Integrated water risk early warning framework of the semi-arid transitional zone based on the water environmental carrying capacity (WECC)

Water risk early warning systems based on the water environmental carrying capacity(WECC)are powerful and effective tools to guarantee the sustainability of rivers.Existing work on the early warning of WECC has mainly concerned the comprehensive evaluation of the status quo and lacked a quantitative prejudgement and warning of future overload.In addition,existing quantitative methods for short-term early warning have rarely focused on the integrated change trends of the early warning indicators.Given the periodicity of the socioeconomic system,however,the water environmental system also follows a trend of cyclical fluctuations.Thus,it is meaningful to monitor and use this periodicity for the early warning of the WECC.In this study,we first adopted and improved the prosperity index method to develop an integrated water risk early warning framework.We also constructed a forecast model to qualitatively and quantitatively prejudge and warn about the development trends of the water environmental system.We selected the North Canal Basin(an essential connection among the Beijing-Tianjin-Hebei region)in China as a case study and predicted the WECC in 25 water environmental management units of the basin in 2018–2023.We found that the analysis of the prosperity index was helpful in predicting the WECC,to some extent.The result demonstrated that the early warning system provided reliable prediction(root mean square error of 0.0651 and mean absolute error of 0.1418),and the calculation results of the comprehensive early warning index(CEWI)conformed to the actual situation and related research in the river basin.From 2008 to 2023,the WECC of most water environmental management units in the basin had improved but with some spatial differences:the CEWI was generally poor in areas with many human disturbances,while it was relatively good in the upstream regions with higher forest and grass covers as well as in the downstream areas with larger water volume.Finally,through a sensitivity analysis of the indicators,we proposed specific management measures for the sustainability of the water environmental system in the North Canal Basin.Overall,the integrated water risk early warning framework could provide an appropriate method for the water environmental administration department to predict the WECC of the basin in the future.This framework could also assist in implementing corresponding management measures in advance,especially for the performance evaluation and the arrangement of key short-term tasks in the River Chief System in China.

Analysis of the Concept of Environmental Carrying Capacity

From the concept of carrying capacity proposed in the early 20th century to as an important tool for describing development constraints in the 21st century,many scholars have conducted extensive and detailed research on carrying capacity at different levels,but the carrying capacity system has not yet formed a unified theoretical and methodological system.By summarizing and analyzing the existing literature,based on the viewpoints of Mr.Gao Jixi and Mr.Zeng Weihua,the relationship between different mainstream carrying capacities is analyzed,and finally a system for summarizing the elements of different carrying capacities is provided,which to some extent serves as a reference for scholars who have just come into contact with the concept of carrying capacity.It is thought that:①the research on ecological carrying capacity covers the scope of cities,and the research at the urban level complements the neglected and insufficient areas of ecological research.②The main difference among ecological carrying capacity,urban comprehensive carrying capacity and resource environment carrying capacity lies in the different research scopes.In the mainstream view,environmental carrying capacity and resource carrying capacity are summarized under the framework of different research scopes.Water environment carrying capacity,land resource carrying capacity and other single factor carrying capacity are special in-depth studies of environment and resource carrying capacity.③Ecological carrying capacity at the ecological level includes environmental carrying capacity and resource carrying capacity.At the urban level,urban ecology is equivalent to urban environment to a certain extent,and resources can be classified into urban environmental carrying capacity as an environmental element.

The impact of demographic dynamics on food consumption and its environmental outcomes:Evidence from China

With increasing population and changing demographics,food consumption has experienced a significant transition in quantity and quality.However,a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics,particularly in emerging economies like China.Using the two-stage Quadratic Almost Demand System(QUAIDS)model,this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China.Under various scenarios,according to changes in demographics,we extend our analysis to project the long-term trend of food consumption and its environmental impacts,including greenhouse gas(GHG)emissions,water footprint(WF),and land appropriation(LA).The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry,egg,and aquatic products,particularly for urban residents.Moreover,an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products.Correspondingly,in the current scenario of an increased aging population and sex ratio,it is anticipated that GHG emissions,WF,and LA are likely to decrease by 1.37,2.52,and 3.56%,respectively.More importantly,in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022,GHG emissions,WF,and LA in urban areas would increase by 12.78,20.94,and 18.32%,respectively.Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption.

