Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we ...Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.展开更多
Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly deve...Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.展开更多
The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential sc...The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.展开更多
The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been doc...The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been documented.This study aims to answer the following questions:Will the typical soums in the SRB become more overgrazed in the future?What optimal strategy should be implemented?Multisource data were integrated and utilized to model the pastoral system of typical soums using a system dynamics approach.Future scenarios under three SSP-RCPs were projected using the model.The conclusions are as follows:(1)From upstream to downstream,rational scenarios for pastoral system transferred from SSP1-RCP2.6 to SSP2-RCP4.5,which reflect improved productivity at the expense of ecosystem stability.(2)Compared with that during the historical period of 2000-2020,the projected carrying capacity of the soums decreases by 15.2%-37.3%,whereas the number of livestock continues to increase.Consequently,the stocking rate is expected to increase from 0.32-1.16 during 2000-2020 to 1.26-2.02 during 2021-2050,indicating that rangeland will become more overloaded.(3)A livestock reduction strategy based on future livestock stock and grassland carrying capacity scenarios was proposed to maintain a dynamic forage-livestock equilibrium.It is suggested that reducing livestock is a practical option for harmonizing grassland conservation with livestock husbandry development.展开更多
Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.展开更多
This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and car...This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.展开更多
Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and ac...Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and accuracy in weapon system strikes.Piezoelectric actuators(PEAs),known for their nanometer-level precision,flexible stroke,resistance to electromagnetic interference,and scalable structure,have been widely adopted across various fields.Therefore,this study focuses on extreme scenarios involving ultra-high precision(micrometer and beyond),minuscule scales,and highly complex operational conditions.It provides a comprehensive overview of the types,working principles,advantages,and disadvantages of PEAs,along with their potential applications in piezo-actuated smart mechatronic systems(PSMSs).To address the demands of extreme scenarios in high-end equipment fields,we have identified five representative application areas:positioning and alignment,biomedical device configuration,advanced manufacturing and processing,vibration mitigation,micro robot system.Each area is further divided into specific subcategories,where we explore the underlying relationships,mechanisms,representative schemes,and characteristics.Finally,we discuss the challenges and future development trends related to PEAs and PSMSs.This work aims to showcase the latest advancements in the application of PEAs and provide valuable guidance for researchers in this field.展开更多
Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environment...Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.展开更多
Guangdong’s carbon emissions have surpassed the world’s 11th largest emitter.It is indispensable for this province to find a robust cost-effective strategy for reducing carbon emissions.This study employed the Low E...Guangdong’s carbon emissions have surpassed the world’s 11th largest emitter.It is indispensable for this province to find a robust cost-effective strategy for reducing carbon emissions.This study employed the Low Emissions Analysis Platform model,marginal cost curves,and Monte Carlo methods to simulate the energy consumption,carbon emissions,and economic benefits of emission reduction in Guangdong Province from 2020 to 2030 under the application of various structural optimization policies and energy-saving technologies.The main findings are as follows:In 2030,Guangdong Province is projected to achieve a carbon emission reduction of 273.6 to 304.6million t CO_(2eq),with a total reduction cost ranging from 1030.9 to 1452.2 billion yuan.Increasing the share of renewable energy,which still has significant growth potential,can lead to a 1.4 times greater reduction in carbon emissions compared to the application of energy-saving technologies,despite the latter yielding 2.3 times more energy savings.The emission reduction measures with net-cost can contribute 71.4%to the total carbon reduction of the province,being much larger than those with net benefits.The power sector plays a critical role in carbon emission reduction within Guangdong Province,with its various measures exerting the most substantial impact on emission reduction quantity and cost,contributing cumulative variance contributions of 90.1%and 84.3%,respectively.It has relatively large potential for emission reduction and relatively low cost of structural adjustment.展开更多
The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and...The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.展开更多
