Assessment of rural sustainable development and analysis and prediction of obstacles and coupled coordinated development:A case study of Zaozhuang City

In China,the Innovation Demonstration Zone for the National Sustainable Development Agenda is a key initiative for executing the United Nations(UN)2030 Agenda for Sustainable Development.The Zone also plays critical roles in addressing the developmental bottlenecks that China faces and sharing Chinese insights into global sustainable development efforts.On July 15,2022,the State Council endorsed the Zone’s establishment in Zaozhuang City,Shandong Province,where it focuses on innovation-led sustainable development in rural areas.Research into the levels,impediments,interdependencies,and evolutionary trends of rural sustainable development is crucial.Therefore,this research aimed to assist in comprehensively assessing developmental challenges and facilitating the harmonious advancement of social,economic,and environmental aspects in rural areas.In pursuit of the three fundamental dimensions of the UN’s Sustainable Development Goals(SDGs),namely development’s drivers,quality,and equity,this study was grounded in China’s national Rural Revitalization Strategy and the demands of sustainable development strategies.It also aligns with the UN 2030 Agenda for Sustainable Development and the associated SDG indicators.Focusing on four key areas,namely production elements,natural elements,social elements,and rural governance,this study developed an evaluation index system for assessing the level of rural sustainable development.It employed a range of analytical models,including the game theory-based combination empowerment method,barrier degree model,coupling degree model,coupling coordination degree model,and gray prediction GM(1,1)model,to analyze the status and evolving trends of rural sustainable development in Zaozhuang City from 2015 to 2022.The key findings were as follows:①Relative to the baseline year 2015,the sustainable development level in Zaozhuang’s rural areas has shifted toward an improved state overall.②The primary barrier to achieving rural sustainable development in Zaozhuang is the city’s rural governance system.③While the components of rural sustainable development in Zaozhuang are in the early stages of both basic and moderate coordination,an overall enhancement has occurred in their integrative coordination.④Between 2023 and 2025,the level of integrative coordination in Zaozhuang is expected to rise steadily.However,reaching a state of advanced coordination will require additional time for development.

Constructing a standard system of city sustainable development assessment technology based on the SDGs

Given the rapid development of China’s new urbanization,cities with different locations and varying functional positioning,resource endowments,and development stages have insufficient scientific and applicable technical tools for implementing the United Nations Sustainable Development Goals(SDGs).City managers and policymakers must urgently establish SDG benchmarks to diagnose city development.Moreover,successful experiences from similar cities regarding sustainable development and self-improvement must be learned from to promote diversified,sustainable development across the country.Furthermore,emerging technologies such as artificial intelligence,the Internet of Things,big data and 5G are widely used in smart cities.Therefore,there is a growing need for“knowledge-based,personalized and intelligent”technologies to support monitoring,evaluation,and decision-making processes facilitating sustainable development in cities.This paper uses standardization as the theoretical support and technical basis.This approach can help clarify the sustainable development processes in China and clarify the evaluation results of and provide data on horizontal city comparisons,which can be used to develop evaluation technology for sustainable development in cities and construct a standardized system.The results provide a standard framework for intelligent assessment and decision-making regarding cities’sustainable development capabilities in China.Evaluating major international standardization institutions reveals that the practices of Chinese national standards should be fully absorbed and integrated to guide the evaluation of smart,resilient,and low-carbon cities.To this end,an indicator library of city sustainable development is proposed to provide standard evaluation technology methods.Finally,analyzing the response relationship of the indicator library to SDGs reveals the need for a standardized knowledge map of sustainable development assessment techniques and methods from the perspective of integrated management for sustainable development in cities.

Development of Sustainable Urban-Rural Integration:Dongtan Case Study

The environmental impact issues,such as global warming and expansion of the urban zone,seem more serious and have become the biggest defining challenges of the 21st century.Climate change can lead to water shortages,desertification,land degradation,air pollution,rising sea levels,accelerated deforestation,and exacerbated economic pressures.Global urban growth greatly impacts changes in sociability,humanity,and the environment of the Earth.The human presence,especially in cities,seriously affects resource use and waste disposal,and they are consuming natural resources faster than the planet can sustain during urbanization,changing how people live.China,with a population of 1.3 billion,has seen tens of millions of people living in the countryside migrate to cities,especially megacities,since the 1980s.As a result of its decision to industrialize and urbanize to boost the economy,China has become the world’s second-largest consumer of energy.In recent years,China’s government has quickly recognized the lessons of“limits to growth”and has taken action by initiating the construction process in Dongtan,Shanghai,China.They are making efforts to build urban-rural integration communities to promote sustainable development.Based on a literature review focusing on Dongtan,research questions are raised according to the research objective:(1)What are the challenges of sustainable development in urban-rural integration?(2)What practices has Dongtan implemented for sustainable development,or how is sustainable development being applied to Dongtan?(3)What are the social,political,environmental,and economic concerns regarding the sustainable development of Dongtan?The sustainable urban-rural integration concerns the ecological,economic,environmental,and psychological aspects of urban-rural integration design and management.The overall objective is to promote sustainable development in economic,social,ecological,and spatial dimensions.It will be a liveable,complete community that makes economic,environmental,and social sense locally while also contributing to national and global sustainable development.It will serve as a compelling model for how to build sustainable urban-rural integration worldwide.