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

Environmental performance assessments of different methods of coal preparation for use in small-capacity boilers: experiment and theory

The purpose of this article is to receive environmental assessments of combustion of different types of coal fuel depending on the preparation(unscreened,size-graded,briquetted and heat-treated)in automated boilers and boilers with manual load-ing.The assessments were made on the basis of data obtained from experimental methods of coal preparation and calculated methods of determining the amount of pollutant and greenhouse gas emissions,as well as the mass of ash and slag waste.The main pollutants from coal combustion are calculated:particulate matter,benz(a)pyrene,nitrogen oxides,sulfur dioxide,carbon monoxide.Of the greenhouse gases carbon dioxide is calculated.As a result of conducted research it is shown that the simplest preliminary preparation(size-graded)of coal significantly improves combustion efficiency and environmental performance:emissions are reduced by 13%for hard coal and up to 20%for brown coal.The introduction of automated boil-ers with heat-treated coal in small boiler facilities allows to reduce emissions and ash and slag waste by 2-3 times.The best environmental indicators correspond to heat-treated lignite,which is characterized by the absence of sulfur dioxide emissions.

Effect of Trimetazidine on Functional Capacity in Patient with Ischaemic Cardiomyopathy (TOFCAPI)

Objective: This study aimed to evaluate the efficacy of trimetazidine on exercise capacity via a six-minute walk test in patients with ischaemic cardiomyopathy and also evaluate the effect of trimetazidine on left ventricular function via echocardiography in the same population. Methods: This prospective observational study, conducted at the National Institute of Cardiovascular Diseases in Dhaka, Bangladesh, enrolled 200 patients with ischaemic cardiomyopathy and a depressed left ventricular ejection fraction (LVEF Results: In this study (n = 200) of ischaemic cardiomyopathy patients, the mean age was 58 years, with 76% of the patients being male. All study subjects received GDMT (Guideline-Directed Medical Therapy) for angina and heart failure. Those who received the modified released form of trimetazidine developed lesions during the 1st and 2nd follow-ups, during which the LVEF, LVIDd, and six-minute walk distance significantly improved (p Conclusion: The findings of the present study demonstrated that the addition of modified-release trimetazidine to GDMT can improve exercise capacity and left ventricular function in patients with ischaemic cardiomyopathy.

Functional Capacity of Patients with Venous Thromboembolic Disease Six to Twelve Months after Treatment

Background: Venous thromboembolism (VTE) is among the leading causes of hospital-related disability-adjusted life years lost. We aimed to determine the prevalence and determinants of functional capacity impairment six to twelve months after an acute VTE event. Methods: This was a cross-sectional study conducted between January and April 2021 in two referral hospitals of Yaoundé, including consenting adult patients admitted to these hospitals six to twelve months ago for VTE. We excluded dead patients and those with any comorbidity or symptoms limiting physical activity. The functional outcome was assessed with the six-minute walk test. Functional capacity impairment was defined as walking distance lower than the expected value. Results: We included 27 cases in this study with a mean age of 53.2 ± 14.4 years. The prevalence of functional capacity impairment was 29.6% (95% CI: 14.8 - 48.1). Factors associated with poor functional outcome were obesity (OR: 59.5;95% CI: 4.6 - 767.2;p - 207.4;p = 0.017), massive PE (OR: 30;95% CI: 2.5 - 354;p = 0.004), and poor adherence to treatment (OR: 30.3;95% CI: 2.5 - 333.3;p = 0.004). Conclusion: Functional capacity impairment is common in the medium-term after VTE and factors associated with this poor outcome are obesity, the severity of the VTE, and poor adherence to treatment.

