TiO2 pigments are typically coated with inert layers to suppress the photocatalytic activity and improve the weatherability. However, the traditional inert layers have a lower refractive index compared to TiO2, and th...TiO2 pigments are typically coated with inert layers to suppress the photocatalytic activity and improve the weatherability. However, the traditional inert layers have a lower refractive index compared to TiO2, and therefore reduce the lightening power of TiO2. In the present work, a uniform, amorphous, 2.9-nm-thick TiO2 protective layer was deposited onto the surface of anatase TiO2 pigments according to pulsed chemical vapor deposition at room temperature, with Ti Cl4 as titanium precursor. Amorphous TiO2 coating layers exhibited poor photocatalytic activity, leading to a boosted weatherability. Similarly, this coating method is also effective for TiO2 coating with amorphous SiO2 and SnO2 layers. However, the lightening power of amorphous TiO2 layer is higher than those of amorphous SiO2 and SnO2 layers. According to the measurements of photoluminescence lifetime, surface photocurrent density, charge-transfer resistance, and electron spin resonance spectroscopy, it is revealed that the amorphous layer can prevent the migration of photogenerated electrons and holes onto the surface, decreasing the densities of surface electron and hole, and thereby suppress the photocatalytic activity.展开更多
Although inorganic pigments in common spectral tuning materials show good weatherability and heat resistance,the limited color choices,weak coloring power,poor dispersibility,and a possibility of toxicity limit their ...Although inorganic pigments in common spectral tuning materials show good weatherability and heat resistance,the limited color choices,weak coloring power,poor dispersibility,and a possibility of toxicity limit their development.On the basis of organic pigments which possess a wide range of colors,high coloring power,good transparency,and high safety,herein,the modified pigment and biomimetic coating with improved weatherability,especially ultraviolet(UV)resistance(from 2 to 6 days),was achieved by intercalating acid green 25(AG25)pigment into Mg/Al-layered double hydroxides(Mg/Al-LDH).Furthermore,the heat resistance of AG25 was also significantly increased.Moreover,the spectral stability of pigments after heat treatment is superior with almost unchanged spectral profile and green reflection peak.The formation of strong N-H bonds and the S-M(Mg,Al)bonds between Mg/Al-LDH laminates and AG25 molecules contributes to the improvement.This work shows potential for biomimetic leaf materials in respect of reflective spectra stability.展开更多
Small things can show a person's true character Find lt What was the weather like when the girl came to the castle door?nce upon a time,there was a prince.He wanted to marry a real princess.He traveled all around ...Small things can show a person's true character Find lt What was the weather like when the girl came to the castle door?nce upon a time,there was a prince.He wanted to marry a real princess.He traveled all around the world looking for one.展开更多
Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and dr...Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.展开更多
Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep...Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge.In this work,three key solutions are proposed:(1)motivated by the need to improve model performance in data-scarce regional forecasting scenarios,the authors innovatively apply semantic segmentation models,to better capture spatiotemporal features and improve prediction accuracy;(2)recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness,a novel learnable Gaussian noise mechanism is introduced that allows the model to adaptively optimize perturbations for different locations,ensuring more effective learning;and(3)to address the issue of error accumulation in autoregressive prediction,as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction,the authors propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance.The method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition.Ablation experiments further validate the effectiveness of each component,highlighting their contributions to enhancing prediction performance.展开更多
In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to...In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.展开更多
Scandium(Sc)is a critical metal with increasing demand driven by its applications in high-technology industries.The Late Permian claystones in the Sichuan-Yunnan-Guizhou region of southwestern(SW)China represent a pot...Scandium(Sc)is a critical metal with increasing demand driven by its applications in high-technology industries.The Late Permian claystones in the Sichuan-Yunnan-Guizhou region of southwestern(SW)China represent a potentially new and important Sc resource.This study investigates the distribution,occurrence,and source of Sc in claystones from the Weining area in western Guizhou,and discusses its precipitation mechanism.The sedimentary succession primarily comprises successive layers of ferric,aluminous,carbonaceous,tuffaceous,and silty clastic claystones from bottom to top.Scandium is mainly enriched in ferric claystones,with