Nano/Micro-Structural Supramolecular Biopolymers: Innovative Networks with the Boundless Potential in Sustainable Agriculture

Sustainable agriculture plays a crucial role in meeting the growing global demand for food while minimizing adverse environmental impacts from the overuse of synthetic pesticides and conventional fertilizers.In this context,renewable biopolymers being more sustainable offer a viable solution to improve agricultural sustainability and production.Nano/micro-structural supramolecular biopolymers are among these innovative biopolymers that are much sought after for their unique features.These biomaterials have complex hierarchical structures,great stability,adjustable mechanical strength,stimuli-responsiveness,and self-healing attributes.Functional molecules may be added to their flexible structure,for enabling novel agricultural uses.This overview scrutinizes how nano/micro-structural supramolecular biopolymers may radically alter farming practices and solve lingering problems in agricultural sector namely improve agricultural production,soil health,and resource efficiency.Controlled bioactive ingredient released from biopolymers allows the tailored administration of agrochemicals,bioactive agents,and biostimulators as they enhance nutrient absorption,moisture retention,and root growth.Nano/micro-structural supramolecular biopolymers may protect crops by appending antimicrobials and biosensing entities while their eco-friendliness supports sustainable agriculture.Despite their potential,further studies are warranted to understand and optimize their usage in agricultural domain.This effort seeks to bridge the knowledge gap by investigating their applications,challenges,and future prospects in the agricultural sector.Through experimental investigations and theoretical modeling,this overview aims to provide valuable insights into the practical implementation and optimization of supramolecular biopolymers in sustainable agriculture,ultimately contributing to the development of innovative and eco-friendly solutions to enhance agricultural productivity while minimizing environmental impact.

Sustainable Mining in the Era of Artificial Intelligence

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

‘Jelly to Joule’:Direct laser writing of sustainable jellyfish-based ‘graphenic silicon’ anodes for environmentally remediating high-performance lithium-ion batteries

The ramifications of global climate change and resource scarcities have made it imperative to re-examine the definition of sustainable energy-storage systems.It is crucial to recognize that not all renewable resources are inherently sustainable,and their full impact on the environment must be assessed.With the proliferation of invasive jellyfish species wreaking havoc on marine ecosystems and economies worldwide,utilizing overabundant jellyfish as a carbon source presents an opportunity to create energy-storage systems that are both financially beneficial and environmentally remediating.Accordingly,a comprehensive approach to sustainability also requires eco-friendly solutions throughout the entire lifecycle,from material sourcing to battery production,without compromising highperformance requirements.Currently,most electrode syntheses for lithium-ion batteries(LIBs) employed are energy-intensive,multiple-steps,complex,and additive-heavy.In response,this work pioneers the straightforward use of low-energy laser irradiation of a jellyfish biomass/silicon nanoparticle blend to encapsulate the silicon nanoparticles in-situ within the as-forming conductive carbonized matrix,creating sustainable and additive-free composite anodes.The self-standing anode is directly synthesized under ambient conditions and requires no post-processing.Here,a laser-synthesized conductive threedimensional porous carbon/silicon composite anode from raw jellyfish biomass for LIBs is presented,displaying outstanding cyclic stability(>1000 cycles),excellent capacity retention(>50% retention after1000 cycles),exceptional coulombic efficiency(>99%),superb reversible gravimetric capacity(>2000 mAh/g),and high rate performance capability(>1.6 A/g),paving a new path to future sustainable energy production.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China