Effect of speed humps on instantaneous traffic emissions in a microscopic model with limited deceleration capacity

As a common transportation facility, speed humps can control the speed of vehicles on special road sections to reduce traffic risks. At the same time, they also cause instantaneous traffic emissions. Based on the classic instantaneous traffic emission model and the limited deceleration capacity microscopic traffic flow model with slow-to-start rules, this paper has investigated the impact of speed humps on traffic flow and the instantaneous emissions of vehicle pollutants in a single lane situation. The numerical simulation results have shown that speed humps have significant effects on traffic flow and traffic emissions. In a free-flow region, the increase of speed humps leads to the continuous rise of CO_(2), NO_X and PM emissions. Within some density ranges, one finds that these pollutant emissions can evolve into some higher values under some random seeds. Under other random seeds, they can evolve into some lower values. In a wide moving jam region, the emission values of these pollutants sometimes appear as continuous or intermittent phenomenon. Compared to the refined Na Sch model, the present model has lower instantaneous emissions such as CO_(2), NO_X and PM and higher volatile organic components(VOC) emissions. Compared to the limited deceleration capacity model without slow-to-start rules, the present model also has lower instantaneous emissions such as CO_(2), NO_X and PM and higher VOC emissions in a wide moving jam region. These results can also be confirmed or explained by the statistical values of vehicle velocity and acceleration.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data

Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.

Prediction of Damping Capacity Demand in Seismic Base Isolators via Machine Learning

Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures.The base isolators may lose their damping capacity over time due to environmental or dynamic effects.This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-termisolator life.In this study,an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time.With the developed model,the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity,and the decrease in the damping property was tried to be determined.For this purpose,a data set was created by collecting the behavior of structures with single degrees of freedom(SDOF),different stiffness,damping ratio and natural period isolated from the foundation under far fault earthquakes.The data is divided into 5 different damping classes varying between 10%and 50%.Machine learning model was trained in damping classes with the data on the structure’s response to random seismic vibrations.As a result of the isolator behavior under randomly selected earthquakes,the recorded motion and structural acceleration of the structure against any seismic vibration were examined,and the decrease in the damping capacity was estimated on a class basis.The performance loss of the isolators,which are separated according to their damping properties,has been tried to be determined,and the reductions in the amounts to be taken into account have been determined by class.In the developed prediction model,using various supervised machine learning classification algorithms,the classification algorithm providing the highest precision for the model has been decided.When the results are examined,it has been determined that the damping of the isolator structure with the machine learning method is predicted successfully at a level exceeding 96%,and it is an effective method in deciding whether there is a decrease in the damping capacity.

Recent Developments in Metallic Degradable Micromotors for Biomedical and Environmental Remediation Applications

Synthetic micromotor has gained substantial attention in biomedicine and environmental remediation.Metal-based degradable micromotor composed of magnesium(Mg),zinc(Zn),and iron(Fe)have promise due to their nontoxic fuel-free propulsion,favorable biocompatibility,and safe excretion of degradation products Recent advances in degradable metallic micromotor have shown their fast movement in complex biological media,efficient cargo delivery and favorable biocompatibility.A noteworthy number of degradable metal-based micromotors employ bubble propulsion,utilizing water as fuel to generate hydrogen bubbles.This novel feature has projected degradable metallic micromotors for active in vivo drug delivery applications.In addition,understanding the degradation mechanism of these micromotors is also a key parameter for their design and performance.Its propulsion efficiency and life span govern the overall performance of a degradable metallic micromotor.Here we review the design and recent advancements of metallic degradable micromotors.Furthermore,we describe the controlled degradation,efficient in vivo drug delivery,and built-in acid neutralization capabilities of degradable micromotors with versatile biomedical applications.Moreover,we discuss micromotors’efficacy in detecting and destroying environmental pollutants.Finally,we address the limitations and future research directions of degradable metallic micromotors.

Durable K-ion batteries with 100%capacity retention up to 40,000 cycles

Currently,the major challenge in terms of research on K-ion batteries is to ensure that they possess satisfactory cycle stability and specific capacity,especially in terms of the intrinsically sluggish kinetics induced by the large radius of K+ions.Here,we explore high-performance K-ion half/full batteries with high rate capability,high specific capacity,and extremely durable cycle stability based on carbon nanosheets with tailored N dopants,which can alleviate the change of volume,increase electronic conductivity,and enhance the K+ion adsorption.The as-assembled K-ion half-batteries show an excellent rate capability of 468 mA h g^(−1) at 100 mA g^(−1),which is superior to those of most carbon materials reported to date.Moreover,the as-assembled half-cells have an outstanding life span,running 40,000 cycles over 8 months with a specific capacity retention of 100%at a high current density of 2000 mA g^(−1),and the target full cells deliver a high reversible specific capacity of 146 mA h g^(−1) after 2000 cycles over 2 months,with a specific capacity retention of 113%at a high current density of 500 mA g^(−1),both of which are state of the art in the field of K-ion batteries.This study might provide some insights into and potential avenues for exploration of advanced K-ion batteries with durable stability for practical applications.

