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
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
The proposal of carbon neutrality target makes decarbonization and hydrogenation typical features of future energy development in China.With a wide range of application scenarios,hydrogen energy will experience rapid ...The proposal of carbon neutrality target makes decarbonization and hydrogenation typical features of future energy development in China.With a wide range of application scenarios,hydrogen energy will experience rapid growth in production and consumption.To formulate an effective hydrogen energy development strategy for the future of China,this study employs the departmental scenario analysis method to calculate and evaluate the future consumption of hydrogen energy in China’s heavy industry,transportation,electricity,and other related fields.Multidimensional technical parameters are selected and predicted accurately and reliably in combination with different development scenarios.The findings indicate that the period from 2030 to 2050 will enjoy rapid development of hydrogen energy,having an average annual growth rate of 2%to 4%.The technological progress and breakthroughs scenario has the greatest potential for hydrogen demand scale among the four development scenarios.Under this scenario,the total demand for hydrogen energy is expected to reach 446.37Mt in 2060.Thetransportation sector will be the sector with the greatest potential for hydrogen deployment growth from 2023 to 2060,which is expected to rise from 0.038Mt to about 163.18Mt,with the ambitious growth in the future.Additionally,hydrogen energy has a considerable development potential in the steel sector,and the trend of de-refueling coke by hydrogenation in this sector will be imperative for this energy-intensive industries.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
Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power gr...Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.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
Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),i...Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),in particular the resonant portion,is found to provide the dominant contribution to the total toroidal torque under the slow plasma flow regime in ITER.While the electromagnetic torque always opposes the plasma flow,the toroidal torque associated with the Reynolds stress enhances the plasma flow independent of the flow direction.A peculiar double-peak structure for the net NTV torque is robustly computed for ITER,as the toroidal rotation frequency is scanned near the zero value.This structure is found to be ultimately due to a non-monotonic behavior of the wave-particle resonance integral(over the particle pitch angle)in the superbanana plateau NTV regime in ITER.These findings are qualitatively insensitive to variations of a range of factors including the wall resistivity,the plasma pedestal flow and the assumed frequency of the rotating RMP field.展开更多
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.展开更多
The gap between the projected urban areas in the current trend(UAC)and those in the sustainable scenario(UAS)is a critical factor in understanding whether cities can fulfill the requirements of sustainable development...The gap between the projected urban areas in the current trend(UAC)and those in the sustainable scenario(UAS)is a critical factor in understanding whether cities can fulfill the requirements of sustainable development.However,there is a paucity of knowledge on this cutting-edge topic.Given the extensive and rapid urbanization in the United States(U.S.)over the past two centuries,accurately measuring this gap between UAS and UAC is of critical importance for advancing future sustainable urban development,as well as having significant global implications.This study finds that although the 740 U.S.cities have a large UAC in 2100,these cities will encom pass a significant gap from UAC to UAS(approximately 165,000 km2),accounting for 30%UAC at that time.The study also reveals the spatio-temporal heterogeneity of the gap.The gap initially increases before reaching a inflection point in 2090,and it disparates greatly from−100%to 240%at city level.While cities in the Northwestern U.S.maintain UAC that exceeds UAS from 2020 to 2100,cities in other regions shift from UAC that exceeds UAS to UAC that falls short of UAS.Filling the gap without additional urban growth planning could lead to a reduction of crop production ranging from 0.3%to 3%and a 0.68%loss of biomass.Hence,dynamic and forward-looking urban planning is essential for addressing the challenges of sustainable development posed by urbanization,both within the U.S.and globally.展开更多
