As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
Microplastics(MPs)pollution has emerged as a critical global environmental issue,for which rivers serve as key conduits for the transport of MPs from land to ocean.There remained a lack of clarity regarding the charac...Microplastics(MPs)pollution has emerged as a critical global environmental issue,for which rivers serve as key conduits for the transport of MPs from land to ocean.There remained a lack of clarity regarding the characteristics and transport patterns of MPs pollution in diverse environmental media and seasons within a river basin.The Jiulong River basin in Fujian,southeast China was studied as case,whose spatial-temporal distribution,pollution characteristics,and transport dynamics of MPs in both surface water and groundwater were analyzed.Additionally,the features of MPs in different land use types during the dry season were examined.Results show that in wet season,the abundance of MPs in river water varied from 840 to 12300 p/m^(3),with an average of 3920 p/m^(3);in groundwater,the range was 740-1820 p/m^(3),averaging 1107 p/m^(3);and from 68 to 951 p/kg,with an average value of 265 p/kg in the soil(dry weight).In dry season,levels of MPs in river water ranged from 580 to 8880 p/m^(3),with an average of 4034 p/m^(3);groundwater exhibited a range of 860-14980 p/m^(3),averaging 3453 p/m^(3).Fibers consistently dominated the morphology of MPs,of which polyethylene terephthalate was identified as the predominant composition in each environmental medium.Our findings underscore the spatial and temporal variability in distribution and contamination characteristics of MPs across different media.Notably,MPs abundance in river water and groundwater exhibited a seasonal pattern,being higher in levels in dry season than in wet season.The downstream transport of MPs was facilitated by surface runoff,in which MPs in groundwater and surface water could complement to each other.Furthermore,population density and human activities were identified as influential factors on the distribution and abundance of MPs.This study revealed the order of magnitude of difference in annual estimates of MPs entering the sea among different models.Additionally,the interception volume by mangrove forest in the Jiulong River estuary was estimated approximately 1.51×10^(10)MPs particles per year.Ecological interception shall be considered when estimating the fluxes of MPs into the sea.展开更多
[Objective] This paper aimed to understand the area change and distribu- tion of medium-low yield farmland, and offered basis to the improvement of mediumlow farmland and its increase of grain production in Tianjin. [...[Objective] This paper aimed to understand the area change and distribu- tion of medium-low yield farmland, and offered basis to the improvement of mediumlow farmland and its increase of grain production in Tianjin. [Method] Based on the statistical date of Tianjin and its relevant counties and districts, the yield standard was set up to classify high-yield, medium-yield and low-yield farmland in Tianjin. The author analyzed area change of medium-low yield farmland in six agricultural counties and districts （including Jixian County, Wuqing District, Baodi District, Ninghe County, Jinghai County and Dagang district of Binghai New Area） from 1980 to 2010. [Result] The results showed that the average yield of grain rose from 2 445 kg/hm^2 in 1980 to 5 130 kg/hm^2 in 2010, increasing 109.82%. The area of mediumlow yield farmland was reduced from 291 250.13 hm^2 in 1985 to 76 489.87 hm^2 in 2010, coming down 74%. In Tianjin, the area of medium-low yield farmland of 2010 accounted for 19% of the total farmland, of which the ratios of medium-low yield farmland of Jinghai County, Jixian County, Dagang district of Binghai New Area, Wuqing District, Baodi District and Ninghe County were 43.12%, 18.59%, 17.23%, 14.01%, 7.05% and 0, respectively. Low soil nutrient content, drought and water shortage, as well as soil salinization were the main yield limiting factors to mediumlow yield farmland in Tianjin in 2010. [Conclusion] The countermeasures to improve the medium-low yield farmland were proposed, involving enhancing the investment of the government, strengthening the construction of water conservancy infrastructure, further improving the soil fertility, as well as saline and alkaline land, optimizing the farming system and planting drought and salt tolerance crops, etc.展开更多
To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produce...To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.展开更多
Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most species...Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most speciesrich genus in the Bambusoideae subfamily.Based on the distribution data of 46 species and 20 environmental variables,we used the MaxEnt model combined with ArcGIS calculations to simulate current and future potential richness distributions under three distinct CO_(2) emission scenarios.The results showed that the MaxEnt model had a good predictive ability,with a mean area under the working characteristic curve(AUC value)of 0.91 for all species.The main environmental variables that impacted the future distribution of most Phyllostachys species were elevation,variations of seasonal precipitation,and mean diurnal range.Phyllostachys species are currently concentrated in southeastern China.Under future climate projections,18 species exhibited significant habitat contraction across three or more future climate scenarios,but suitable habitats for other species will expand.This enhancement is most pronounced under the extreme climate scenario(2090s-SSP585),primarily driven by high species gains contributing to elevated turnover values across scenarios.The center of maximum richness will progressively shift southwestward over time.Predictive modeling of Phyllostachys richness distribution dynamics under climate change enhances our understanding of its biogeography and informs strategic introduction programs to bamboo management and augments China’s carbon sequestration capacity.展开更多
Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges...Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges.There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning.Therefore,this study integrated 4 key biodiversity indices including species richness(SR),phylogenetic diversity(PD),threatened species richness(TSR),and endemic species richness(ESR)to map species diversity distribution patterns,identify conservation gaps,and elucidate their effects of climatic factors.This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan.The central–western mountains(specifically the Gissar-Darvasian and Zeravshanian regions)emerge as irreplaceable biodiversity hotspots.However,we found a severe spatial mismatch between these priority areas and the existing protected areas(PAs).Protection coverage for all hotspots was alarmingly low,ranging from 31.00%to 38.00%.Consequently,a critical 64.80%of integrated priority areas fall outside of the current PAs,representing a major conservation gap.This study identified precipitation seasonality and isothermality as the principal drivers,collectively explaining over 50.00%of the diversity variation and suggesting high vulnerability to hydrological shifts.Furthermore,we detected significant geographic sampling bias in the public biodiversity databases,with the most critical hotspot being systematically under-sampled.This study provides a robust scientific basis for conservation action,highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys.These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3(“30×30 Protection”).展开更多
Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in a...Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in alpine mountains with climate change.Hence,94 samples of river water were collected from 2018 to 2020 in the headwaters of the Shule River Basin to assess the nutrients spatiotemporal distribution and combined ap-proach of water quality index to assess water quality and potential sources.The findings depict that high nutrient concentrations were found to coincide with snowmelt and glacial meltwater and rainfall recharge periods,while total flux peaked from June to September due to increased runoff.Notably,total nitrogen(TN)concentrations were significantly higher near the town,primarily attributed to the replenishment of nitrate(NO_(3)^(‒)-N)from live-stock manure.The high total P(TP)was near the glacier,which was attributed to the transportation of glacial sediments into the river,and pH was another critical factor.N was the primary nutrient limiting factor for the growth of phytoplankton in river water.Although the migration and transport of nutrients have altered with climate change,river water quality is good in alpine mountains based on an overall evaluation.These findings contribute to enriching nutrient datasets and highlight the importance of water resource management and water quality assessment in sensitive and fragile alpine mountains.展开更多
Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated...Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.展开更多
Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ...Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.展开更多
Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces th...Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.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
Ceramic cells promise ideal energy conversion and storage devices,making the development of efficient and robust air electrodes crucial for their application.In this study,a Ba_(0.4)Sr_(0.5)Cs_(0.1)Co_(0.7)Fe_(0.2)Nb_...Ceramic cells promise ideal energy conversion and storage devices,making the development of efficient and robust air electrodes crucial for their application.In this study,a Ba_(0.4)Sr_(0.5)Cs_(0.1)Co_(0.7)Fe_(0.2)Nb_(0.1)O_(3−δ)(BSCCFN)air electrode,based on Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3−δ)(BSCF),is designed using a perovskite A-B-site ionic Lewis acid strength(ISA)polarization distribution strategy and is successfully applied in both oxygen-ion conducting solid oxide fuel cells(O-SOFCs)and proton-conducting reversible protonic ceramic cells(R-PCCs).When BSCCFN is used as the air electrode in O-SOFCs,a peak power density(PPD)of 1.45 W cm^(−2)is achieved at 650°C,whereas in R-PCCs,a PPD of 1.13 W cm^(−2)and a current density of−1.8 A cm^(−2)at 1.3 V are achieved at the same temperature and show stable reversibility over 100 h.Experimental measurements and theoretical calculations demonstrate that low-ISA Cs+doping accelerates the reaction kinetics of both oxygen ions and protons,while high-ISA Nb^(5+)doping enhances electrode stability.The synergistic effect of Cs^(+)and Nb^(5+)co-doping in the BSCCFN electrode lies in the ISA polarization distribution,which weakens the Co/Fe–O bond covalency,thereby promoting oxygen vacancy formation and facilitating the conduction of oxygen ions and protons.展开更多
Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting d...Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construc...Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construct the展开更多
With basic information from 8353 archaeological sites, this study describes a holistic spatial-temporal distribution pattern of archaeological sites of the prehistoric culture sequence from 9.5 ka BP (ka BP = thousand...With basic information from 8353 archaeological sites, this study describes a holistic spatial-temporal distribution pattern of archaeological sites of the prehistoric culture sequence from 9.5 ka BP (ka BP = thousands of years before 0 BP, where "0 BP" is defined as the year AD 1950) to 2.3 ka BP in the region that extends from the Yanshan Mountains to the Liaohe River Plain(i.e., the Yan-Liao region) in northern China. Based on spatial statistics analysis – including the spatial density of the sites and Geographic Information System nearest-neighbour analysis, combined with a review of environmental and climatic data – this paper analyses cultural evolution, the spatial-temporal features of the archaeological sites and human activities against the backdrop of climatic and environmental changes in this region. The results reveal that prehistoric cultural evolution in the Yan-Liao region is extensively influenced by climatic and environmental changes. The Xinglongwa, Zhaobaogou and Fuhe cultures, which primarily developed during a habitable period from 8.5 ka BP to 6.0 ka BP with strong summer monsoons, have similar maximum density values, spatial patterns and subsistence strategies dominated by hunting-gathering. Significant changes occurred in the Hongshan and Lower Xiajiadian cultures, with a significant increase in numbers and densities of sites and a slump in average nearest-neighbour ratio when the environment began to deteriorate starting in 6.0 ka BP. Additionally, with the onset of a weak summer monsoon and the predominance of primitive agriculture, sites of these two cultures present a different type of concentric circle-shaped pattern in space. As the environment continuously deteriorated with increasing aridity and the spread of steppe, more sites were distributed towards the south, and primitive agriculture was replaced by livestock husbandry in the Upper Xiajiadian culture. The most densely populated areas of the studied cultures are centralized within a limited area. The Laohahe River and Jiaolaihe River basins formed the core area in which most archaeological sites were distributed during the strong summer monsoon period and the first few thousand years of the weak summer monsoon period.展开更多
Grain composition plays a vital role in impact pressure of debris flow. Current approaches treat debris flow as uniform fluid and almost ignore its granular effects. A series of flume experiments have been carried out...Grain composition plays a vital role in impact pressure of debris flow. Current approaches treat debris flow as uniform fluid and almost ignore its granular effects. A series of flume experiments have been carried out to explore the granular influence on the impact process of debris flow by using a contact surface pressure gauge sensor(Tactilus~?, produced by Sensor Products LLC). It is found that the maximum impact pressure for debris flow of low density fluctuates drastically with a long duration time while the fluctuation for flow of high density is short in time, respectively presenting logarithmic and linear form in longitudinal attenuation. This can be ascribed to the turbulence effect in the former and grain collisions and grainfluid interaction in the latter. The horizontal distribution of the impact pressure can be considered as the equivalent distribution. For engineering purposes, the longitudinal distribution of the pressure can be generalized to a triangular distribution, from which a new impact method considering granular effects is proposed.展开更多
The variation of the atmospheric Carbon Dioxide （CO2） concentration plays an important role in global cli- mate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around...The variation of the atmospheric Carbon Dioxide （CO2） concentration plays an important role in global cli- mate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite （Greenhouse Gases Observing Satellite）. In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate charac- teristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON （Total Carbon Column Observing Network） observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 da- ta can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 oomv in the 0-40？N latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concen- tration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in win- ter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an av- erage concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentra- tion has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.展开更多