Environmental Impact Assessment of Onshore Wind Farms in the Region of Central Greece Using a Modified RIAM Method

Wind energy is one of the most basic forms of renewable energy,which shows an increasing rate of development worldwide and also at the European level.However,this rapid deployment of wind farms makes the need for an impact assessment of this type of projects on the natural and man-made environment imperative.The present paper aims to identify and assess the environmental impacts of wind farm projects in the Region of Central Greece.A modified Rapid Impact Assessment Matrix(RIAM)method is used for this purpose.The methodology includes the identification of the existing onshore wind farm projects in the study area,the appropriate modifications of the RIAM method to respond to the characteristics of the projects and the study area,the qualitative assessment of their potential impacts during construction and operational phases and the computation of the Environmental Performance Grade(EPG)of projects based on the pro-posed modified RIAM method.The results reveal that although there are some slight negative impacts on the natural environment of the study area,the examined wind farms contribute positively both to the atmosphere and to the socio-economic environment of the study.This study extends the potential for using RIAM as a tool in environmental impact assessment studies of renewable energy projects.

Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

MOF-derived porous graphitic carbon with optimized plateau capacity and rate capability for high performance lithium-ion capacitors

The development of anode materials with high rate capability and long charge-discharge plateau is the key to improve per-formance of lithium-ion capacitors(LICs).Herein,the porous graphitic carbon(PGC-1300)derived from a new triply interpenetrated co-balt metal-organic framework(Co-MOF)was prepared through the facile and robust carbonization at 1300°C and washing by HCl solu-tion.The as-prepared PGC-1300 featured an optimized graphitization degree and porous framework,which not only contributes to high plateau capacity(105.0 mAh·g^(−1)below 0.2 V at 0.05 A·g^(−1)),but also supplies more convenient pathways for ions and increases the rate capability(128.5 mAh·g^(−1)at 3.2 A·g^(−1)).According to the kinetics analyses,it can be found that diffusion regulated surface induced capa-citive process and Li-ions intercalation process are coexisted for lithium-ion storage.Additionally,LIC PGC-1300//AC constructed with pre-lithiated PGC-1300 anode and activated carbon(AC)cathode exhibited an increased energy density of 102.8 Wh·kg^(−1),a power dens-ity of 6017.1 W·kg^(−1),together with the excellent cyclic stability(91.6%retention after 10000 cycles at 1.0 A·g^(−1)).

Groundwater and environmental challenges in Asia

Asia stands out as the most populous and geographically diverse region globally.The pressing issues of water resource development and the resulting ecological impacts are exacerbated by the region's rapid population growth and economic expansion.Groundwater,a vital source of water in Asia,faces significant disparities in distribution and suffers from unsustainable exploitation practices.This study applies groundwater system theory and categorizes Asia into 11 primary groundwater systems and 36 secondary ones,based on intercontinental geological structures,climate,terrain,and hydrogeological characteristics.As of the end of 2010,Asia's assessed groundwater resources totalled 4.677×10^(9) m^(3)/a,with exploitable resources amounting to 3.274×10^(9) m^(3)/a.By considering the geological environmental impacts of groundwater development and the distinctive characteristics of terrain and landforms,six categories of effect zones with varying distribution patterns are identified.The current research on Asia's groundwater resources,environmental dynamics,and human impacts aims to provide a theoretical foundation for sustainable groundwater management and environmental conservation in the region.

