JFE-SQI) and seedcotton yield (JFE-Y) in a cotton–wheat cropping system of East China. The results showed that straw return with moderate nitrogen rate (i.e.N150) improved soil quality by reducing bulk density, increasing soil carbon and nitrogen sequestration, promoting nutrient availability, stimulating microbial growth and enhancing soil enzyme activities, thereby improving seedcotton yield and its stability. Straw return with N150 could also achieve higher JFE-SQI and JFE-Y synergistically. Meanwhile, JFE-SQI and JFE-Y at N150 had a synergistic effect (JFE > 10%) in the first 5 year while a summing effect (−10%

\leq

JFE

\leq

10%) from the sixth year. And the highest JFE-Y could be reached when moderate JFE-SQI was achieved, indicating that there was a nitrogen-driven tradeoff between JFE-SQI and JFE-Y. Moreover, Climatic factor exerted a significant contribution to seedcotton yield and JFE-Y. In conclusion, reasonable straw return and nitrogen fertilizer management strategy is an effective way to realize sustainable cotton planting under the global climate change.

秸秆还田配氮肥优化是实现棉花可持续生产的重要途径。然而，秸秆还田与氮肥联合施肥对土壤质量和籽棉产量的定量分析仍不确定。基于7年的大田试验，研究了秸秆还田和施氮量（分别为75、150和300 kg N ha−1，分别为N75、N150和N300）对华东棉麦种植体系土壤质量指数（JFE- sqi）和籽棉产量（JFE- y）的动态特征。结果表明，中等施氮量（即n150）秸秆还田可通过降低容重、增加土壤固碳和固氮、促进养分有效性、刺激微生物生长和提高土壤酶活性等方式改善土壤质量，从而提高棉籽产量及其稳定性。秸秆还田N150也能协同提高JFE-SQI和JFE-Y。同时，N150时JFE- sqi和JFE- y具有协同效应(JFE >；前5年为10%)，第6年为累加效应（- 10%≤JFE≤10%）。当JFE-SQI适中时，JFE-Y最高，说明JFE-SQI和JFE-Y之间存在氮驱动的权衡。此外，气候因子对籽棉产量和JFE-Y均有显著影响。综上所述，合理的秸秆还田和氮肥管理策略是在全球气候变化下实现棉花可持续种植的有效途径。

{"title":"Enhancement joint fertilization efficacy of straw and nitrogen fertilizer on soil quality and seedcotton yield for sustainable cotton farming","authors":"Qiang Li , Zhitao Liu , Li’an Wang, Ying Zhang, Mengyao Guo, Wen Jin, Wei Hu, Yali Meng, Haishui Yang, Zhiguo Zhou","doi":"10.1016/j.resenv.2025.100218","DOIUrl":"10.1016/j.resenv.2025.100218","url":null,"abstract":"<div><div>Straw return with optimizing nitrogen fertilizer is an important way to achieve sustainable cotton farming. However, quantitative analysis of joint fertilization efficacy (JFE) of straw return and nitrogen fertilizer on soil quality and seedcotton yield remains uncertain. Herein, based on a 7-year field experiment, we evaluated the dynamic characteristics of JFE of straw return and nitrogen rates (75, 150 and 300 kg N ha<sup>−1</sup>, denote as N75, N150 and N300, respectively) on soil quality index (JFE-SQI) and seedcotton yield (JFE-Y) in a cotton–wheat cropping system of East China. The results showed that straw return with moderate nitrogen rate (i.e.N150) improved soil quality by reducing bulk density, increasing soil carbon and nitrogen sequestration, promoting nutrient availability, stimulating microbial growth and enhancing soil enzyme activities, thereby improving seedcotton yield and its stability. Straw return with N150 could also achieve higher JFE-SQI and JFE-Y synergistically. Meanwhile, JFE-SQI and JFE-Y at N150 had a synergistic effect (JFE > 10%) in the first 5 year while a summing effect (−10% <span><math><mo>≤</mo></math></span> JFE <span><math><mo>≤</mo></math></span> 10%) from the sixth year. And the highest JFE-Y could be reached when moderate JFE-SQI was achieved, indicating that there was a nitrogen-driven tradeoff between JFE-SQI and JFE-Y. Moreover, Climatic factor exerted a significant contribution to seedcotton yield and JFE-Y. In conclusion, reasonable straw return and nitrogen fertilizer management strategy is an effective way to realize sustainable cotton planting under the global climate change.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"20 ","pages":"Article 100218"},"PeriodicalIF":12.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143791349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is ‘local food’ best? Evaluating agricultural greenhouses in Switzerland as an alternative to imports for reducing carbon footprint “本地食物”最好吗？评估瑞士的农业温室作为减少碳足迹的进口替代方案