Earthquakes exhibit clear clustering on the earth. It is important to explore the spatial-temporal characteristics of seismicity clusters and their spatial heterogeneity. We analyze effects of plate space, tectonic st...Earthquakes exhibit clear clustering on the earth. It is important to explore the spatial-temporal characteristics of seismicity clusters and their spatial heterogeneity. We analyze effects of plate space, tectonic style, and their interaction on characteristic of cluster.Based on data of earthquakes not less than moment magnitude(M_w) 5.6 from 1960 to 2014, this study used the spatial-temporal scan method to identify earthquake clusters. The results indicate that seismic spatial-temporal clusters can be classified into two types based on duration: persistent clusters and burst clusters. Finally, we analysed the spatial heterogeneity of the two types. The main conclusions are as follows: 1) Ninety percent of the persistent clusters last for 22-38 yr and show a high clustering likelihood;ninety percent of the burst clusters last for 1-1.78 yr and show a high relative risk. 2) The persistent clusters are mainly distributed in interplate zones, especially along the western margin of the Pacific Ocean. The burst clusters are distributed in both intraplate and interplate zones, slightly concentrated in the India-Eurasia interaction zone. 3) For the persistent type, plate interaction plays an important role in the distribution of the clusters’ likelihood and relative risk. In addition, the tectonic style further enhances the spatial heterogeneity. 4) For the burst type,neither plate activity nor tectonic style has an obvious effect on the distribution of the clusters’ likelihood and relative risk. Nevertheless,interaction between these two spatial factors enhances the spatial heterogeneity, especially in terms of relative risk.展开更多
Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral dep...Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral deposits are spatially distributed mainly in the Altay and Southern Great Xingán Range regions in the Central Asian orogenic belt;in the Middle Qilian,South Qinling and East Qinling mountains regions in the Qilian-Qinling-Dabie orogenic belt;in the Western Sichuan and Bailongshan-Dahongliutan regions in the Kunlun-Songpan-Garze orogenic belt,and in the Northeastern Jiangxi,Northwestern Jiangxi,and Southern Hunan regions in South China.Major ore-forming epochs include Indosinian(mostly 200-240 Ma,in particular in western China)and the Yanshanian(mostly 120-160 Ma,in particular in South China).In addition,Bayan Obo,Inner Mongolia,northeastern China,with a complex formation history,hosts the largest REE and Nb deposits in China.There are six major rare metal mineral deposit types in China:Highly fractionated granite;Pegmatite;Alkaline granite;Carbonatite and alkaline rock;Volcanic;and Hydrothermal types.Two further types,namely the Leptynite type and Breccia pipe type,have recently been discovered in China,and are represented by the Yushishan Nb-Ta-(Zr-Hf-REE)and the Weilasituo Li-Rb-Sn-W-Zn-Pb deposits.Several most important controlling factors for rare metal mineral deposits are discussed,including geochemical behaviors and sources of the rare metals,highly evolved magmatic fractionation,and structural controls such as the metamorphic core complex setting,with a revised conceptual model for the latter.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金Supported by the National Natural Science Foundation of China(No.41961144011)。
文摘Microplastics(MPs)pollution has emerged as a critical global environmental issue,for which rivers serve as key conduits for the transport of MPs from land to ocean.There remained a lack of clarity regarding the characteristics and transport patterns of MPs pollution in diverse environmental media and seasons within a river basin.The Jiulong River basin in Fujian,southeast China was studied as case,whose spatial-temporal distribution,pollution characteristics,and transport dynamics of MPs in both surface water and groundwater were analyzed.Additionally,the features of MPs in different land use types during the dry season were examined.Results show that in wet season,the abundance of MPs in river water varied from 840 to 12300 p/m^(3),with an average of 3920 p/m^(3);in groundwater,the range was 740-1820 p/m^(3),averaging 1107 p/m^(3);and from 68 to 951 p/kg,with an average value of 265 p/kg in the soil(dry weight).In dry season,levels of MPs in river water ranged from 580 to 8880 p/m^(3),with an average of 4034 p/m^(3);groundwater exhibited a range of 860-14980 p/m^(3),averaging 3453 p/m^(3).Fibers consistently dominated the morphology of MPs,of which polyethylene terephthalate was identified as the predominant composition in each environmental medium.Our findings underscore the spatial and temporal variability in distribution and contamination characteristics of MPs across different media.Notably,MPs abundance in river water and groundwater exhibited a seasonal pattern,being higher in levels in dry season than in wet season.The downstream transport of MPs was facilitated by surface runoff,in which MPs in groundwater and surface water could complement to each other.Furthermore,population density and human activities were identified as influential factors on the distribution and abundance of MPs.This study revealed the order of magnitude of difference in annual estimates of MPs entering the sea among different models.Additionally,the interception volume by mangrove forest in the Jiulong River estuary was estimated approximately 1.51×10^(10)MPs particles per year.Ecological interception shall be considered when estimating the fluxes of MPs into the sea.