Upland crop-rice cropping systems(UCR)facilitate sustainable agricultural intensification.Accurate UCR cultivation mapping is needed to ensure food security,sustainable water management,and rural revitalization.However,datasets describing cropping systems are limited in spatial coverage and crop types.Mapping UCR is more challenging than crop identification and most existing approaches rely heavily on accurate phenology calendars and representative training samples,which limits its applications over large regions.We describe a novel algorithm(RRSS)for automatic mapping of upland crop-rice cropping systems using Sentinel-1 Synthetic Aperture Radar(SAR)and Sentinel-2 Multispectral Instrument(MSI)data.One indicator,the VV backscatter range,was proposed to discriminate UCR and another two indicators were designed by coupling greenness and pigment indices to further discriminate tobacco or oilseed UCR.The RRSS algorithm was applied to South China characterized by complex smallholder rice cropping systems and diverse topographic conditions.This study developed 10-m UCR maps of a major rice bowl in South China,the Xiang-Gan-Min(XGM)region.The performance of the RRSS algorithm was validated based on 5197 ground-truth reference sites,with an overall accuracy of 91.92%.There were7348 km^(2) areas of UCR,roughly one-half of them located in plains.The UCR was represented mainly by oilseed-UCR and tobacco-UCR,which contributed respectively 69%and 15%of UCR area.UCR patterns accounted for only one-tenth of rice production,which can be tripled by intensification from single rice cropping.Application to complex and fragmented subtropical regions suggested the spatiotemporal robustness of the RRSS algorithm,which could be further applied to generate 10-m UCR datasets for application at national or global scales.

Artificial Intelligence Prediction of One-Part Geopolymer Compressive Strength for Sustainable Concrete

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part geopolymer.However,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported.Therefore,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part geopolymer.The database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing temperature.The performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed GEP.Sensitivity and parametric analysis were also performed to identify the significant contributor to strength.According to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 days.The water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

Sustainable land management in Mali

This study uses logistic and Poisson regression models to examine the factors influencing the adoption of sustain-able land management(SLM)practices in Mali using two rounds of the nationally representative survey Enquête Agricole de Conjoncture Intégrée aux Conditions de Vie des Ménages.The SLMs considered include the applica-tion of organic fertilizers,the application of inorganic fertilizers,the use of improved seeds,and the practice of intercropping.On average the application of organic fertilizers(39.2%),and inorganic fertilizers(28.7%)are the most frequent SLM practices among Malian farmers,and between 2014 and 2017,we observe a decline in the practice of intercropping.The regression results show that farmers’adoption of different SLMs is significantly associated with biophysical factors(average temperature,climate type,plot size,plot shape,and location),de-mographic factors(age,gender,education,household size),and socioeconomic factors(number of cultivated plots,livelihood diversification,type of crop grown,market access,credit access,economic shocks,and social capital).Our findings suggest that policymakers and agricultural development agencies in Mali need to adopt a multidimensional policy framework to unlock the untapped potential of SLM practices in promoting sustainable agriculture and food security.

Identifying influencing factors and characterizing key issues in urban sustainable development capacity through machine learning

In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda(IDZSDAs),combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity(USDC).After obtaining USDC assessment results through the assessment system,an approach combining Least Absolute Shrinkage and Selection Operator(LASSO)regression and Random Forest(RF)based on machine learning is proposed for identifying influencing factors and characterizing key issues.Combining Coupling Coordination Degree(CCD)analysis,the study further summarizes the systemic patterns and future directions of urban sustainable development.A case study on the IDZSDAs from 2015 to 2022 reveals that:(1)the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process;(2)the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities;and(3)the machine learning-based combined recognition method is scalable and dynamic.It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.

Sustainable Intensification and Large-scale Operation of Cultivated Land Use at the Farmers’ Scale:A Case Study of Shandong Province,China

Sustainable intensification of cultivated land use(SICLU) and large-scale operations(LSO) are widely acknowledged strategies for enhancing agricultural performance.However,the existing literature has faced challenges in precisely defining SICLU and constructing comprehensive indicators,which has hindered the exploration of factors influencing LSO within the SICLU framework.To address this gap,we integrated self-efficacy theory into the design of an index framework for evaluating SICLU.We subsequently employed econometric models to analyze the significant factors that impact LSO.Our findings reveal that SICLU can be divided into four key dimensions:intensive management,efficient output,resource conservation,and ecological environment optimization.Furthermore,it is crucial to incorporate belief-based cognitive factors into the index system,as farmers’ understanding of fertilizer and pesticide application significantly influences their willingness to engage in LSO.Moreover,we identify grain market turnover as the most influential factor in promoting LSO,with single-factor contribution rates reaching 70.9% for cultivated land transfer willingness and 62.5% for the total planting areas.Interestingly,unlike irrigation and agricultural machinery inputs,increased labor inputs correspond to larger planting areas for farmers.This trend may be attributed to reduced labor availability because of rural labor migration,whereas the reduction in irrigation and agricultural input is contingent on innovations in production practices and the transfer of cultivated land management rights.Importantly,SICLU dynamically influences LSO,with each index related to SICLU having an optimal range that fosters LSO.These insights offer valuable guidance for policymakers,emphasizing farmers as their central focus,with the adjustment of input and output factors as a means to achieve LSO as the ultimate goal.In conclusion,we propose research avenues for further enriching the SICLU framework to ensure that it aligns with the specific characteristics of regional agricultural development.

