Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp le...Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp les are taken at different locations,inclu ding three kinds of covering soil,th ree different depths of soil layers a nd four different covering ages of covering soil.The s patial-temporal variation of heavy metal element content in reclamatio n soil is stud-ied.The results indicate that the co ntent of heavy metal elements is decreasing year after year;the determin ant reason why the content of heavy metal elemen ts at 60cm depth layer is higher than t hat at 30cm depth layer and surface is fertiliz-er and manure application;the metal elements mainly come from external environment;there is no metal pollut ion coming from mother material(coal mining wastes)in plough layer of covering soil.展开更多
Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance o...Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.展开更多
Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-langu...Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-language Climate Index （RClimDex）. The spatial-temporal change characteristics in the past 50 years have been examined using the method of trend analysis, Mann-Kendall and the spatial analysis module of Arcgis9.2. The results show that the spatial distribution of the indices for extreme precipitation in Northwest China is greatly influenced by geographic location, atmospheric circulation and topography, and the spatial difference of extreme precipitation events is very evident, while the indices reduce from the southeast to the northwest except Consecutive Dry Days （CDD）. In Xinjiang region, high values appear in Tianshan Mountains and decrease towards the south and north respectively. In the past 50 years, the temporal variation tendency of the indices for extreme precipitation in Northwest China has a great spatial distinction. It shows that the variation tendency is opposite between the east （decrease） and the west （increase）, and CDD has a decreasing tendency while other indices increase. For each region, it is found that the indices for extreme precipitation in Xinjiang and Qinghai Province shows an increasing trend, and it is remarkable in Tianshan Mountains, the north of Xinjiang and the northeast of Qinghai Province. The temporal variation tendency of the indices for extreme precipitation in Ningxia, Shaanxi and Gansu has a large spatial distinction. The stations which have an increasing tend are mainly found in the north of Ningxia, south of Shaanxi and Hexi Corridor of Gansu. However, the south of Ningxia, north of Shaanxi and Longnan of Gansu Province mainly present a decreasing trend. The temporal variation tendency of the indices for extreme precipitation in Inner Mongolia is not obvious. Overall, the east part of Northwest China has a dry tendency, while the west part has an opposite trend.展开更多
As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wet...As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.展开更多
To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytopla...To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytoplankton community structure and various environmental parameters were examined. The phytoplankton community in the bay was composed of mainly diatoms and dinofl agellates, and several other species of Chrysophyta were also observed. Diatoms were the most dominant phytoplankton group throughout the year, except in spring and winter, when Noctiluca scintillans was co-dominant. High Si/N ratios in summer and fall refl ect the high dominance of diatoms in the two seasons. Temporally, the phytoplankton cell abundance peaked in summer, due mainly to the high temperatures and nutrient concentrations in summer. Spatially, the phytoplankton cell abundance was higher in the northern part of the bay than in the other parts of the bay in four seasons. The diatom cell abundances show signifi cant positive correlations with the nutrient concentrations, while the dinofl agellate cell abundances show no correlation or a negative correlation with the nutrient concentrations but a signifi cant positive correlation with the stratifi cation index. This discrepancy was mainly due to the diff erent survival strategies between diatoms and dinofl agellates. The Shannon-Wiener diversity index ( H′) values in the bay ranged from 0.08 to 4.18, which fell in the range reported in historical studies. The distribution pattern of H′ values was quite diff erent from that of chlorophyll a , indicating that the phytoplankton community structure might have high biomass with a low diversity index. Compared with historical studies, we believe that the dominant phytoplankton species have been changed in recent years due mainly to the changing environment in the Jiaozhou Bay in recent 30 years.展开更多
Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of grid...Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.展开更多
Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 ...Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 national meteorological stations during 1961-2017,trend analysis,mutation analysis,partial correlation analysis,and Mann-Kendall mutation analysis were used to analyze the temporal and spatial variation characteristics of sunshine duration in different regions of China,and the influence of main climatic factors and human activities.The results showed that:the sunshine duration in China showed a significant decreasing trend with a rate of-45.8 h/10 a,and the sunshine duration in 7 regions of Northwestern China,Northern China,Northeastern China,Center China,Eastern China,Southern China,and Southwestern China also showed a significant decrease.The spatial distribution of sunshine duration in China was characterized by"less in the south and more in the north",and the sunshine duration in the northern region was significantly higher than those in the southern region.The sunshine duration in Tibet,Qinghai,Gansu and west Inner Mongolia was higher,while it was obviously lower in Sichuan Basin.Through M-K mutation test analysis,it was found that sunshine duration in the whole country decreased significantly,but there was no mutation station,while mutation occurred at 1989 in Southwestern China,1983 in Northwestern China,1985 in Northeastern China.Seasonally,there was the highest sunshine duration in summer,followed by spring,autumn,and winter;the decline rate was also the highest in summer,followed by autumn,winter,and spring.Sunshine duration had a highly negative correlation with total cloud amount,visibility,haze,and precipitation,while had a strongly positive correlation with wind speed,and had no significant correlation with fog.展开更多
By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of g...By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.展开更多
Marine biodiversity is changing in response to altered physical environment, subsequent ecological changes as well as anthropogenic disturbances. In this study, phytoplankton samples in situ collected in the Bering Se...Marine biodiversity is changing in response to altered physical environment, subsequent ecological changes as well as anthropogenic disturbances. In this study, phytoplankton samples in situ collected in the Bering Sea in July of 1999 and 2010 were analyzed to obtain phytoplankton community structure and spatial-temporal variation between the beginning and end of this decade, and the correlation of phytoplankton community dynamics and environmental factors was investigated. A total of 5 divisions, 58 genera and 153 species of phytoplankton belonging to 3 ecological groups were identified. The vast majority of phytoplankton consisted of diatoms accounting for 66.7% of the total species and 95.2% of the total abundance. Considering differentiation in spatial extent and phytoplankton sample types, there were subtle changes in species composition, large altering in abundance and significant variation in spatial distribution between two surveys. The abundance peak area was located at the Bering Strait while sub peak was found at the Bering Sea Basin. The boreal-temperate diatom was the dominant flora, which was subsequently replaced by eurythermal and frigid-water diatom. Phytoplankton community in the Bering Sea was not a simplex uniform community but composed of deep-ocean assemblage and neritic assemblage. The deep-ocean assemblage was located in the northwestern Pacific Ocean and Bering Sea Basin, dominated by boreal-temperate species（Neodenticula seminae, Thalassiothrix longissima, Amphiprora hyperborean, Chaetoceros atlanticus, Thalassiosira trifulta, etc.） and eurychoric species（Thalassionema nitzschioides, Ch. compressus, Rhizosolenia styliformis, etc.）, and characterized by low abundance, even interspecies abundance allocations, diverse dominant species and high species diversity. The neritic assemblage was distributed on the continental shelf and slope of Bering Sea and was mainly composed of frigid-water species（Th.nordenski？ldii, Ch. furcellatus, Ch. socialis, Bacteriosira fragilis, etc.） and eurythermal and euryhaline species（L.danicus, Ch. curvisetus, Coscinodiscus curvatulus, etc.）, and it was characterized by high abundance, uneven interspecies allocations, prominent dominant species and low species diversity. Spatial-temporal variation of species composition and abundance of phytoplankton in the Bering Sea was directly controlled by surface circulation,nutrient supply and ice edge.展开更多
Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inv...Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies （GIMMS） NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer （MODIS） NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax （the maximum NDVI during the growing season） for desert vegetation in Hexi region increased at the rate of 0.65x10-3/a （P〈0.05） from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin （an extremely arid area）, indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.展开更多
Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density ...Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density to assess wind resource.The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China.The air density at 100 m height is accurately calculated by using air temperature,pressure,and humidity.The spatial-temporal variation features of air density are firstly analyzed.Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,respectively.Usingρstoverestimates the annual wind energy production(AEP)in 93.6%of the study area.Humidity significantly affects AEP in central and southern China areas.In more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated.Usingρsitesignificantly reduces the estimation error in AEP.But AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in winter.Except for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρsite.Usingρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as well.The impacts of air density on assessing wind resource are almost independent of the wind turbine types.展开更多