Increased human activities in China's coastal zone have resulted in the depletion of ecological land resources.Thus,conducting current and future multi-scenario simulation research on land use and land cover chang...Increased human activities in China's coastal zone have resulted in the depletion of ecological land resources.Thus,conducting current and future multi-scenario simulation research on land use and land cover change(LUCC)is crucial for guiding the healthy and sustainable development of coastal zones.System dynamic(SD)-future land use simulation(FLUS)model,a coupled simulation model,was developed to analyze land use dynamics in China's coastal zone.This model encompasses five scenarios,namely,SSP1-RCP2.6(A),SSP2-RCP4.5(B),SSP3-RCP4.5(C),SSP4-RCP4.5(D),and SSP5-RCP8.5(E).The SD model simulates land use demand on an annual basis up to the year 2100.Subsequently,the FLUS model determines the spatial distribution of land use for the near term(2035),medium term(2050),and long term(2100).Results reveal a slowing trend in land use changes in China's coastal zone from 2000–2020.Among these changes,the expansion rate of construction land was the highest and exhibited an annual decrease.By 2100,land use predictions exhibit high accuracy,and notable differences are observed in trends across scenarios.In summary,the expansion of production,living,and ecological spaces toward the sea remains prominent.Scenario A emphasizes reduced land resource dependence,benefiting ecological land protection.Scenario B witnesses an intensified expansion of artificial wetlands.Scenario C sees substantial land needs for living and production,while Scenario D shows coastal forest and grassland shrinkage.Lastly,in Scenario E,the conflict between humans and land intensifies.This study presents pertinent recommendations for the future development,utilization,and management of coastal areas in China.The research contributes valuable scientific support for informed,long-term strategic decision making within coastal regions.展开更多
The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajecto...The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.展开更多
Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon...Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.展开更多
Scenario planning is a powerful tool for cities to navigate uncertainties and mitigate the impacts of adverse scenarios by projecting future outcomes based on present-day decisions.This approach is becoming increasing...Scenario planning is a powerful tool for cities to navigate uncertainties and mitigate the impacts of adverse scenarios by projecting future outcomes based on present-day decisions.This approach is becoming increasingly important given the growing call for building resilient cities to face adverse future scenarios posed by emerging disruptive technologies and climate change.However,conventional scenario planning practices predominantly rely on expert knowledge and judgment,which may be limited in accounting for the complexity of future scenarios.Therefore,we explored the potential integration of artificial intelligence(AI)techniques to assist scenario planning practices.We synthesized related studies from various disciplines(e.g.,engineering,computer science,and urban planning)to identify the potential applications of AI in the three key components of scenario planning:plan generation,scenario generation,and plan evaluation.We then discuss the challenges and possible solutions for integrating AI into the scenario planning process and highlight the critical role of planning experts in this process.We conclude by outlining future research opportunities in this context.Ultimately,this study contributes to the advancement of scenario planning practices and aids the creation of more resilient cities that can thrive in an uncertain future.展开更多
Urban agglomerations,serving as pivotal centers of human activity,undergo swift alterations in ecosystem services prompted by shifts in land utilization.Strengthening the monitoring of ecosystem services in present an...Urban agglomerations,serving as pivotal centers of human activity,undergo swift alterations in ecosystem services prompted by shifts in land utilization.Strengthening the monitoring of ecosystem services in present and future urban agglomerations contributes to the rational planning of these areas and enhances the well-being of their inhabitants.Here,we analyzed land use conversion in the Yangtze River Delta(YRD)urban agglomeration during 1990-2020 and discussed the spatiotemporal response and main drivers of changes in ecosystem service value(ESV).By considering the different development strategic directions described in land use planning policies,we predicted land use conversion and its impact on ESV using the Future Land Use Simulation(FLUS)model in three scenari-os in 2025 and 2030.Results show that:1)from 1990 to 2020,land use change is mainly manifested as the continuous expansion of con-struction land to cultivated land.Among the reduced cultivated land,82.2%were occupied by construction land.2)The land use types conversion caused a loss of 21.85 billion yuan(RMB)in ESV during 1990-2020.Moreover,the large reduction of cultivated land area led to the continuous decline of food production value,accounting for 13%of the total ESV loss.3)From 2020 to 2030,land use change will mainly focus on Yangzhou and Zhenjiang in central Jiangsu Province and Taizhou in southern Zhejiang Province.Under the BAU(natural development)and ED(cultivated land protection)scenarios,construction land expansion remains dominant.In contrast,under the EP(ecological protection)scenario,the areas of water bodies and forest land increase significantly.Among the different scenarios,ESV is highest in the EP scenario,making it the optimal solution for sustainable land use.It can be seen that the space use conflict among urban,agriculture and ecology is a key factor leading to ESV change in the urban agglomeration of Yangtze River Delta.There-fore,it is crucial to maintain spatial land use coordination.Our findings provide suggestions for scientific and rational land use planning for the urban agglomeration.展开更多