IF 12.4 Q1 ENVIRONMENTAL SCIENCES

Resources Environment and Sustainability

Pub Date : 2025-06-01 Epub Date: 2025-03-07 DOI: 10.1016/j.resenv.2025.100209

Vanessa Burg , Hamidreza Solgi , Farzaneh Rezaei , Stephan Pfister , Ramin Roshandel , Stefanie Hellweg

Sustainable agricultural practices are essential to mitigate environmental impacts. Greenhouse cultivation offers potential solutions for enhancing crop yields and reducing the impacts on land and water resources. However, reliance on fossil-based heating systems poses challenges regarding carbon footprint. This study provides a comparative life cycle assessment (LCA) of the carbon and water footprints of imported and locally produced greenhouse crops in Switzerland, considering the local climatic conditions and the predominant production systems in different regions. The findings reveal that the carbon footprint is primarily driven by heating, supplementary lighting, and CO₂ fertilization, while transportation emissions are relatively minor. A key insight is that using waste heat for greenhouse heating in Switzerland can reduce the carbon footprint to less than one-third (e.g., 0.6 CO₂-eq/kg for tomatoes) compared to local natural-gas-based heating systems. However, imports from warmer locations still show a slightly lower carbon footprint (0.4-0.5 CO₂-eq/kg) due to the absence of heating, lighting, and CO₂ enrichment, but often come with trade-offs concerning the water footprint. Seasonal variations also strongly influence the carbon footprint: early winter cultivation can result in up to five times higher carbon footprint than summer cultivation, while waste-heat systems reduce but do not eliminate this effect. These findings highlight the potential of waste-heat-based greenhouses as a lower-carbon alternative to fossil-fueled domestic production and imports from less favorable climates while underscoring the environmental benefits of seasonal diets.

可持续农业做法对减轻环境影响至关重要。温室栽培为提高作物产量和减少对土地和水资源的影响提供了潜在的解决方案。然而，对化石燃料供暖系统的依赖带来了碳足迹方面的挑战。考虑到当地气候条件和不同地区的主要生产系统，本研究对瑞士进口和本地生产的温室作物的碳和水足迹进行了比较生命周期评估（LCA）。研究结果表明，碳足迹主要由供暖、补充照明和二氧化碳施肥驱动，而交通排放相对较小。一个关键的见解是，与当地的天然气供暖系统相比，在瑞士使用废热为温室供暖可以将碳足迹减少到不到三分之一（例如，西红柿每公斤0.6二氧化碳当量）。然而，由于缺乏供暖、照明和二氧化碳富集，从较温暖地区进口的碳足迹仍略低（0.4-0.5 CO2当量/kg），但往往需要在水足迹方面进行权衡。季节变化也对碳足迹产生强烈影响：早冬栽培的碳足迹可能比夏季栽培高出5倍，而废热系统减少但不能消除这种影响。这些发现强调了废热温室作为化石燃料国内生产和从不太有利气候进口的低碳替代品的潜力，同时强调了季节性饮食的环境效益。

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引用次数: 0