文摘[Objective] This paper aimed to understand the area change and distribu- tion of medium-low yield farmland, and offered basis to the improvement of mediumlow farmland and its increase of grain production in Tianjin. [Method] Based on the statistical date of Tianjin and its relevant counties and districts, the yield standard was set up to classify high-yield, medium-yield and low-yield farmland in Tianjin. The author analyzed area change of medium-low yield farmland in six agricultural counties and districts （including Jixian County, Wuqing District, Baodi District, Ninghe County, Jinghai County and Dagang district of Binghai New Area） from 1980 to 2010. [Result] The results showed that the average yield of grain rose from 2 445 kg/hm^2 in 1980 to 5 130 kg/hm^2 in 2010, increasing 109.82%. The area of mediumlow yield farmland was reduced from 291 250.13 hm^2 in 1985 to 76 489.87 hm^2 in 2010, coming down 74%. In Tianjin, the area of medium-low yield farmland of 2010 accounted for 19% of the total farmland, of which the ratios of medium-low yield farmland of Jinghai County, Jixian County, Dagang district of Binghai New Area, Wuqing District, Baodi District and Ninghe County were 43.12%, 18.59%, 17.23%, 14.01%, 7.05% and 0, respectively. Low soil nutrient content, drought and water shortage, as well as soil salinization were the main yield limiting factors to mediumlow yield farmland in Tianjin in 2010. [Conclusion] The countermeasures to improve the medium-low yield farmland were proposed, involving enhancing the investment of the government, strengthening the construction of water conservancy infrastructure, further improving the soil fertility, as well as saline and alkaline land, optimizing the farming system and planting drought and salt tolerance crops, etc.
基金National Natural Science Foundation of China(12125509,11961141003,12275361,U2267205,12175152,12175121)National Key Research and Development Project(2022YFA1602301)Continuous-support Basic Scientific Research Project。
文摘To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.
基金supported by the National Science Foundation of China(32201643)the Key Research Projects of Yibin,research and integrated demonstration and key technologies for smart bamboo industry(YBZD2024-1).
文摘Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most speciesrich genus in the Bambusoideae subfamily.Based on the distribution data of 46 species and 20 environmental variables,we used the MaxEnt model combined with ArcGIS calculations to simulate current and future potential richness distributions under three distinct CO_(2) emission scenarios.The results showed that the MaxEnt model had a good predictive ability,with a mean area under the working characteristic curve(AUC value)of 0.91 for all species.The main environmental variables that impacted the future distribution of most Phyllostachys species were elevation,variations of seasonal precipitation,and mean diurnal range.Phyllostachys species are currently concentrated in southeastern China.Under future climate projections,18 species exhibited significant habitat contraction across three or more future climate scenarios,but suitable habitats for other species will expand.This enhancement is most pronounced under the extreme climate scenario(2090s-SSP585),primarily driven by high species gains contributing to elevated turnover values across scenarios.The center of maximum richness will progressively shift southwestward over time.Predictive modeling of Phyllostachys richness distribution dynamics under climate change enhances our understanding of its biogeography and informs strategic introduction programs to bamboo management and augments China’s carbon sequestration capacity.