To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and ...To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.展开更多
Nanopesticides,as a promising technology,bring scientific and technological impetus to sustainable development and green revolution of agriculture.The excellent physicochemical properties,beneficial biological effects...Nanopesticides,as a promising technology,bring scientific and technological impetus to sustainable development and green revolution of agriculture.The excellent physicochemical properties,beneficial biological effects,and functional potential of nanopesticides have significantly contributed to improving utilization rates of pesticides,enhancing pest and disease management,and alleviating stresses.However,agricultural production and plant cultivation are diverse,leading to a wide range of application scenarios for pesticides.These application scenarios put forward more precise requirements and numerous innovative opportunities for the development of nanopesticides.Scenario-oriented nanopesticides are customized for various application scenarios and methods,aligning with the principles of economical,efficient,and sustainable future agriculture.This article outlines the development status of nanopesticides and then reviews the research progress of scenario-oriented nanopesticides,encompassing nine major application scenarios.Finally,the development priorities and prospects of scenariooriented nanopesticides are summarized,offering innovative concepts for advancement of nanopesticides.展开更多
The glacial history of Pico de Orizaba indicates that during the Last Glacial Maximum,its icecap covered up to~3000 m asl;due to the air temperature increasing,its main glacier has retreated to 5050 m asl.The retracti...The glacial history of Pico de Orizaba indicates that during the Last Glacial Maximum,its icecap covered up to~3000 m asl;due to the air temperature increasing,its main glacier has retreated to 5050 m asl.The retraction of the glacier has left behind an intense climatic instability that causes a high frequency of freeze-thaw cycles of great intensity;the resulting geomorphological processes are represented by the fragmentation of the bedrock that occupies the upper parts of the mountain.There is a notable lack of studies regarding the fragmentation and erosion occurring in tropical high mountains,and the associated geomorphological risks;for this reason,as a first stage of future continuous research,this study analyzes the freezing and thawing cycles that occur above 4000 m asl,through continuous monitoring of surface ground temperature.The results allow us to identify and characterize four zones:glacial,paraglacial,periglacial and proglacial.It was found that the paraglacial zone presents an intense drop of temperature,of up to~9℃ in only sixty minutes.The rock fatigue and intense freeze-thaw cycles that occur in this area are responsible for the high rate of rock disintegration and represent the main factor of the constant slope dynamics that occur at the site.This activity decreases,both in frequency and intensity,according to the distance to the glacier,which is where the temperature presents a certain degree of stability,until reaching the proglacial zone,where cycles are almost non-existent,and therefore there is no gelifraction activity.The geomorphological processes have resulted in significant alterations to the mountain slopes,which can have severe consequences in terms of risk and water.展开更多
The hybrid scenario,which has good confinement and moderate MHD instabilities,is a proposed operation scenario for international thermonuclear experimental reactor(ITER).In this work,the effect of plasma rotation on t...The hybrid scenario,which has good confinement and moderate MHD instabilities,is a proposed operation scenario for international thermonuclear experimental reactor(ITER).In this work,the effect of plasma rotation on the HL-3 hybrid scenario is analyzed with the integrated modeling framework OMFIT.The results show that toroidal rotation has no obvious effect on confinement with a high line averaged density of n_(bar)~(7)×10^(19)m^(-3).In this case,the ion temperature only changes from 4.7 keV to 4.4 keV with the rotation decreasing from 10^(5) rad/s to 10^(3) rad/s,which means that the turbulent heat transport is not dominant.While in the scenarios characterized by lower densities,such as n_(bar)~4×10^(19)m^(-3),turbulent transport becomes dominant in determining heat transport.The ion temperature rises from 3.8 keV to 6.1 keV in the core as the rotation velocity increases from 10^(3) rad/s to 10^(5) rad/s.Despite the ion temperature rising,the rotation velocity does not obviously affect electron temperature or density.Additionally,it is noteworthy that the variation in rotation velocity does not significantly affect the global confinement of plasma in scenarios with low density or with high density.展开更多
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.
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 Natural Science Foundation of China(No.71704178)Beijing Municipal Excellent Talents Foundation(No.2017000020124G133)Major consulting project of the Chinese Academy of Engineering(Nos.2023-JB-08,2022-PP-03).