Scientific principles for accelerating the Sustainable Development Goals

The Sustainable Development Goals(SDGs)are significantly off-course as we reach the midpoint of their 2030 deadline.From a scientific perspective,the critical challenge in achieving the SDGs lies in the need for more scientific principles to understand the complex socio-ecological systems(SES)and their interactions influencing the 17 SDGs.Here,we propose a scientific framework to clarify the common scientific principles and the rational treatment of diversity under these principles.The framework’s core is revealing the complex mechanisms underlying the achievement of each Sustainable Development Goal(SDG)and SDG interactions.Building upon the identified mechanisms,complex SES models can be established,and the implementation of SDGs can be formulated as a multi-objective optimization problem,seeking a compromise in competition between essential costs and desired benefits.Our framework can assist countries,and even the world in accelerating progress towards the SDGs.

Knowledge mapping of research on sustainable utilization of landscape resources:a case study of Guilin National Innovation Demonstration Zone for sustainable development in China

Worldwide interest has increasingly focused on the sustainable utilization of landscape as a resource in urban areas,emphasizing its ecological,cultural and social significance.This study examines Guilin City,China,as a representative case study due to its rich landscape resources and status as a national innovation demonstration zone for implementing the 2030 Agenda for Sustainable Development.This study uses bibliometric visualization tools like CiteSpace and VOSviewer to analyze research trends from 1980 to 2021 in the Chinese Academic Journal Network Publishing Database(CNKI).The results show increasing academic interest over three stages:initiation(1982-1997),exploration(1998-2004),and diversified development(2005-2021).Contributions are predominantly from local academic and tourism sectors,indicating a strong regional influence;however,relatively weak interinstitutional collaboration occurs,suggesting potential for more integrated research efforts.Primary research is also concentrated within economic disciplines,particularly tourism-related ones.The evolution of research frontiers reveals three main paths:urban development strategies,industrial economic theories and empirical validation,and ecosystem analysis and evaluation.A multidisciplinary approach and stronger collaborative efforts are crucial to enhance research on ecological values and empirical models while supporting evidence-based urban development strategies in Guilin City and comparable cities globally.

Promoting sustainable consumption and circular economy:the intention of Vietnamese youth consumers to purchase products made from recycled plastics

Recycling is viewed as a key component in a circular economy and serves as an ideal solution for promoting sustainability.During the global plastic crisis,plastic recycling practices have been adopted worldwide,leading to the production of various products made from recycled plastics(PRP).Nevertheless,a gap persists between consumption and demand for such products,which is primarily attributed to a lack of comprehension from the consumer perspective.Given the pivotal role consumers play in the adoption of these products,this study explores consumers’intentions to purchase PRP.This is particularly significant in Vietnam,which is an emerging economy aspiring to achieve the objectives of a circular economy and sustainable development.Utilizing an integrated cognitive-emotional framework comprising the Valence Theory and the Norm Activation Model,data from 564 Vietnamese students were gathered and analyzed using structural equation modeling.The results show that awareness of consequences is a major driver of consumer purchase intentions,followed by perceived ease of application and monetary incentives.The results also indicate that health concerns have the strongest effect on purchase intention and in the negative side,meaning that the health-related risk is the primary concern for consumers during the decision-making process.This research holds substantial value for academics and managers,as it aids in the theoretical exploration and the formulation of strategies to improve consumer acceptance of PRP.

Spatial differences of Sustainable Development Goals(SDGs)among counties(cities)on the northern slope of the Kunlun Mountains