concentrations reaching up to 56 ppm,while other types contain less than 30 ppm.The principal Sc-hosting minerals include goethite,anatase,brookite,zircon,and xenotime.High-resolution transmission electron microscopy indicates that Sc(~0.9 wt%)is homogeneously distributed within nanometer-scale zircon.The presence of xenotime inclusions within zircon suggests a sedimentary origin.Rare earth element and platinum-group element patterns,together with trace element ratios,indicate that Sc in ferric horizons was derived from intense subaerial weathering of high-Ti basalts and precipitated under oxygenated aquatic conditions.Subsequent multi-stage hydrodynamic processes,including marine transgression-regression and fluvial reworking,facilitated Sc remobilization via mineral dissolution-reprecipitation,ultimately leading to further enrichment within ferric horizons through downward migration.展开更多
Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC rec...Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.展开更多
The Changbai Mountains,in Northeast China's Jilin Province,are covered by vast,wild forests.The mountainous region has chilly,snowy weather for about nine months of the year.The lowest temperature is below-40 C in...The Changbai Mountains,in Northeast China's Jilin Province,are covered by vast,wild forests.The mountainous region has chilly,snowy weather for about nine months of the year.The lowest temperature is below-40 C in winter.In 2005,Huang Yi,a native of Southwest China's Sichuan Province,relocated to the Changbai Mountains,to work at the Mount Hengshan frontier inspection station.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
Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have un...Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have unique chemical and physical properties that allow np-Fe^(0) to form at a lower initial reaction temperature.Through the insitu heating experiment of ilmenite in the Chang'e-5 sample,it was found that ilmenite can form np-Fe^(0) at 400℃under high vacuum(10-6 Pa).This fills in the missing information on the lowest measured temperature at which ilmenite forms np-Fe^(0).At 400-800℃,only np-Fe^(0) and vesicles were formed without new Ti-rich minerals.At the same time,thermodynamic calculations showed that decomposition of ilmenite occurs in two stages.The experiments correspond to the initial stage of ilmenite thermal decomposition under high vacuum.The study explains the thermal decomposition reaction of ilmenite in a vacuum environment,provides a reference for the minimum measured temperature required for the formation of np-Fe^(0),and further improves the formation mechanism of np-Fe^(0).展开更多
To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the ...To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.展开更多
Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns(SWPs),however,the consistency of different classification methods is rarely examine...Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns(SWPs),however,the consistency of different classification methods is rarely examined.In this study,we apply two widely-used objective methods,the self-organizing map(SOM)and K-means clustering analysis,to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022.We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities.In the case of classifying six SWPs,the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods,and the difference in themean frequency of each SWP is less than 7%.The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature,lower cloud cover,relative humidity,and wind speed,and stronger subsidence compared to climatology mean.We find that during 2015-2022,the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 days/year,faster than the increases in the ozone exceedance days(3.0 days/year).The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6.In particular,the significant increase in ozone-favorable SWPs in 2022,especially the Subtropical High type which typically occurs in September,is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022.Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.展开更多
Extreme ozone pollution events(EOPEs)are associated with synoptic weather patterns(SWPs)and pose severe health and ecological risks.However,a systematic investigation of themeteorological causes,transport pathways,and...Extreme ozone pollution events(EOPEs)are associated with synoptic weather patterns(SWPs)and pose severe health and ecological risks.However,a systematic investigation of themeteorological causes,transport pathways,and source contributions to historical EOPEs is still lacking.In this paper,the K-means clustering method is applied to identify six dominant SWPs during the warm season in the Yangtze River Delta(YRD)region from 2016 to 2022.It provides an integrated analysis of the meteorological factors affecting ozone pollution in Hefei under different SWPs.Using the WRF-FLEXPART model,the transport pathways(TPPs)and geographical sources of the near-surface air masses in Hefei during EOPEs are investigated.The results reveal that Hefei experienced the highest ozone concentration(134.77±42.82μg/m^(3)),exceedance frequency(46 days(23.23%)),and proportion of EOPEs(21 instances,47.7%)under the control of peripheral subsidence of typhoon(Type 5).Regional southeast winds correlated with the ozone pollution in Hefei.During EOPEs,a high boundary layer height,solar radiation,and temperature;lowhumidity and cloud cover;and pronounced subsidence airflow occurred over Hefei and the broader YRD region.The East-South(E_S)patterns exhibited the highest frequency(28 instances,65.11%).Regarding the TPPs and geographical sources of the near-surface air masses during historical EOPEs.The YRD was the main source for land-originating air masses under E_S patterns(50.28%),with Hefei,southern Anhui,southern Jiangsu,and northern Zhejiang being key contributors.These findings can help improve ozone pollution early warning and control mechanisms at urban and regional scales.展开更多