文摘The proposal of carbon neutrality target makes decarbonization and hydrogenation typical features of future energy development in China.With a wide range of application scenarios,hydrogen energy will experience rapid growth in production and consumption.To formulate an effective hydrogen energy development strategy for the future of China,this study employs the departmental scenario analysis method to calculate and evaluate the future consumption of hydrogen energy in China’s heavy industry,transportation,electricity,and other related fields.Multidimensional technical parameters are selected and predicted accurately and reliably in combination with different development scenarios.The findings indicate that the period from 2030 to 2050 will enjoy rapid development of hydrogen energy,having an average annual growth rate of 2%to 4%.The technological progress and breakthroughs scenario has the greatest potential for hydrogen demand scale among the four development scenarios.Under this scenario,the total demand for hydrogen energy is expected to reach 446.37Mt in 2060.Thetransportation sector will be the sector with the greatest potential for hydrogen deployment growth from 2023 to 2060,which is expected to rise from 0.038Mt to about 163.18Mt,with the ambitious growth in the future.Additionally,hydrogen energy has a considerable development potential in the steel sector,and the trend of de-refueling coke by hydrogenation in this sector will be imperative for this energy-intensive industries.
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funded by the Science and Technology Project of State Grid Corporation of China under Grant No.5108-202218280A-2-299-XG.
文摘Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.
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funded by National Natural Science Foundation of China(NSFC)(Nos.12075053,11505021 and 11975068)by National Key R&D Program of China(No.2022YFE 03060002)+1 种基金by Fundamental Research Funds for the Central Universities(No.2232024G-10)supported by the U.S.DoE Office of Science(No.DE-FG02–95ER54309)。
文摘Toroidal torques,generated by the resonant magnetic perturbation(RMP)and acting on the plasma column,are numerically systematically investigated for an ITER baseline scenario.The neoclassical toroidal viscosity(NTV),in particular the resonant portion,is found to provide the dominant contribution to the total toroidal torque under the slow plasma flow regime in ITER.While the electromagnetic torque always opposes the plasma flow,the toroidal torque associated with the Reynolds stress enhances the plasma flow independent of the flow direction.A peculiar double-peak structure for the net NTV torque is robustly computed for ITER,as the toroidal rotation frequency is scanned near the zero value.This structure is found to be ultimately due to a non-monotonic behavior of the wave-particle resonance integral(over the particle pitch angle)in the superbanana plateau NTV regime in ITER.These findings are qualitatively insensitive to variations of a range of factors including the wall resistivity,the plasma pedestal flow and the assumed frequency of the rotating RMP field.
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
基金supported by the National Natural Science Foun-dation of China(Grants No.42330103,42271469)the Ningbo Science and Technology Bureau(Grant No.2022Z081).
文摘The gap between the projected urban areas in the current trend(UAC)and those in the sustainable scenario(UAS)is a critical factor in understanding whether cities can fulfill the requirements of sustainable development.However,there is a paucity of knowledge on this cutting-edge topic.Given the extensive and rapid urbanization in the United States(U.S.)over the past two centuries,accurately measuring this gap between UAS and UAC is of critical importance for advancing future sustainable urban development,as well as having significant global implications.This study finds that although the 740 U.S.cities have a large UAC in 2100,these cities will encom pass a significant gap from UAC to UAS(approximately 165,000 km2),accounting for 30%UAC at that time.The study also reveals the spatio-temporal heterogeneity of the gap.The gap initially increases before reaching a inflection point in 2090,and it disparates greatly from−100%to 240%at city level.While cities in the Northwestern U.S.maintain UAC that exceeds UAS from 2020 to 2100,cities in other regions shift from UAC that exceeds UAS to UAC that falls short of UAS.Filling the gap without additional urban growth planning could lead to a reduction of crop production ranging from 0.3%to 3%and a 0.68%loss of biomass.Hence,dynamic and forward-looking urban planning is essential for addressing the challenges of sustainable development posed by urbanization,both within the U.S.and globally.