基金the Chinese Academy of Sciences Research Center for Ecology and Environment of Central Asia(RCEECA),the construction and joint research for the China-Tajikistan“Belt and Road”Joint Laboratory on Biodiversity Conservation and Sustainable Use(2024YFE0214200)the Shanghai Cooperation Organization Partnership and International Technology Cooperation Plan of Science and Technology Projects(2023E01018,2025E01056)the Chinese Academy of Sciences President’s International Fellowship Initiative(PIFI)(2024VBC0006).
文摘Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges.There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning.Therefore,this study integrated 4 key biodiversity indices including species richness(SR),phylogenetic diversity(PD),threatened species richness(TSR),and endemic species richness(ESR)to map species diversity distribution patterns,identify conservation gaps,and elucidate their effects of climatic factors.This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan.The central–western mountains(specifically the Gissar-Darvasian and Zeravshanian regions)emerge as irreplaceable biodiversity hotspots.However,we found a severe spatial mismatch between these priority areas and the existing protected areas(PAs).Protection coverage for all hotspots was alarmingly low,ranging from 31.00%to 38.00%.Consequently,a critical 64.80%of integrated priority areas fall outside of the current PAs,representing a major conservation gap.This study identified precipitation seasonality and isothermality as the principal drivers,collectively explaining over 50.00%of the diversity variation and suggesting high vulnerability to hydrological shifts.Furthermore,we detected significant geographic sampling bias in the public biodiversity databases,with the most critical hotspot being systematically under-sampled.This study provides a robust scientific basis for conservation action,highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys.These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3(“30×30 Protection”).
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0208)the National Natural Science Foundation of China(Nos.42171148 and 42330512)the Key R&D Project from the Science and Technology Department of Tibet(No.XZ202501ZY0030).
文摘Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in alpine mountains with climate change.Hence,94 samples of river water were collected from 2018 to 2020 in the headwaters of the Shule River Basin to assess the nutrients spatiotemporal distribution and combined ap-proach of water quality index to assess water quality and potential sources.The findings depict that high nutrient concentrations were found to coincide with snowmelt and glacial meltwater and rainfall recharge periods,while total flux peaked from June to September due to increased runoff.Notably,total nitrogen(TN)concentrations were significantly higher near the town,primarily attributed to the replenishment of nitrate(NO_(3)^(‒)-N)from live-stock manure.The high total P(TP)was near the glacier,which was attributed to the transportation of glacial sediments into the river,and pH was another critical factor.N was the primary nutrient limiting factor for the growth of phytoplankton in river water.Although the migration and transport of nutrients have altered with climate change,river water quality is good in alpine mountains based on an overall evaluation.These findings contribute to enriching nutrient datasets and highlight the importance of water resource management and water quality assessment in sensitive and fragile alpine mountains.
基金Supported by the National Key Research and Development Program of China(No.2023YFD2400800)the Laoshan Laboratory(Nos.LSKJ202203801,LSKJ202203204)+4 种基金the Natural Science Foundation of Shandong Province(Nos.ZR2023MD127,ZR2021MD075)the Central Public-interest Scientific Institution Basal Research Fund CAFS(Nos.2023TD28,20603022023012)the National Natural Science Foundation of China(No.32373107)the China Agriculture Research System(No.CARS-50)the Taishan Scholars Program。
文摘Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.
文摘Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.
基金Project supported by the Project of the Anhui Provincial Natural Science Foundation(Grant No.2308085MA19)Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA0410401)+2 种基金the National Natural Science Foundation of China(Grant No.52202120)the National Key Research and Development Program of China(Grant No.2023YFA1609800)USTC Research Funds of the Double First-Class Initiative(Grant No.YD2310002013)。
文摘Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.
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 from the National Natural Science Foundation of China (Award 91745203) supplemented by Central Universities’ Basic Research Funds.