Tafoni are globally developed on cliffy slopes,and many of them are favorable places for the preservation of stone historical relics.However,the characteristics and formation processes of tafoni in the Loess Plateau a...Tafoni are globally developed on cliffy slopes,and many of them are favorable places for the preservation of stone historical relics.However,the characteristics and formation processes of tafoni in the Loess Plateau are yet to be understood.This paper studied the features of the tafoni on conglomerate slopes in Huoshizhai National Geopark of Ningxia Hui Autonomous Region and discussed its formation processes by field investigation and morphometry,insitu relative humidity(RH)measurement,salt chemistry and X-ray fluorescence spectrometer(XRF)experiments of 24 samples.The bedrock of the tafoni is dominated by reddish fluvial conglomerates of the Lower Cretaceous Heshangpu Formation with abundant chemically unstable components including feldspars,lithic fragments,and calcite cements.The RH values vary from 5%to 100%,but the backwalls of the tafoni have higher RH values than outer surfaces.The more moisture on the backwalls is possibly generated by water influx from the rock interior,resulting in more salt precipitation on the backwalls.As a result,the backwalls have been subject to predominant salt weathering.The dominant salts involved in salt weathering are probably derived from the dissolution of the salt interbeds in the basin,although the chemical dissolution of the unstable components such as feldspars,lithic fragments,and calcite cements might have produced small amounts of salts.The salt types dominantly include nitrates,sulfates,and halite.In the progression of tafoni,the moisture maintenance on the backwalls gives rise to the accretion of salts,which in turn enhance the weathering rates of the backwalls.As a result,the volumes of the tafoni have become enlarged owing to inward growth and coalescence of adjacent smaller ones.展开更多
Weathering steel exhibits excellent corrosion resistance and is widely used in bridges,towers,railways,highways,and other engineering projects that are exposed to the atmosphere for long periods of time.However,before...Weathering steel exhibits excellent corrosion resistance and is widely used in bridges,towers,railways,highways,and other engineering projects that are exposed to the atmosphere for long periods of time.However,before the formation of stable rust layers,weathering steel is prone to liquid rust sagging and spattering,leading to environmental pollution and city appearance concerns.These factors limit the application and development of weathering steel.In this study,a rapid and environmentally friendly method was de-veloped by introducing alloying elements,specifically investigating the role of Sn in the rapid stabilization of rust layers in marine atmo-spheric environments.The rust layer formed on weathering low-alloy steel exposed to prolonged outdoor conditions and laboratory im-mersion experiments was explored using electron probe micro-analyzer(EPMA),micro-Raman,X-ray photoelectron spectroscopy(XPS),and electrochemical measurements.Results showed an optimal synergistic effect between Sn and Cr,which facilitated the accelerated densification of the rust layer.This beneficial effect enhanced the capability of the rust layer to resist Cl^(-)erosion and improved the protec-tion performance of the rust layer.展开更多
Black soil is essential for maintaining regional food security and promoting global agricultural production.Understanding the weathering process of parent material and the accumulation of organic carbon is crucial to ...Black soil is essential for maintaining regional food security and promoting global agricultural production.Understanding the weathering process of parent material and the accumulation of organic carbon is crucial to comprehending the developmental history and future trends of black soil,especially against the background of large-scale global cultivation and climate change.Although the importance of black soil formation and evolution cannot be ignored,the relevant research is still very scarce.In this study,a typical eight-meter-deep soil core was collected from the Keshan area of the Songnen Plain,Northeast China,where surface black soil developed on paleo-sediments.Using^(14)C dating,the formation age of the black soil was determined.Based on the characteristics of the geochemical composition,grain size and the magnetic susceptibility of the sediments,it was demonstrated that