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.

Recycled graphite for more sustainable lithium-ion batteries

The demand for lithium-ion batteries(LIBs)is driven largely by their use in electric vehicles,which is projected to increase dramatically in the future.This great success,however,urgently calls for the efficient recycling of LIBs at the end of their life.Herein,we describe a froth flotation-based process to recycle graphite—the predominant active material for the negative electrode—from spent LIBs and investigate its reuse in newly assembled LIBs.It has been found that the structure and morphology of the recycled graphite are essentially unchanged compared to pristine commercial anode-grade graphite,and despite some minor impurities from the recycling process,the recycled graphite provides a remarkable reversible specific capacity of more than 350 mAh g^(−1).Even more importantly,newly assembled graphite‖NMC532 cells show excellent cycling stability with a capacity retention of 80%after 1000 cycles,that is,comparable to the performance of reference full cells comprising pristine commercial graphite.

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.

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.

Phytoremediation Strategies for Heavy Metal Contamination: A Review on Sustainable Approach for Environmental Restoration

Current globalization trends and important breakthroughs globally need a complete study of heavy metal contamination, its causes, its impacts on human and environmental health, and different remediation strategies. Heavy metal pollution is mostly produced by urbanization and industry, which threatens ecosystems and human health. Herein, we discuss a sustainable environmental restoration strategy employing phytoremediation for heavy metal pollution, the carcinogenic, mutagenic, and cytotoxic effects of heavy metals such as cadmium, copper, mercury, selenium, zinc, arsenic, chromium, lead, nickel, and silver, which may be fatal. Phytoremediation, which was prioritized, uses plants to remove, accumulate, and depollute pollutants. This eco-friendly method may safely collect, accumulate, and detoxify toxins using plants, making it popular. This study covers phytostabilization, phytodegradation, rhizodegradation, phytoextraction, phytovolatilization, and rhizofiltration. A phytoremediation process’s efficiency in varied environmental circumstances depends on these components’ complex interplay. This paper also introduces developing phytoremediation approaches including microbe-assisted, chemical-assisted, and organic or bio-char use. These advancements attempt to overcome conventional phytoremediation’s limitations, such as limited suitable plant species, location problems, and sluggish remediation. Current research includes machine learning techniques and computer modeling, biostimulation, genetic engineering, bioaugmentation, and hybrid remediation. These front-line solutions show that phytoremediation research is developing towards transdisciplinary efficiency enhancement. We acknowledge phytoremediation’s promise but also its drawbacks, such as site-specific variables, biomass buildup, and sluggish remediation, as well as ongoing research to address them. In conclusion, heavy metal pollution threatens the ecology and public health and must be reduced. Phytoremediation treats heavy metal pollution in different ways. Over time, phytoremediation systems have developed unique ways that improve efficiency. Despite difficulties like site-specificity, sluggish remediation, and biomass buildup potential, phytoremediation is still a vital tool for environmental sustainability.

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.

Deep sea mineral resources and underground space as well as infrastructure for sustainable and liveable cities

This issue covers the papers on two special themes:(1)Mineral resources from deep sea—Science and Engineering and(2)Planning and development of underground space and infrastructure for sustainable and liveable cities.

Minerals in edible insects:a review of content and potential for sustainable sourcing

In response to the rapid increase in world population and subsequent demands for food,edible insects represent an alternative food source for humans that is rich in proteins,amino acids and minerals.Entomophagy is a tradition in many countries including China and Thailand,and edible insects have attracted a lot of attention in Western World due to their suitable nutrient composition,high mineral content(e.g.,Fe,Zn,Ca,Mg)and potential use as a supplement in human diet.In this study,we surveyed mineral content in seven insect orders and 67 species of mass produced and wild-harvested edible insects.The total content of essential elements in edible insects was very high in Tenebrio molitor,Bombyx mori,and Zonocerus variegatus.The heavy metal content(summarized for eight species)was below the maximum limit allowed for safe consumption.Sustainable supply of minerals derived from insect biomass is complicated due to the high variations of mineral content in insects and the potential of its change due to processing.

Smart Farming for Sustainable Rice Production:An Insight into Application,Challenge,and Future Prospect

Rice has a huge impact on socio-economic growth,and ensuring its sustainability and optimal utilization is vital.This review provides an insight into the role of smart farming in enhancing rice productivity.The applications of smart farming in rice production including yield estimation,smart irrigation systems,monitoring disease and growth,and predicting rice quality and classifications are highlighted.The challenges of smart farming in sustainable rice production to enhance the understanding of researchers,policymakers,and stakeholders are discussed.Numerous efforts have been exerted to combat the issues in rice production in order to promote rice sector development.The effective implementation of smart farming in rice production has been facilitated by various technical advancements,particularly the integration of the Internet of Things and artificial intelligence.The future prospects of smart farming in transforming existing rice production practices are also elucidated.Through the utilization of smart farming,the rice industry can attain sustainable and resilient production systems that could mitigate environmental impact and safeguard food security.Thus,the rice industry holds a bright future in transforming current rice production practices into a new outlook in rice smart farming development.

Investigating and predicting the role of photovoltaic, wind, and hydrogen energies in sustainable global energy evolution

The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels.This review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and hydrogen.This transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic development.The transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community impact.The environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological footprint.This study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero emissions.By 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and India.These developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy solutions.This review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.