文摘Ceramic cells promise ideal energy conversion and storage devices,making the development of efficient and robust air electrodes crucial for their application.In this study,a Ba_(0.4)Sr_(0.5)Cs_(0.1)Co_(0.7)Fe_(0.2)Nb_(0.1)O_(3−δ)(BSCCFN)air electrode,based on Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3−δ)(BSCF),is designed using a perovskite A-B-site ionic Lewis acid strength(ISA)polarization distribution strategy and is successfully applied in both oxygen-ion conducting solid oxide fuel cells(O-SOFCs)and proton-conducting reversible protonic ceramic cells(R-PCCs).When BSCCFN is used as the air electrode in O-SOFCs,a peak power density(PPD)of 1.45 W cm^(−2)is achieved at 650°C,whereas in R-PCCs,a PPD of 1.13 W cm^(−2)and a current density of−1.8 A cm^(−2)at 1.3 V are achieved at the same temperature and show stable reversibility over 100 h.Experimental measurements and theoretical calculations demonstrate that low-ISA Cs+doping accelerates the reaction kinetics of both oxygen ions and protons,while high-ISA Nb^(5+)doping enhances electrode stability.The synergistic effect of Cs^(+)and Nb^(5+)co-doping in the BSCCFN electrode lies in the ISA polarization distribution,which weakens the Co/Fe–O bond covalency,thereby promoting oxygen vacancy formation and facilitating the conduction of oxygen ions and protons.
基金supported by the Hubei Provincial Science and Technology Project,China(2025CSA039)the National Natural Science Foundation of China(32001467)。
文摘Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
基金co-supported by National Natural Science Foundation of China (Project number 41502201)"Western Light" project of Chinese Academy of Sciences (XBBS201301)
文摘Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construct the
基金National Natural Science Foundation of China,No.41371148Major Program of National Social Science Fund of China,No.13&ZD082
文摘With basic information from 8353 archaeological sites, this study describes a holistic spatial-temporal distribution pattern of archaeological sites of the prehistoric culture sequence from 9.5 ka BP (ka BP = thousands of years before 0 BP, where "0 BP" is defined as the year AD 1950) to 2.3 ka BP in the region that extends from the Yanshan Mountains to the Liaohe River Plain(i.e., the Yan-Liao region) in northern China. Based on spatial statistics analysis – including the spatial density of the sites and Geographic Information System nearest-neighbour analysis, combined with a review of environmental and climatic data – this paper analyses cultural evolution, the spatial-temporal features of the archaeological sites and human activities against the backdrop of climatic and environmental changes in this region. The results reveal that prehistoric cultural evolution in the Yan-Liao region is extensively influenced by climatic and environmental changes. The Xinglongwa, Zhaobaogou and Fuhe cultures, which primarily developed during a habitable period from 8.5 ka BP to 6.0 ka BP with strong summer monsoons, have similar maximum density values, spatial patterns and subsistence strategies dominated by hunting-gathering. Significant changes occurred in the Hongshan and Lower Xiajiadian cultures, with a significant increase in numbers and densities of sites and a slump in average nearest-neighbour ratio when the environment began to deteriorate starting in 6.0 ka BP. Additionally, with the onset of a weak summer monsoon and the predominance of primitive agriculture, sites of these two cultures present a different type of concentric circle-shaped pattern in space. As the environment continuously deteriorated with increasing aridity and the spread of steppe, more sites were distributed towards the south, and primitive agriculture was replaced by livestock husbandry in the Upper Xiajiadian culture. The most densely populated areas of the studied cultures are centralized within a limited area. The Laohahe River and Jiaolaihe River basins formed the core area in which most archaeological sites were distributed during the strong summer monsoon period and the first few thousand years of the weak summer monsoon period.
基金funded by the Research on Prevention and Control Technology of Ecological Debris Flow Disasters from Department of Land and Resources of Sichuan Province (Grant No. KJ2018-24)the Natural Science Foundation of China (Grant No. 41772343)+2 种基金the Chinese Academy of Sciences and Organization Department of Sichuan Provincial Party Committee "Light of West China" Program (the key control techniques of glacial debris flow along the Sichuan-Tibet Railway)the Key International S&T Cooperation Projects (Grant No. 2016YFE0122400)the Natural Science Foundation of China (Grant No. 41471011)
文摘Grain composition plays a vital role in impact pressure of debris flow. Current approaches treat debris flow as uniform fluid and almost ignore its granular effects. A series of flume experiments have been carried out to explore the granular influence on the impact process of debris flow by using a contact surface pressure gauge sensor(Tactilus~?, produced by Sensor Products LLC). It is found that the maximum impact pressure for debris flow of low density fluctuates drastically with a long duration time while the fluctuation for flow of high density is short in time, respectively presenting logarithmic and linear form in longitudinal attenuation. This can be ascribed to the turbulence effect in the former and grain collisions and grainfluid interaction in the latter. The horizontal distribution of the impact pressure can be considered as the equivalent distribution. For engineering purposes, the longitudinal distribution of the pressure can be generalized to a triangular distribution, from which a new impact method considering granular effects is proposed.