基金Under the auspices of National Natural Science Foundation of China (No.42176221,41901133)Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDA19060205)Seed project of Yantai Institute of Coastal Zone Research,Chinese Academy of Sciences (No.YIC-E3518907)。
文摘Increased human activities in China's coastal zone have resulted in the depletion of ecological land resources.Thus,conducting current and future multi-scenario simulation research on land use and land cover change(LUCC)is crucial for guiding the healthy and sustainable development of coastal zones.System dynamic(SD)-future land use simulation(FLUS)model,a coupled simulation model,was developed to analyze land use dynamics in China's coastal zone.This model encompasses five scenarios,namely,SSP1-RCP2.6(A),SSP2-RCP4.5(B),SSP3-RCP4.5(C),SSP4-RCP4.5(D),and SSP5-RCP8.5(E).The SD model simulates land use demand on an annual basis up to the year 2100.Subsequently,the FLUS model determines the spatial distribution of land use for the near term(2035),medium term(2050),and long term(2100).Results reveal a slowing trend in land use changes in China's coastal zone from 2000–2020.Among these changes,the expansion rate of construction land was the highest and exhibited an annual decrease.By 2100,land use predictions exhibit high accuracy,and notable differences are observed in trends across scenarios.In summary,the expansion of production,living,and ecological spaces toward the sea remains prominent.Scenario A emphasizes reduced land resource dependence,benefiting ecological land protection.Scenario B witnesses an intensified expansion of artificial wetlands.Scenario C sees substantial land needs for living and production,while Scenario D shows coastal forest and grassland shrinkage.Lastly,in Scenario E,the conflict between humans and land intensifies.This study presents pertinent recommendations for the future development,utilization,and management of coastal areas in China.The research contributes valuable scientific support for informed,long-term strategic decision making within coastal regions.
基金supported by the National Natural Science Foundation of China(51875302)。
文摘The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.
文摘Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.
基金supported by the University Development Fund(UDF01003238)provided by the Chinese University of Hong Kong(Shenzhen)graduate school fellowship program at the University of Florida。
文摘Scenario planning is a powerful tool for cities to navigate uncertainties and mitigate the impacts of adverse scenarios by projecting future outcomes based on present-day decisions.This approach is becoming increasingly important given the growing call for building resilient cities to face adverse future scenarios posed by emerging disruptive technologies and climate change.However,conventional scenario planning practices predominantly rely on expert knowledge and judgment,which may be limited in accounting for the complexity of future scenarios.Therefore,we explored the potential integration of artificial intelligence(AI)techniques to assist scenario planning practices.We synthesized related studies from various disciplines(e.g.,engineering,computer science,and urban planning)to identify the potential applications of AI in the three key components of scenario planning:plan generation,scenario generation,and plan evaluation.We then discuss the challenges and possible solutions for integrating AI into the scenario planning process and highlight the critical role of planning experts in this process.We conclude by outlining future research opportunities in this context.Ultimately,this study contributes to the advancement of scenario planning practices and aids the creation of more resilient cities that can thrive in an uncertain future.
基金Under the auspices of National Natural Science Foundation of China(No.42276234)National Social Science Foundation Major Project of China(No.23&ZD105)+1 种基金the Open Fund of the Key Laboratory of Coastal Zone Exploitation and Protection,Ministry of Natural Resources of China(No.2023CZEPK04)the Science and Technology Major Project of Ningbo(No.2021Z181)。
文摘Urban agglomerations,serving as pivotal centers of human activity,undergo swift alterations in ecosystem services prompted by shifts in land utilization.Strengthening the monitoring of ecosystem services in present and future urban agglomerations contributes to the rational planning of these areas and enhances the well-being of their inhabitants.Here,we analyzed land use conversion in the Yangtze River Delta(YRD)urban agglomeration during 1990-2020 and discussed the spatiotemporal response and main drivers of changes in ecosystem service value(ESV).By considering the different development strategic directions described in land use planning policies,we predicted land use conversion and its impact on ESV using the Future Land Use Simulation(FLUS)model in three scenari-os in 2025 and 2030.Results show that:1)from 1990 to 2020,land use change is mainly manifested as the continuous expansion of con-struction land to cultivated land.Among the reduced cultivated land,82.2%were occupied by construction land.2)The land use types conversion caused a loss of 21.85 billion yuan(RMB)in ESV during 1990-2020.Moreover,the large reduction of cultivated land area led to the continuous decline of food production value,accounting for 13%of the total ESV loss.3)From 2020 to 2030,land use change will mainly focus on Yangzhou and Zhenjiang in central Jiangsu Province and Taizhou in southern Zhejiang Province.Under the BAU(natural development)and ED(cultivated land protection)scenarios,construction land expansion remains dominant.In contrast,under the EP(ecological protection)scenario,the areas of water bodies and forest land increase significantly.Among the different scenarios,ESV is highest in the EP scenario,making it the optimal solution for sustainable land use.It can be seen that the space use conflict among urban,agriculture and ecology is a key factor leading to ESV change in the urban agglomeration of Yangtze River Delta.There-fore,it is crucial to maintain spatial land use coordination.Our findings provide suggestions for scientific and rational land use planning for the urban agglomeration.