the black soil and its parent material originated from reworked loess.Furthermore,the mass transfer coefficient(τ)of some elements was determined,in order to explore the soil weathering process.By calculating the transported amount of alkaline and alkaline-earth elements,the weathering rate of parent material to black soil was found to be weak,at 0.16 kEq·ha^(-1)·year^(-1).Combining the results of dating and carbon density in the different layers of black soil,the accumulation rate of organic carbon was determined as follows:rapidly increasing in the initial period of 13.2-2.2 ka,reaching its maximum average value of 34.0 g·cm^(-2)·a^(-1)at 2.2-0.8 ka,then showing a decreasing trend with an average value of-77.5 g·cm^(-2)·a^(-1).Compared with regional climate change,Keshan black soil has developed under a colder and wetter climate during the Holocene.Predictably,ongoing global warming may lead to the degradation of black soils in the Songnen Plain,as well as in other regions.Our results will enrich geological knowledge of black soil formation and future evolutionary trends.展开更多
This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has ...This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.展开更多
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
基金Supported by the National Key R&D Program of China(2018YFB0605700).
文摘TiO2 pigments are typically coated with inert layers to suppress the photocatalytic activity and improve the weatherability. However, the traditional inert layers have a lower refractive index compared to TiO2, and therefore reduce the lightening power of TiO2. In the present work, a uniform, amorphous, 2.9-nm-thick TiO2 protective layer was deposited onto the surface of anatase TiO2 pigments according to pulsed chemical vapor deposition at room temperature, with Ti Cl4 as titanium precursor. Amorphous TiO2 coating layers exhibited poor photocatalytic activity, leading to a boosted weatherability. Similarly, this coating method is also effective for TiO2 coating with amorphous SiO2 and SnO2 layers. However, the lightening power of amorphous TiO2 layer is higher than those of amorphous SiO2 and SnO2 layers. According to the measurements of photoluminescence lifetime, surface photocurrent density, charge-transfer resistance, and electron spin resonance spectroscopy, it is revealed that the amorphous layer can prevent the migration of photogenerated electrons and holes onto the surface, decreasing the densities of surface electron and hole, and thereby suppress the photocatalytic activity.
基金financially supported by the External Collaboration Fund(No.XM2022FH5079)。
文摘Although inorganic pigments in common spectral tuning materials show good weatherability and heat resistance,the limited color choices,weak coloring power,poor dispersibility,and a possibility of toxicity limit their development.On the basis of organic pigments which possess a wide range of colors,high coloring power,good transparency,and high safety,herein,the modified pigment and biomimetic coating with improved weatherability,especially ultraviolet(UV)resistance(from 2 to 6 days),was achieved by intercalating acid green 25(AG25)pigment into Mg/Al-layered double hydroxides(Mg/Al-LDH).Furthermore,the heat resistance of AG25 was also significantly increased.Moreover,the spectral stability of pigments after heat treatment is superior with almost unchanged spectral profile and green reflection peak.The formation of strong N-H bonds and the S-M(Mg,Al)bonds between Mg/Al-LDH laminates and AG25 molecules contributes to the improvement.This work shows potential for biomimetic leaf materials in respect of reflective spectra stability.
文摘Small things can show a person's true character Find lt What was the weather like when the girl came to the castle door?nce upon a time,there was a prince.He wanted to marry a real princess.He traveled all around the world looking for one.
基金funded by the National Natural Science Foundation of China(42571311).
文摘Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.
基金supported by the National Natural Science Foundation of China[grant number 62376217]the Young Elite Scientists Sponsorship Program by CAST[grant number 2023QNRC001]the Joint Research Project for Meteorological Capacity Improvement[grant number 24NLTSZ003]。
文摘Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge.In this work,three key solutions are proposed:(1)motivated by the need to improve model performance in data-scarce regional forecasting scenarios,the authors innovatively apply semantic segmentation models,to better capture spatiotemporal features and improve prediction accuracy;(2)recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness,a novel learnable Gaussian noise mechanism is introduced that allows the model to adaptively optimize perturbations for different locations,ensuring more effective learning;and(3)to address the issue of error accumulation in autoregressive prediction,as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction,the authors propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance.The method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition.Ablation experiments further validate the effectiveness of each component,highlighting their contributions to enhancing prediction performance.