The county(city)located on the northern slope of the Kunlun Mountains is the primary area to solidify and extend the success of Xinjiang Uygur Autonomous Region,China in poverty alleviation.Its Sustainable Development Goals(SDGs)are intertwined with the concerted economic and social development of Xinjiang and the objective of achieving shared prosperity within the region.This study established a sustainable development evaluation framework by selecting 15 SDGs and 20 secondary indicators from the United Nations’SDGs.The aim of this study is to quantitatively assess the progress of SDGs at the county(city)level on the northern slope of the Kunlun Mountains.The results indicate that there are substantial variations in the scores of SDGs among the nine counties and one city located on the northern slope of the Kunlun Mountains.Notable high scores of SDGs are observed in the central and eastern regions,whereas lower scores are prevalent in the western areas.The scores of SDGs,in descending order,are as follows:62.22 for Minfeng County,54.22 for Hotan City,50.21 for Qiemo County,42.54 for Moyu County,41.56 for Ruoqiang County,41.39 for Qira County,39.86 for Lop County,38.25 for Yutian County,38.10 for Pishan County,and 36.87 for Hotan County.The performances of SDGs reveal that Hotan City,Lop County,Minfeng County,and Ruoqiang County have significant sustainable development capacity because they have three or more SDGs ranked as green color.However,Hotan County,Moyu County,Qira County,and Yutian County show the poorest performance,as they lack SDGs with green color.It is important to establish and enhance mechanisms that can ensure sustained income growth among poverty alleviation beneficiaries,sustained improvement in the capacity of rural governance,and the gradual improvement of social security system.These measures will facilitate the effective implementation of SDGs.Finally,this study offers a valuable support for governmental authorities and relevant departments in their decision-making processes.In addition,these results hold significant reference value for assessing SDGs at the county(city)level,particularly in areas characterized by low levels of economic development.

Role of self-help groups on socioeconomic development and the achievement of Sustainable Development Goals(SDGs)among rural women in Cooch Behar District,India

This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United Nations.In this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in SHGs.The survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey form.The results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test results.Memberships in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and 5.This study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ventures.Moreover,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural women.Finally,doing so enabled them to move more freely for work and other activities and to make family and common decisions.

A cross-cultural study of sustainable nutrition and its environmental impact in Asia and Europe:A comparison of China and Germany

Global challenges such as climate change,biodiversity loss,and health crises necessitate a shift towards sustainable diets.Incorporating sustainability into food-based dietary guidelines(FBDGs)is essential for this shift,and cultural considerations also play a vital role,as food culture significantly influences dietary habits.Considering that Asia and Europe exhibit distinct food cultures,tailored approaches are necessary.Additionally,countries face diverse nutritional challenges,ranging from malnutrition to diet-related diseases,and regional variation in environmental impact necessitates context-specific strategies.Achieving sustainable nutrition depends on understanding cultural influences and regional dynamics.This paper compares China’s and Germany’s dietary guidelines and dietary patterns and their impact on sustainability.It shows that Chinese and German FBDGs only slightly differ,despite the different eating cultures and habits of each country.Alone the recommended amounts for eggs and fish are considerably higher in China than in Germany.However,in both China and Germany,actual dietary patterns deviate from the dietary guidelines.In China,concomitant with economic growth and urbanization,a dietary shift towards increased consumption of animal products and decreased consumption of vegetables and cereals has been observed in the last decades,which has led to a decline in nutritional deficiencies but an increase in obesity and overweight.Obesity and overweight are also on the rise in Germany.A dietary shift could therefore also be beneficial for public health.While following the respective national guidelines would benefit the environment,alternative diets such as a plant-based diet offer even lower environmental footprint.Revising guidelines to prioritize sustainability in addition to health aspects while considering regional contexts and cultural preferences is recommended to foster sustainable eating habits globally.This approach is pivotal for promoting dietary shift towards sustainability on a global scale.

Potentials and Challenges of Carbon Knowledge Graph in Sustainable Textile Production for Carbon Traceability:A Review

Textile production has received considerable attention owing to its significance in production value,the complexity of its manufacturing processes and the extensive reach of its supply chains.However,textile industry consumes substantial energy and materials and emits greenhouse gases that severely harm the environment.In addressing this challenge,the concept of sustainable production offers crucial guidance for the sustainable development of the textile industry.Low-carbon manufacturing technologies provide robust technical support for the textile industry to transition to a low-carbon model by optimizing production processes,enhancing energy efficiency and minimizing material waste.Consequently,low-carbon manufacturing technologies have gradually been implemented in sustainable textile production scenarios.However,while research on low-carbon manufacturing technologies for textile production has advanced,these studies predominantly concentrate on theoretical methods,with relatively limited exploration of practical applications.To address this gap,a thorough overview of carbon emission management methods and tools in textile production,as well as the characteristics and influencing factors of carbon emissions in key textile manufacturing processes is presented to identify common issues.Additionally,two new concepts,carbon knowledge graph and carbon traceability,are introduced,offering strategic recommendations and application directions for the low-carbon development of sustainable textile production.Beginning with seven key aspects of sustainable textile production,the characteristics of carbon emissions and their influencing factors in key textile manufacturing process are systematically summarized.The aim is to provide guidance and optimization strategies for future emission reduction efforts by exploring the carbon emission situations and influencing factors at each stage.Furthermore,the potential and challenges of carbon knowledge graph technology are summarized in achieving carbon traceability,and several research ideas and suggestions are proposed.