Using sea ice concentration dataset covering the period of 1968-2002 obtained from the Hadley Center of UK, this paper investigates characters of Antarctic sea ice variations .The finding demonstrates that the change ...Using sea ice concentration dataset covering the period of 1968-2002 obtained from the Hadley Center of UK, this paper investigates characters of Antarctic sea ice variations .The finding demonstrates that the change of mean sea-ice extent is almost consistent with that of sea-ice area, so sea-ice extent can be chosen to go on this research. The maximum and the minimum of Antarctic sea ice appear in September and February respectively. The maximum and the maximal variation of sea ice appear in Weddell Sea and Ross Sea, while the minimum and the minimal variation of sea-ice appear in Antarctic Peninsula. In recent 35 years, as a whole, Antarctic sea ice decreased distinctly. Moreover, there are 5 subdivision characteristic regions considering their different variations. Hereinto, the sea-ice extent of Weddell Sea and Ross Sea regions extends and area increases, while the sea-ice extent of the other three regions contracts and area decreases. They are all of obvious 2-4 years and 5-7 years significant oscillation periods. It is of significance for further understanding the sea-ice-air interaction in Antarctica region and discussing the relationship between sea-ice variation and atmospheric circulation.展开更多
Cirrus clouds play a crucial role in the energy balance of the Earth-atmosphere system.We investigated the spatiotemporal variations of cirrus over the South China Sea(SCS)using satellite data(MOD08,MYD08,CALIPSO)and ...Cirrus clouds play a crucial role in the energy balance of the Earth-atmosphere system.We investigated the spatiotemporal variations of cirrus over the South China Sea(SCS)using satellite data(MOD08,MYD08,CALIPSO)and reanalysis data(MERRA-2)from March 2007 to February 2015(eight years).The horizontal distribution reveals lower cirrus fraction values in the northern SCS and higher values in the southern region,with minima observed in March and April and maxima sequentially occurring in August(northern SCS,NSCS),September(middle SCS,MSCS),and December(southern SCS,SSCS).Vertically,the cirrus fraction peaks in summer and reaches its lowest levels in spring.Opaque cirrus dominates during summer in the NSCS and MSCS,comprising 53.6%and 55.9%,respectively,while the SSCS exhibits a higher frequency of opaque cirrus relative to other cloud types.Subvisible cirrus clouds have the lowest frequency year-round,whereas thin cirrus is most prominent in winter in the NSCS(46.3%)and in spring in the MSCS(45.3%).A case study from September 2021 further explores the influence of ice crystal habits on brightness temperature(BT)over the SCS.Simulations utilizing five ice crystal shapes from the ARTS DDA(Atmospheric Radiative Transfer Simulator Discrete Dipole Approximation)database and the RTTOV 12.4 radiative transfer model reveal that the 8-column-aggregate shape best represents BT in the NSCS and SSCS,while the large-block-aggregate shape performs better in the SSCS.展开更多
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive degeneration of upper and lower motor neurons in the brainstem and spinal cord,leading to muscle weakness,para...Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive degeneration of upper and lower motor neurons in the brainstem and spinal cord,leading to muscle weakness,paralysis,and respiratory failure (Morgan and Orrell,2016).展开更多
As one of the areas with numerous lakes on the Tibetan Plateau, the Hoh Xil region plays an extremely important role in the fragile plateau eco-environment. Based on topographic maps in the 1970s and Landsat TM/ETM＋ ...As one of the areas with numerous lakes on the Tibetan Plateau, the Hoh Xil region plays an extremely important role in the fragile plateau eco-environment. Based on topographic maps in the 1970s and Landsat TM/ETM＋ remote sensing images iin the 1990s and the period from 2000 to 2011, the data of 83 lakes with an area above 10 km2 each were obtained by digitization method and artificial visual interpretation technology, and the causes for lake variations were also analyzed. Some conclusions can be drawn as follows. （1） From the 1970s to 2011, the lakes in the Hoh Xil region firstly shrank and then expanded, in particular, the area of lakes generally decreased during the 1970s-1990s. Then the lakes expanded from the 1990s to 2000 and the area was slightly higher than that in the 1970s. The area of lakes dramatically increased after 2000. （2） From 2000 to 2011, the lakes with different area ranks in the Hoh Xil region showed an overall expansion trend. Meanwhile, some regional differences were also discovered. Most of the lakes expanded and were widely distributed in the northern, central and western parts of the region. Some lakes were merged together or overflowed due to their rapid expansion. A small number of lakes with the trend of area decrease or strong fluctuation were scattered in the central and southern parts of the study area. And their variations were related to their own supply conditions or hydraulic connection with the downstream lakes or rivers. （3） The increase in precipitation was the dominant factor resulting in the expansion of lakes in the Hoh Xil region. The secondary factor was the increase in meltwater from glaciers and frozen soil due to climate warming.展开更多