基金supported by Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the Korean government(MSIT)(No.2019-0-01842,Artificial Intelligence Graduate School Program(GIST))supported by Korea Planning&Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)(RS-2025-25448249+1 种基金Automotive Industry Technology Development(R&D)Program)supported by the Regional Innovation System&Education(RISE)programthrough the(Gwangju RISE Center),funded by the Ministry of Education(MOE)and the Gwangju Metropolitan City,Republic of Korea(2025-RISE-05-001).
文摘In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA0430201)the Science and Technology Plan Project of Guizhou Province(Grant No.QKHJC-ZD[2025]035)+2 种基金the Geological Exploration Fund of Guizhou Province(Grant No.2024-2)the National Natural Science Foundation of China(Grant No.U23A2027)the CAS Hundred Talents Program to XWH.
文摘Scandium(Sc)is a critical metal with increasing demand driven by its applications in high-technology industries.The Late Permian claystones in the Sichuan-Yunnan-Guizhou region of southwestern(SW)China represent a potentially new and important Sc resource.This study investigates the distribution,occurrence,and source of Sc in claystones from the Weining area in western Guizhou,and discusses its precipitation mechanism.The sedimentary succession primarily comprises successive layers of ferric,aluminous,carbonaceous,tuffaceous,and silty clastic claystones from bottom to top.Scandium is mainly enriched in ferric claystones,with concentrations reaching up to 56 ppm,while other types contain less than 30 ppm.The principal Sc-hosting minerals include goethite,anatase,brookite,zircon,and xenotime.High-resolution transmission electron microscopy indicates that Sc(~0.9 wt%)is homogeneously distributed within nanometer-scale zircon.The presence of xenotime inclusions within zircon suggests a sedimentary origin.Rare earth element and platinum-group element patterns,together with trace element ratios,indicate that Sc in ferric horizons was derived from intense subaerial weathering of high-Ti basalts and precipitated under oxygenated aquatic conditions.Subsequent multi-stage hydrodynamic processes,including marine transgression-regression and fluvial reworking,facilitated Sc remobilization via mineral dissolution-reprecipitation,ultimately leading to further enrichment within ferric horizons through downward migration.
基金supported by the National Natural Science Foundation of China(Grant Nos.42077242 and 42171407)the Graduate Innovation Fund of Jilin University.
文摘Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.
文摘The Changbai Mountains,in Northeast China's Jilin Province,are covered by vast,wild forests.The mountainous region has chilly,snowy weather for about nine months of the year.The lowest temperature is below-40 C in winter.In 2005,Huang Yi,a native of Southwest China's Sichuan Province,relocated to the Changbai Mountains,to work at the Mount Hengshan frontier inspection station.
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.
基金funding support from the National Natural Science Foundation of China(Grant Nos.42441804,42403043,42273042,42303041,and U24A2008)Youth Innovation Promotion Association CAS awards+5 种基金"From 0 to 1"Original Exploration Cultivation Project,Institute of Geochemistry,Chinese Academy of Sciences(Grant No.DHSZZ2023.3)Bureau of Frontier Sciences and Basic Research,CAS,(Grant No.QYJ-2025-0103)Guizhou Provincial Foundation for Excellent Scholars Program(Grant No.GCC[2023]088)Provincial Key Research and Development(R&D)Plan Projects of Heilongjiang(Grant No.2024ZXDXB52)The Innovation and Development Fund of Science and Technology of Institute of Geochemistry,Chinese Academy of SciencesGuizhou Province Basic Research Program Project(QKHJC-ZK[2023]-General 473)。
文摘Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have unique chemical and physical properties that allow np-Fe^(0) to form at a lower initial reaction temperature.Through the insitu heating experiment of ilmenite in the Chang'e-5 sample,it was found that ilmenite can form np-Fe^(0) at 400℃under high vacuum(10-6 Pa).This fills in the missing information on the lowest measured temperature at which ilmenite forms np-Fe^(0).At 400-800℃,only np-Fe^(0) and vesicles were formed without new Ti-rich minerals.At the same time,thermodynamic calculations showed that decomposition of ilmenite occurs in two stages.The experiments correspond to the initial stage of ilmenite thermal decomposition under high vacuum.The study explains the thermal decomposition reaction of ilmenite in a vacuum environment,provides a reference for the minimum measured temperature required for the formation of np-Fe^(0),and further improves the formation mechanism of np-Fe^(0).