Aerodynamic evaluation under multi-condition is indispensable for the design of aircraft,and the requirement for mass data still means a high cost.To address this problem,we propose a novel point-cloud multi-condition...Aerodynamic evaluation under multi-condition is indispensable for the design of aircraft,and the requirement for mass data still means a high cost.To address this problem,we propose a novel point-cloud multi-condition aerodynamics transfer learning(PCMCA-TL)framework that enables aerodynamic prediction in data-scarce sce-narios by transferring knowledge from well-learned scenarios.We modified the PointNeXt segmentation archi-tecture to a PointNeXtReg+regression model,including a working condition input module.The model is first pre-trained on a public dataset with 2000 shapes but only one working condition and then fine-tuned on a multi-condition small-scale spaceplane dataset.The effectiveness of the PCMCA-TL framework is verified by comparing the pressure coefficients predicted by direct training,pre-training,and TL models.Furthermore,by comparing the aerodynamic force coefficients calculated by predicted pressure coefficients in seconds with the correspond-ing CFD results obtained in hours,the accuracy highlights the development potential of deep transfer learning in aerodynamic evaluation.展开更多
With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in...With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.展开更多
Real-time assessment of subgrade compaction quality poses a significant challenge in the implementation of intelligent compaction(IC).Current compaction evaluation models are confined to specific scenarios and lack ro...Real-time assessment of subgrade compaction quality poses a significant challenge in the implementation of intelligent compaction(IC).Current compaction evaluation models are confined to specific scenarios and lack robustness.This study proposes a subgrade compaction strategy that utilizes a heterogeneous dataset to estimate compaction quality across diverse scenarios while maintaining model accuracy.Field compaction tests are conducted in four distinct scenarios,considering various construction parameters.Compaction models are developed using several machine learning algorithms.The datasets are thoroughly assessed in terms of quality,diversity and similarity.The proposed model exhibits good performance in new scenarios by incorporating an additional 5%e8%of new data for retraining.The model's generalization capability is enhanced by conducting a limited number of field tests,which are labor-saving and time-efficient.The model's accuracy consistently improves across diverse scenarios and optimal algorithms.The proposed compaction strategy adopts a physics-and-data dual-driven approach,aimed at practical engineering applications and guiding the compaction procedure.展开更多
To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distrib...To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.展开更多
Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we pr...Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.展开更多
In recent years,urban floods have increased in frequency and severity due to intensified extreme rainfall events exacerbated by rapid urbanization.This study integrates a Markov-PLUS model and a rainfall-runoff-flood ...In recent years,urban floods have increased in frequency and severity due to intensified extreme rainfall events exacerbated by rapid urbanization.This study integrates a Markov-PLUS model and a rainfall-runoff-flood hydraulic numerical model to establish a scenario-based research framework for identifying interactions between land use dynamics and urban flood risk,using the Jialu River basin in Zhengzhou,China,as a case study.Future land use changes under three scenarios were forecast:Natural Development(ND),Economic Development(ED),and Ecological Protection(EP),alongside rainfall scenarios occurring every 10,50,and 100 years.There were expansions and decreases in construction land under the ED and EP scenarios,respectively,emphasizing the importance of prioritizing ecological conservation.Economic scenarios showed the highest risks under the increased surface runoff and flood risk driven by higher rainstorm intensity.Over the next 15 years,the Economic Development scenario is projected to increase flood hazard areas,whereas the intensified Ecological Protection scenario is expected to reduce these risks.This underscores the contribution of prioritizing ecological conservation to mitigating disaster risks,calling for enhanced drainage systems and elevated flood protection standards to promote resilient urban development in the face of increasingly severe urban flood challenges.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.展开更多
Economic development,food security,and ecological preservation are important issues encountered by karst re-gions.Faced with complex natural and social dynamics,we attempted to explore how interdependence within socio...Economic development,food security,and ecological preservation are important issues encountered by karst re-gions.Faced with complex natural and social dynamics,we attempted to explore how interdependence within socio-ecological system(SES)shaped sustainability in this region.A SES framework was constructed and three scenarios were predesigned:economic priority scenario,food security scenario,and ecological protection sce-nario.The System Dynamics model was used to simulate and forecast the evolution across various scenarios within the SES from 2005 to 2035.Through the Production-Possibility Frontiers in combined scenarios,trade-offpotential was identified and quantified.The results showed that the decoupling between social and ecological subsystems can be weaken in economic priority scenario,while coupling between them can be strengthen in food security scenario and ecological protection scenario.Within the SES,combined scenario analyses further suggest that the rocky desertification rate and the urban-rural income ratio exhibit the least trade-offpotential and inten-sity in combined economic priority scenario and ecological protection scenario,and the Soil Conservation and Food Supply demonstrate the least trade-offpotential and intensity in combined economic priority scenario and food security scenario.We can conclude the ecological engineering plays a significant role in alleviating trade-offs within the SES,but the effectiveness is limited.In light of intertwined socio-ecological challenges,combining ecological engineering with adaptive adjustments is a crucial strategy to enhance SES resilience and promote sustainable development in the South China Karst.展开更多
Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses o...Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses on Lake Tudakul,one of Uzbekistan’s largest saline lakes and a Ramsar-listed wetland,assessing its vulnerability under future climate scenarios.The study integrates climate scenario modeling(RCP4.5 and RCP8.5)with standardized ecotoxicological bioassays—Microtox®,MARA,algal growth inhibition,Lemna minor,and Daphnia magna toxicity tests—to evaluate combined effects of rising temperatures(2.0℃and 4.5℃)and chemical pollutants.Results reveal increased biological sensitivity to contaminants under elevated temperatures,suggesting potential synergistic impacts that may disrupt lake ecosystem structure and function.Lake Tudakul,a regional biodiversity hotspot,is exposed to agrochemical runoff,increasing salinity,and microplastic pollution,threatening aquatic organisms and ecological services.The accumulation and trophic transfer of pollutants—such as heavy metals,persistent organic compounds,and micro(nano)plastics—pose risks to food webs,public health,and water safety.These stressors may also increase the likelihood of harmful algal blooms and cyanotoxin outbreaks.The study emphasizes the urgent need for early-warning systems,adaptive management,and transboundary cooperation to mitigate ecological risks.Lake Tudakul exemplifies the vulnerability of semi-arid lakes under compounding climate and human pressures,highlighting the importance of integrative,ecosystem-based strategies to safeguard biodiversity and freshwater resources.展开更多
基金supported by the National Natural Science Foundation of China(Nos.42107420,U23A20157,and U1910207)Shanxi Province Science Foundation for Young Scholars(No.20210302124363).
文摘Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1303405).
文摘Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.
基金supported by the Natural Science Foundation of Shandong Province under Grant ZR2024MF062the open research fund of National Mobile Communications Research Laboratory,Southeast University under Grants 2025D03+1 种基金the Future Plan Program for Young Scholars of Shandong University,and the Innovation and Technology Support Program for Young Scholars of Colleges and Universities in Shandong Province under Grant 2022KJ009The B6G R&D Group in Shandong University is greatly thanked for channel measurements.
文摘The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.
基金National Natural Science Foundation of China,No.32161143025,No.42371283,No.W2412155National Key R&D Program of China,No.2022YFE0119200。
文摘The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been documented.This study aims to answer the following questions:Will the typical soums in the SRB become more overgrazed in the future?What optimal strategy should be implemented?Multisource data were integrated and utilized to model the pastoral system of typical soums using a system dynamics approach.Future scenarios under three SSP-RCPs were projected using the model.The conclusions are as follows:(1)From upstream to downstream,rational scenarios for pastoral system transferred from SSP1-RCP2.6 to SSP2-RCP4.5,which reflect improved productivity at the expense of ecosystem stability.(2)Compared with that during the historical period of 2000-2020,the projected carrying capacity of the soums decreases by 15.2%-37.3%,whereas the number of livestock continues to increase.Consequently,the stocking rate is expected to increase from 0.32-1.16 during 2000-2020 to 1.26-2.02 during 2021-2050,indicating that rangeland will become more overloaded.(3)A livestock reduction strategy based on future livestock stock and grassland carrying capacity scenarios was proposed to maintain a dynamic forage-livestock equilibrium.It is suggested that reducing livestock is a practical option for harmonizing grassland conservation with livestock husbandry development.
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
基金supported by the top-level design of the National Natural Science Foundation of China(NSFC)Major Project“Realization of optimal carbon neutral pathway and coupling of multi-scale interaction patterns of natural-social systems in China”(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.
基金financially supported by the National Key R&D Program of China(Grant No.2022YFC2204203)the National Natural Science Foundation of China(Grant No.52305107)。
文摘Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and accuracy in weapon system strikes.Piezoelectric actuators(PEAs),known for their nanometer-level precision,flexible stroke,resistance to electromagnetic interference,and scalable structure,have been widely adopted across various fields.Therefore,this study focuses on extreme scenarios involving ultra-high precision(micrometer and beyond),minuscule scales,and highly complex operational conditions.It provides a comprehensive overview of the types,working principles,advantages,and disadvantages of PEAs,along with their potential applications in piezo-actuated smart mechatronic systems(PSMSs).To address the demands of extreme scenarios in high-end equipment fields,we have identified five representative application areas:positioning and alignment,biomedical device configuration,advanced manufacturing and processing,vibration mitigation,micro robot system.Each area is further divided into specific subcategories,where we explore the underlying relationships,mechanisms,representative schemes,and characteristics.Finally,we discuss the challenges and future development trends related to PEAs and PSMSs.This work aims to showcase the latest advancements in the application of PEAs and provide valuable guidance for researchers in this field.