Regional economic assessment of a novel place-based model for sustainable food systems

Several actions from both the environmental and human viewpoints have already been made to meet the sustainability goals targeted at food systems.Still,new place-based ideas to improve sustainability are needed.Agroecological symbiosis(AES),a novel food system model,is an example of a suggested system-level change to attain sustainability targets;it is a symbiosis of food production and processing using renewable energy that uses its own feedstock.AES has already been found advantageous from the ecological and biophysical viewpoints,but a regional economic evaluation of the model is still lacking.Thus,the aim of our paper is to assess the regional economic impact of a possible systemic change in the food system using the network of agroecological symbiosis(NAES)as an example.We applied scenarios representing different ways of moving towards envisioned NAES models in Mäntsälä,Finland,and a computable general equilibrium model to evaluate the regional economic impact.According to our results,both regional economy and employment would increase,and the regional production base would diversify with NAES implementation applied to the region,but the extent of the benefits varies between scenarios.The scenario that includes change in both public and private food demand,production of bioenergy and utilization of by-products would cause the largest impacts.However,realizing NAES requires investments that may influence the actual implementation of such models.Nonetheless,a change towards NAES can promote an economically and spatially just transition to sustainability,as NAES seems to be economically most beneficial for rural areas.

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.

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.

Agricultural intensity for sustainable regional development:A case study in peri-urban areas of Karawang Regency,Indonesia

Peri-urban areas are playing an increasingly crucial role in the agricultural development and intensification in Indonesia.Peri-urban agriculture is highly vulnerable to change compared with urban and rural agriculture,due to its location in transitional areas.Indicators of peri-urban agricultural intensity can help guide regional development.In this study,we assessed the sustainability of peri-urban areas based on agricultural intensity in Karawang Regency,Indonesia.We developed a village-based index to assess the region’s agricultural intensity by rescaling the village agriculture index(VAI)and combining the local sustainability index(LSI)with factor analysis.Since the unit of analysis is the village,we modified the LSI to the village sustainability index(VSI).In addition,we also developed a logical matrix analysis to determine the level of agricultural sustainability(LoAS)of each village.The combined results of the three indices(VAI,VSI,and LoAS)generated information about agricultural sustainability.The results indicated that peri-urban villages with high agricultural intensity tended to exhibit low levels of social welfare,economic development,and disaster risk.Moreover,high agricultural intensity did not necessarily ensure the prosperity of the people.Instead,there was the economic disparity among the villages in the study area.Encouraging diversity of agricultural intensity seems to be more critical than promoting agricultural intensity itself.Overall,this study highlights the distinctive characteristics and dynamic of peri-urban areas.New approaches,variables,and information regarding the combination of agricultural intensity and sustainability need to be developed as valuable tools for regional planning.

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.

Economy Function in the Mode of Sustainable Development

To implement the previously formulated principles of sustainable economic development, all solutions of the linear system of equations and inequalities, which are satisfied by the vector of real consumption, are completely described. It is established that the vector of real consumption with the minimum level of excess supply is determined by the solution of some quadratic programming problem. The necessary and sufficient conditions are established under which the economic system, described by the “input-output” production model, functions in the mode of sustainable development. A complete description of the equilibrium states for which markets are partially cleared in the economy model of production “input-output” is given, on the basis that all solutions of system of linear equations and inequalities are completely described. The existence of a family of taxation vectors in the “input-output” model of production, under which the economic system is able to function in the mode of sustainable development, is proved. Restrictions were found for the vector of taxation in the economic system, under which the economic system is able to function in the mode of sustainable development.

Social and Economic Considerations for Creating Sustainable Climate Change Haven Communities

As Climate Change Haven Communities are constructed across the Northern Hemisphere, it will be necessary to attract two types of migrants to populate them. The first group consists of professionals and companies in eco-sustainable businesses, such as law firms, insurance companies, investment firms, banking, technological innovation, mass media, medical research and pharmaceutical research. The second group will consist of persons engaged in organic/eco-sustainable agriculture whose crops and animal husbandry practices can be transferred successfully to Climate Change Haven regions. The present research focuses on the social and economic variables that must be taken into account to insure that each new Climate Change Haven Community becomes successfully integrated with the local population and forms a cohesive, harmonious social structure. Examples are given from the United States, France, Spain, Portugal and Italy.

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.

Food Security Problems and Solutions in China Based on the Strategy of Sustainable Agricultural Development

China attaches great importance to food security.With the strong promotion of the government,Chinas grain output has achieved a great feat from"shortage"to"surplus in bumper years"and then to"rising steadily",achieving a record"increase for the tenth consecutive year".From the current balance of food supply and demand in China,the food security situation can be guaranteed on the whole.However,if we analyze the food security in China from the perspective of agricultural sustainable development strategy,there are some difficulties,such as the reduction of cultivated land area,the decline of cultivated land quality,the fragility of agricultural ecological environment,and the transformation of residentsconsumption structure.This paper analyzes the difficulties faced by the development of food security in China under the strategy of sustainable agricultural development,and puts forward that to implement the strategy of sustainable agricultural development,it is necessary to realize the coordinated development of food security,science and technology,ecological environment,resources and society.

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.