基金National Key R&D Program of China of the 13th Five-Year Plan(No.2018YFD1100704)。
文摘To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.
基金supported by the Guangdong Basic and Applied Basic Research project (No.2020B0301030004)the Key-Area Research and Development Program of Guangdong Province (No.2020B1111360003)+1 种基金the National Natural Science Foundation of China (No.42105103)the Guangdong Basic and Applied Basic Research Foundation (No.2022A1515011554).
文摘Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns(SWPs),however,the consistency of different classification methods is rarely examined.In this study,we apply two widely-used objective methods,the self-organizing map(SOM)and K-means clustering analysis,to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022.We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities.In the case of classifying six SWPs,the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods,and the difference in themean frequency of each SWP is less than 7%.The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature,lower cloud cover,relative humidity,and wind speed,and stronger subsidence compared to climatology mean.We find that during 2015-2022,the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 days/year,faster than the increases in the ozone exceedance days(3.0 days/year).The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6.In particular,the significant increase in ozone-favorable SWPs in 2022,especially the Subtropical High type which typically occurs in September,is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022.Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,and 41975037)the National Key Research and Development Programof China(No.2022YFC3700303).
文摘Extreme ozone pollution events(EOPEs)are associated with synoptic weather patterns(SWPs)and pose severe health and ecological risks.However,a systematic investigation of themeteorological causes,transport pathways,and source contributions to historical EOPEs is still lacking.In this paper,the K-means clustering method is applied to identify six dominant SWPs during the warm season in the Yangtze River Delta(YRD)region from 2016 to 2022.It provides an integrated analysis of the meteorological factors affecting ozone pollution in Hefei under different SWPs.Using the WRF-FLEXPART model,the transport pathways(TPPs)and geographical sources of the near-surface air masses in Hefei during EOPEs are investigated.The results reveal that Hefei experienced the highest ozone concentration(134.77±42.82μg/m^(3)),exceedance frequency(46 days(23.23%)),and proportion of EOPEs(21 instances,47.7%)under the control of peripheral subsidence of typhoon(Type 5).Regional southeast winds correlated with the ozone pollution in Hefei.During EOPEs,a high boundary layer height,solar radiation,and temperature;lowhumidity and cloud cover;and pronounced subsidence airflow occurred over Hefei and the broader YRD region.The East-South(E_S)patterns exhibited the highest frequency(28 instances,65.11%).Regarding the TPPs and geographical sources of the near-surface air masses during historical EOPEs.The YRD was the main source for land-originating air masses under E_S patterns(50.28%),with Hefei,southern Anhui,southern Jiangsu,and northern Zhejiang being key contributors.These findings can help improve ozone pollution early warning and control mechanisms at urban and regional scales.
基金financially supported by the National Natural Science Foundation of China(Grant No.42361002)the Fund of Ningxia Hui Autonomous Region(Grant No.2022AAC03665).