基金National Natural Science Foundation of China,No.42207078CUG Scholar-Scientific Research Funds at China University of Geosciences(Wuhan),No.2022166+1 种基金China Scholarship Council,No.202306410026Opening Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research,No.IWHR-SKL-KF202217。
文摘Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.
基金supported by Hainan Provincial Natural Science Foundation of China(No.721RC525).
文摘Guangdong’s carbon emissions have surpassed the world’s 11th largest emitter.It is indispensable for this province to find a robust cost-effective strategy for reducing carbon emissions.This study employed the Low Emissions Analysis Platform model,marginal cost curves,and Monte Carlo methods to simulate the energy consumption,carbon emissions,and economic benefits of emission reduction in Guangdong Province from 2020 to 2030 under the application of various structural optimization policies and energy-saving technologies.The main findings are as follows:In 2030,Guangdong Province is projected to achieve a carbon emission reduction of 273.6 to 304.6million t CO_(2eq),with a total reduction cost ranging from 1030.9 to 1452.2 billion yuan.Increasing the share of renewable energy,which still has significant growth potential,can lead to a 1.4 times greater reduction in carbon emissions compared to the application of energy-saving technologies,despite the latter yielding 2.3 times more energy savings.The emission reduction measures with net-cost can contribute 71.4%to the total carbon reduction of the province,being much larger than those with net benefits.The power sector plays a critical role in carbon emission reduction within Guangdong Province,with its various measures exerting the most substantial impact on emission reduction quantity and cost,contributing cumulative variance contributions of 90.1%and 84.3%,respectively.It has relatively large potential for emission reduction and relatively low cost of structural adjustment.
基金Under the auspices of National Natural Science Foundation of China(No.42201374,42071359)。
文摘The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.
基金supported by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045).
文摘Aerodynamic evaluation under multi-condition is indispensable for the design of aircraft,and the requirement for mass data still means a high cost.To address this problem,we propose a novel point-cloud multi-condition aerodynamics transfer learning(PCMCA-TL)framework that enables aerodynamic prediction in data-scarce sce-narios by transferring knowledge from well-learned scenarios.We modified the PointNeXt segmentation archi-tecture to a PointNeXtReg+regression model,including a working condition input module.The model is first pre-trained on a public dataset with 2000 shapes but only one working condition and then fine-tuned on a multi-condition small-scale spaceplane dataset.The effectiveness of the PCMCA-TL framework is verified by comparing the pressure coefficients predicted by direct training,pre-training,and TL models.Furthermore,by comparing the aerodynamic force coefficients calculated by predicted pressure coefficients in seconds with the correspond-ing CFD results obtained in hours,the accuracy highlights the development potential of deep transfer learning in aerodynamic evaluation.
文摘With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.
基金supported by the National Natural Science Foundation of China(Grant Nos.52038005 and 52278342)the Natural Science Foundation of Tianjin Municipal(Grant No.23JCJQJC00160).
文摘Real-time assessment of subgrade compaction quality poses a significant challenge in the implementation of intelligent compaction(IC).Current compaction evaluation models are confined to specific scenarios and lack robustness.This study proposes a subgrade compaction strategy that utilizes a heterogeneous dataset to estimate compaction quality across diverse scenarios while maintaining model accuracy.Field compaction tests are conducted in four distinct scenarios,considering various construction parameters.Compaction models are developed using several machine learning algorithms.The datasets are thoroughly assessed in terms of quality,diversity and similarity.The proposed model exhibits good performance in new scenarios by incorporating an additional 5%e8%of new data for retraining.The model's generalization capability is enhanced by conducting a limited number of field tests,which are labor-saving and time-efficient.The model's accuracy consistently improves across diverse scenarios and optimal algorithms.The proposed compaction strategy adopts a physics-and-data dual-driven approach,aimed at practical engineering applications and guiding the compaction procedure.
基金supported by State Grid Anhui Electric Power Co.,Ltd.Research Program(B3120923000C).
文摘To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.