基金National Natural Science Foundation of China(41375025)863 Program(2012AA120903,2011AA12A104-3)+2 种基金Public Welfare Research Foundation of China Meteorological Administration(GYHY201106044,GYHY201106045)Meteorological Application Demonstration Project(E310/1112)4th and 5th GOSAT/TANSO joint research Project 2013-2015
文摘The variation of the atmospheric Carbon Dioxide （CO2） concentration plays an important role in global cli- mate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite （Greenhouse Gases Observing Satellite）. In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate charac- teristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON （Total Carbon Column Observing Network） observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 da- ta can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 oomv in the 0-40？N latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concen- tration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in win- ter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an av- erage concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentra- tion has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.
基金Under the auspices of National Natural Science Foundation of China(No.41771537)Fundamental Research Funds for the Central Universities
文摘Earthquakes exhibit clear clustering on the earth. It is important to explore the spatial-temporal characteristics of seismicity clusters and their spatial heterogeneity. We analyze effects of plate space, tectonic style, and their interaction on characteristic of cluster.Based on data of earthquakes not less than moment magnitude(M_w) 5.6 from 1960 to 2014, this study used the spatial-temporal scan method to identify earthquake clusters. The results indicate that seismic spatial-temporal clusters can be classified into two types based on duration: persistent clusters and burst clusters. Finally, we analysed the spatial heterogeneity of the two types. The main conclusions are as follows: 1) Ninety percent of the persistent clusters last for 22-38 yr and show a high clustering likelihood;ninety percent of the burst clusters last for 1-1.78 yr and show a high relative risk. 2) The persistent clusters are mainly distributed in interplate zones, especially along the western margin of the Pacific Ocean. The burst clusters are distributed in both intraplate and interplate zones, slightly concentrated in the India-Eurasia interaction zone. 3) For the persistent type, plate interaction plays an important role in the distribution of the clusters’ likelihood and relative risk. In addition, the tectonic style further enhances the spatial heterogeneity. 4) For the burst type,neither plate activity nor tectonic style has an obvious effect on the distribution of the clusters’ likelihood and relative risk. Nevertheless,interaction between these two spatial factors enhances the spatial heterogeneity, especially in terms of relative risk.
基金financially supported by the National Key R&D Program of China(grant no.2017YFC0602405)the National Natural Science Foundation of China(grant no.42030811)。
文摘Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral deposits are spatially distributed mainly in the Altay and Southern Great Xingán Range regions in the Central Asian orogenic belt;in the Middle Qilian,South Qinling and East Qinling mountains regions in the Qilian-Qinling-Dabie orogenic belt;in the Western Sichuan and Bailongshan-Dahongliutan regions in the Kunlun-Songpan-Garze orogenic belt,and in the Northeastern Jiangxi,Northwestern Jiangxi,and Southern Hunan regions in South China.Major ore-forming epochs include Indosinian(mostly 200-240 Ma,in particular in western China)and the Yanshanian(mostly 120-160 Ma,in particular in South China).In addition,Bayan Obo,Inner Mongolia,northeastern China,with a complex formation history,hosts the largest REE and Nb deposits in China.There are six major rare metal mineral deposit types in China:Highly fractionated granite;Pegmatite;Alkaline granite;Carbonatite and alkaline rock;Volcanic;and Hydrothermal types.Two further types,namely the Leptynite type and Breccia pipe type,have recently been discovered in China,and are represented by the Yushishan Nb-Ta-(Zr-Hf-REE)and the Weilasituo Li-Rb-Sn-W-Zn-Pb deposits.Several most important controlling factors for rare metal mineral deposits are discussed,including geochemical behaviors and sources of the rare metals,highly evolved magmatic fractionation,and structural controls such as the metamorphic core complex setting,with a revised conceptual model for the latter.