文摘Tafoni are globally developed on cliffy slopes,and many of them are favorable places for the preservation of stone historical relics.However,the characteristics and formation processes of tafoni in the Loess Plateau are yet to be understood.This paper studied the features of the tafoni on conglomerate slopes in Huoshizhai National Geopark of Ningxia Hui Autonomous Region and discussed its formation processes by field investigation and morphometry,insitu relative humidity(RH)measurement,salt chemistry and X-ray fluorescence spectrometer(XRF)experiments of 24 samples.The bedrock of the tafoni is dominated by reddish fluvial conglomerates of the Lower Cretaceous Heshangpu Formation with abundant chemically unstable components including feldspars,lithic fragments,and calcite cements.The RH values vary from 5%to 100%,but the backwalls of the tafoni have higher RH values than outer surfaces.The more moisture on the backwalls is possibly generated by water influx from the rock interior,resulting in more salt precipitation on the backwalls.As a result,the backwalls have been subject to predominant salt weathering.The dominant salts involved in salt weathering are probably derived from the dissolution of the salt interbeds in the basin,although the chemical dissolution of the unstable components such as feldspars,lithic fragments,and calcite cements might have produced small amounts of salts.The salt types dominantly include nitrates,sulfates,and halite.In the progression of tafoni,the moisture maintenance on the backwalls gives rise to the accretion of salts,which in turn enhance the weathering rates of the backwalls.As a result,the volumes of the tafoni have become enlarged owing to inward growth and coalescence of adjacent smaller ones.
基金support of the National Natural Science Foundation of China(No.52171063).
文摘Weathering steel exhibits excellent corrosion resistance and is widely used in bridges,towers,railways,highways,and other engineering projects that are exposed to the atmosphere for long periods of time.However,before the formation of stable rust layers,weathering steel is prone to liquid rust sagging and spattering,leading to environmental pollution and city appearance concerns.These factors limit the application and development of weathering steel.In this study,a rapid and environmentally friendly method was de-veloped by introducing alloying elements,specifically investigating the role of Sn in the rapid stabilization of rust layers in marine atmo-spheric environments.The rust layer formed on weathering low-alloy steel exposed to prolonged outdoor conditions and laboratory im-mersion experiments was explored using electron probe micro-analyzer(EPMA),micro-Raman,X-ray photoelectron spectroscopy(XPS),and electrochemical measurements.Results showed an optimal synergistic effect between Sn and Cr,which facilitated the accelerated densification of the rust layer.This beneficial effect enhanced the capability of the rust layer to resist Cl^(-)erosion and improved the protec-tion performance of the rust layer.
基金financially supported by the Science and Technology Innovation Foundation of the Command Center of Integrated Natural Resources Survey Center(KC20230002)the China Geological Survey Project(DD20230471,DD20220855 and DD20243282)+1 种基金the National Natural Science Foundation of China(41872100)the National Key R&D Plan(2022YFC2903402)。
文摘Black soil is essential for maintaining regional food security and promoting global agricultural production.Understanding the weathering process of parent material and the accumulation of organic carbon is crucial to comprehending the developmental history and future trends of black soil,especially against the background of large-scale global cultivation and climate change.Although the importance of black soil formation and evolution cannot be ignored,the relevant research is still very scarce.In this study,a typical eight-meter-deep soil core was collected from the Keshan area of the Songnen Plain,Northeast China,where surface black soil developed on paleo-sediments.Using^(14)C dating,the formation age of the black soil was determined.Based on the characteristics of the geochemical composition,grain size and the magnetic susceptibility of the sediments,it was demonstrated that the black soil and its parent material originated from reworked loess.Furthermore,the mass transfer coefficient(τ)of some elements was determined,in order to explore the soil weathering process.By calculating the transported amount of alkaline and alkaline-earth elements,the weathering rate of parent material to black soil was found to be weak,at 0.16 kEq·ha^(-1)·year^(-1).Combining the results of dating and carbon density in the different layers of black soil,the accumulation rate of organic carbon was determined as follows:rapidly increasing in the initial period of 13.2-2.2 ka,reaching its maximum average value of 34.0 g·cm^(-2)·a^(-1)at 2.2-0.8 ka,then showing a decreasing trend with an average value of-77.5 g·cm^(-2)·a^(-1).Compared with regional climate change,Keshan black soil has developed under a colder and wetter climate during the Holocene.Predictably,ongoing global warming may lead to the degradation of black soils in the Songnen Plain,as well as in other regions.Our results will enrich geological knowledge of black soil formation and future evolutionary trends.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42422502 and 42275038)the China Meteorological Administration Climate Change Special Program (Grant No.QBZ202306)funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)。
文摘This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