High-temperature corrosion of sintered RE_(2)Si_(2)O_(7)(RE=Yb and Ho)environmental barrier coating materials by volcanic ash

Rare-earth silicates are promising environmental barrier coatings(EBCs)that can protect SiC_(f)/Si C_(m)substrates in next-genera tion gas turbine blades.Notably,RE_(2)Si_(2)O_(7)(RE=Yb and Ho)shows potential as an EBC due to its coefficient of thermal expansion(CTE)compatible with substrates and high resistance to water vapor corrosion.The target operating temperature for next-generation tur bine blades is 1400°C.Corrosion is inevitable during adhesion to molten volcanic ash,and thus,understanding the corrosion behavior o the material is crucial to its reliability.This study investigates the high-temperature corrosion behavior of sintered RE_(2)Si_(2)O_(7)(RE=Yb and Ho).Samples were prepared using a solid-state reaction and hot-press method.They were then exposed to volcanic ash at 1400°C for 224,and 48 h.After 48 h of exposure,volcanic ash did not react with Yb_(2)Si_(2)O_(7)but penetrated its interior,causing damage.Meanwhile Ho_(2)Si_(2)O_(7)was partially dissolved in the molten volcanic ash,forming a reaction zone that prevented volcanic ash melts from penetrating the interior.With increasing heat treatment time,the reaction zone expanded,and the thickness of the acicular apatite grains increased The Ca:Si ratios in the residual volcanic ash were mostly unchanged for Yb_(2)Si_(2)O_(7)but decreased considerably over time for Ho_(2)Si_(2)O_(7).Th Ca in volcanic ash was consumed and formed apatite,indicating that RE^(3+)ions with large ionic radii(Ho>Yb)easily precipitated apatit from the volcanic ash.

Tensile Strain Capacity Prediction of Engineered Cementitious Composites (ECC) Using Soft Computing Techniques

Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is present.In order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional concrete.Since concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched properties.As a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes challenging.Meanwhile,the effort required for laboratory trial batches to determine the TSC is reduced.To achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly ash.Data from115 mixtures are gathered and analyzed to develop a new model.The input variables include mixture proportions,fiber length and diameter,and the time required for curing the various mixtures.The model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)value.Consequently,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.

Grain size and surface micro-texture characteristics and their paleoenvironmental significance of Holocene sediment in southern margin of the Gurbantunggut Desert,China

The southern margin of the Gurbantunggut Desert,China,is characterized by alternating layers of aeolian and alluvial deposits.Investigating the characteristics of arenaceous sediment in this area is of significant importance for understanding the interactive processes of wind and water forces,as well as the provenance of sediment.However,there are relatively few investigations on the characteristics of such sediment at present.In this study,we researched three aeolian-alluvial interactive stratigraphic profiles and different types of surface sediment on the desert-oasis transitional zone of southern margin of the Gurbantunggut Desert.Based on the optically stimulated luminescence(OSL)dating of aeolian sand and analyses of quartz sand grain size and surface micro-texture,we explored the aeolian-alluvial environmental change at southern margin of the desert in Holocene,as well as the provenance of sediment.The results indicated that the grain size characteristics of different types of sediment in the stratigraphic profiles were similar to those of modern dune sand,interdune sand,muddy desert surface soil,and riverbed sand.Their frequency curves were unimodal or bimodal,and cumulative probability curves were two-segment or three-segment,mainly composed of suspension load and saltation load.The quartz sand in the sediment at southern margin of the desert had undergone alternating transformation of various exogenic forces,with short transportation distance and time,and sedimentary environment was relatively humid.In Holocene,southern margin of the desert primarily featured braided river deposits,and during intermittent period of river activity,there were also aeolian deposits such as sand sheet deposits,stabilized dune deposits,and mobile dune deposits.The provenance for Holocene alluvial deposits at southern margin of the desert remains relatively constant,with the debris of the Tianshan Mountains being the primary provenance.Aeolian sand is mainly near-source recharge,which is formed by in situ deposition of fluvial or lacustrine materials in southern margin of the desert transported by wind erosion,and its provenance was still the weathered debris of the Tianshan Mountains.In addition,the sand in interior of the desert may be transported by northwest wind in desert-scale,thus affecting the development of dunes in southern margin of the desert.The results of this study provide a reference for understanding the composition and provenance changes of desert sand in the context of global climate change.