基金supported in part by the National Key Research and Development Program of China(2024YFB4709100,2021YFE0206100)the National Natural Science Foundation of China(62073321)+1 种基金the National Defense Basic Scientific Research Program(JCKY2019203C029)the Science and Technology Development Fund,Macao SAR,China(0015/2020/AMJ)
文摘Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.
基金supported by the National Key Research and Development Plan of China(Grants No.2022YFC3004404 and 2023YFF1305303)。
文摘In recent years,urban floods have increased in frequency and severity due to intensified extreme rainfall events exacerbated by rapid urbanization.This study integrates a Markov-PLUS model and a rainfall-runoff-flood hydraulic numerical model to establish a scenario-based research framework for identifying interactions between land use dynamics and urban flood risk,using the Jialu River basin in Zhengzhou,China,as a case study.Future land use changes under three scenarios were forecast:Natural Development(ND),Economic Development(ED),and Ecological Protection(EP),alongside rainfall scenarios occurring every 10,50,and 100 years.There were expansions and decreases in construction land under the ED and EP scenarios,respectively,emphasizing the importance of prioritizing ecological conservation.Economic scenarios showed the highest risks under the increased surface runoff and flood risk driven by higher rainstorm intensity.Over the next 15 years,the Economic Development scenario is projected to increase flood hazard areas,whereas the intensified Ecological Protection scenario is expected to reduce these risks.This underscores the contribution of prioritizing ecological conservation to mitigating disaster risks,calling for enhanced drainage systems and elevated flood protection standards to promote resilient urban development in the face of increasingly severe urban flood challenges.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
基金supported by the National Key Research and Develop-ment Program of China(Grant No.2022YFF1300701)the Sichuan Science and Technology Program(Grant No.2022JDJQ0015).
文摘Economic development,food security,and ecological preservation are important issues encountered by karst re-gions.Faced with complex natural and social dynamics,we attempted to explore how interdependence within socio-ecological system(SES)shaped sustainability in this region.A SES framework was constructed and three scenarios were predesigned:economic priority scenario,food security scenario,and ecological protection sce-nario.The System Dynamics model was used to simulate and forecast the evolution across various scenarios within the SES from 2005 to 2035.Through the Production-Possibility Frontiers in combined scenarios,trade-offpotential was identified and quantified.The results showed that the decoupling between social and ecological subsystems can be weaken in economic priority scenario,while coupling between them can be strengthen in food security scenario and ecological protection scenario.Within the SES,combined scenario analyses further suggest that the rocky desertification rate and the urban-rural income ratio exhibit the least trade-offpotential and inten-sity in combined economic priority scenario and ecological protection scenario,and the Soil Conservation and Food Supply demonstrate the least trade-offpotential and intensity in combined economic priority scenario and food security scenario.We can conclude the ecological engineering plays a significant role in alleviating trade-offs within the SES,but the effectiveness is limited.In light of intertwined socio-ecological challenges,combining ecological engineering with adaptive adjustments is a crucial strategy to enhance SES resilience and promote sustainable development in the South China Karst.
基金supported by Türkiye Council of Higher Education Research Universities Support Program(Project Number:32762).
文摘Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses on Lake Tudakul,one of Uzbekistan’s largest saline lakes and a Ramsar-listed wetland,assessing its vulnerability under future climate scenarios.The study integrates climate scenario modeling(RCP4.5 and RCP8.5)with standardized ecotoxicological bioassays—Microtox®,MARA,algal growth inhibition,Lemna minor,and Daphnia magna toxicity tests—to evaluate combined effects of rising temperatures(2.0℃and 4.5℃)and chemical pollutants.Results reveal increased biological sensitivity to contaminants under elevated temperatures,suggesting potential synergistic impacts that may disrupt lake ecosystem structure and function.Lake Tudakul,a regional biodiversity hotspot,is exposed to agrochemical runoff,increasing salinity,and microplastic pollution,threatening aquatic organisms and ecological services.The accumulation and trophic transfer of pollutants—such as heavy metals,persistent organic compounds,and micro(nano)plastics—pose risks to food webs,public health,and water safety.These stressors may also increase the likelihood of harmful algal blooms and cyanotoxin outbreaks.The study emphasizes the urgent need for early-warning systems,adaptive management,and transboundary cooperation to mitigate ecological risks.Lake Tudakul exemplifies the vulnerability of semi-arid lakes under compounding climate and human pressures,highlighting the importance of integrative,ecosystem-based strategies to safeguard biodiversity and freshwater resources.