基金the National Natural Science Foundation of China Youth Fund,Research on Security Low Carbon Collaborative Situation Awareness of Comprehensive Energy System from the Perspective of Dynamic Security Domain(52307130).
文摘To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.
基金funded by the National Key Research Development Program of China(2022YFD1700500)Beijing Natural Science Foundation(6232033).
文摘Nanopesticides,as a promising technology,bring scientific and technological impetus to sustainable development and green revolution of agriculture.The excellent physicochemical properties,beneficial biological effects,and functional potential of nanopesticides have significantly contributed to improving utilization rates of pesticides,enhancing pest and disease management,and alleviating stresses.However,agricultural production and plant cultivation are diverse,leading to a wide range of application scenarios for pesticides.These application scenarios put forward more precise requirements and numerous innovative opportunities for the development of nanopesticides.Scenario-oriented nanopesticides are customized for various application scenarios and methods,aligning with the principles of economical,efficient,and sustainable future agriculture.This article outlines the development status of nanopesticides and then reviews the research progress of scenario-oriented nanopesticides,encompassing nine major application scenarios.Finally,the development priorities and prospects of scenariooriented nanopesticides are summarized,offering innovative concepts for advancement of nanopesticides.
基金support from the Programa de Apoyos para la Superación del Personal Académico (DGAPA)the support by the Alexander von Humboldt Foundationpart of the SIREI project num 531062023178 developed at CCT-UV
文摘The glacial history of Pico de Orizaba indicates that during the Last Glacial Maximum,its icecap covered up to~3000 m asl;due to the air temperature increasing,its main glacier has retreated to 5050 m asl.The retraction of the glacier has left behind an intense climatic instability that causes a high frequency of freeze-thaw cycles of great intensity;the resulting geomorphological processes are represented by the fragmentation of the bedrock that occupies the upper parts of the mountain.There is a notable lack of studies regarding the fragmentation and erosion occurring in tropical high mountains,and the associated geomorphological risks;for this reason,as a first stage of future continuous research,this study analyzes the freezing and thawing cycles that occur above 4000 m asl,through continuous monitoring of surface ground temperature.The results allow us to identify and characterize four zones:glacial,paraglacial,periglacial and proglacial.It was found that the paraglacial zone presents an intense drop of temperature,of up to~9℃ in only sixty minutes.The rock fatigue and intense freeze-thaw cycles that occur in this area are responsible for the high rate of rock disintegration and represent the main factor of the constant slope dynamics that occur at the site.This activity decreases,both in frequency and intensity,according to the distance to the glacier,which is where the temperature presents a certain degree of stability,until reaching the proglacial zone,where cycles are almost non-existent,and therefore there is no gelifraction activity.The geomorphological processes have resulted in significant alterations to the mountain slopes,which can have severe consequences in terms of risk and water.
基金Project supported by the National Magnetic Confinement Fusion Program of China (Grants Nos.2019YFE03040002 and 2018YFE0301101)the Talent Project of China National Nuclear Corporation,China (Grant No.2022JZYF-01)。
文摘The hybrid scenario,which has good confinement and moderate MHD instabilities,is a proposed operation scenario for international thermonuclear experimental reactor(ITER).In this work,the effect of plasma rotation on the HL-3 hybrid scenario is analyzed with the integrated modeling framework OMFIT.The results show that toroidal rotation has no obvious effect on confinement with a high line averaged density of n_(bar)~(7)×10^(19)m^(-3).In this case,the ion temperature only changes from 4.7 keV to 4.4 keV with the rotation decreasing from 10^(5) rad/s to 10^(3) rad/s,which means that the turbulent heat transport is not dominant.While in the scenarios characterized by lower densities,such as n_(bar)~4×10^(19)m^(-3),turbulent transport becomes dominant in determining heat transport.The ion temperature rises from 3.8 keV to 6.1 keV in the core as the rotation velocity increases from 10^(3) rad/s to 10^(5) rad/s.Despite the ion temperature rising,the rotation velocity does not obviously affect electron temperature or density.Additionally,it is noteworthy that the variation in rotation velocity does not significantly affect the global confinement of plasma in scenarios with low density or with high density.