Grassland is the largest terrestrial ecosystem in China. It is of great significance to measure accurately the soil respiration of different grassland types for the contribution evaluation of the Chinese terrestrial e...Grassland is the largest terrestrial ecosystem in China. It is of great significance to measure accurately the soil respiration of different grassland types for the contribution evaluation of the Chinese terrestrial ecosystem’s carbon emission to the atmospheric CO2 concentration. A three-year (2005-2007) field experiment was carried out on three steppes of Stipa L. in the Xilin River Basin, Inner Mongolia, China, using a static opaque chamber technique. The seasonal and interannual variations of soil respiration rates were analyzed, and the annual total soil respiration of the three steppes was estimated. The numerical models between soil respiration and water-heat factors were established respectively. Similar seasonal dynamic and high annual and interannual variations of soil respiration were found in all of the three steppes. In the growing season, the fluctuation of soil respiration was particularly evident. The coefficients of variation (CVs) for soil respiration in different growing seasons ranged from 54% to 93%, and the annual CVs were all above 115%. The interannual CV of soil respiration progressively decreased in the order of Stipa grandis (S. grandis) steppe 】 Stipa baicalensis (S. baicalensis) steppe 】 Stipa krylovii (S. krylovii) steppe. The annual total soil respiration for the S. baicalensis steppe was 223.62?299.24 gC m-2 a-1, 150.62-226.99 gC m-2 a-1 for the S. grandis steppe, and 111.31–131.55 gC m-2 a-1 for the S. krylovii steppe, which were consistent with the precipitation gradient. The variation in the best fitting temperature factor explained the 63.5%, 73.0%, and 73.2% change in soil respiration in the three steppes at an annual time scale, and the corresponding Q10 values were 2.16, 2.98, and 2.40, respectively. Moreover, the Q10 values that were calculated by soil temperature at different depths all expressed a 10 cm 】 5 cm 】 surface in the three sampling sites. In the growing season, the soil respiration rates were related mostly to the surface soil moisture, and the 95.2%, 97.4%, and 93.2% variations in soil respiration in the three steppes were explained by the change in soil moisture at a depth of 0-10 cm, respectively.展开更多
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
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A...In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.展开更多
Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,bu...Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,but the regional sources of halocarbons in China are not yet well comprehended.To investigate the characteristics,emissions,and source profiles,this study conducted a field campaign in Xiamen,a coastal city in southeastern China.Higher enhancements were found in the unregulated halocarbons(CH_(3)Cl,CH_(2)Cl_(2),CHCl_(3))than in the MP eliminated species(CCl_(4),CH_(3)Br)and theMP controlled species(HCFCs,HFCs).Many of the measured halocarbons varied seasonally and regionally,depending on the anthropogenic sources and atmospheric transport.Backward trajectory analysis showed that the air masses from inland were polluted over Shandong,Hebei,and northern Fujian in the cold season,while the air masses fromthe sea in the warm season were clean.Different air masses in two seasons were associated with the halocarbon patterns in the study area.Industrial activities,especially solvent usage,were the primary sources of halocarbons.The emission hot spots in Fujian Province were concentrated in Sanming,Fuzhou,and Xiamen,and the unregulated halocarbons made the largest contribution.This study provides an insight for a deep understanding of the characteristics and potential sources of halocarbons,and for strengthened management of halocarbons in China.展开更多
Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional bree...Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional breeding methods raise concerns about reduced genetic diversity,epibreeding propels crop improvement through epigenetic variations that regulate gene expression,ultimately impacting crop yield.Epigenetic regulation in crops encompasses various modes,including histone modification,DNA modification,RNA modification,non-coding RNA,and chromatin remodeling.This review summarizes the epigenetic mechanisms underlying major agronomic traits in maize and identifies candidate epigenetic landmarks in the maize breeding process.We propose a valuable strategy for improving maize yield through epibreeding,combining CRISPR/Cas-based epigenome editing technology and Synthetic Epigenetics(SynEpi).Finally,we discuss the challenges and opportunities associated with maize trait improvement through epibreeding.展开更多
文摘Grid method is employed for sampling covering soil at the test field,whic h is reclamation area filled by coal mining wastes for cropland in th e Fushun coal mine,Liaoning Province,the Northeast China.The soil samp les are taken at different locations,inclu ding three kinds of covering soil,th ree different depths of soil layers a nd four different covering ages of covering soil.The s patial-temporal variation of heavy metal element content in reclamatio n soil is stud-ied.The results indicate that the co ntent of heavy metal elements is decreasing year after year;the determin ant reason why the content of heavy metal elemen ts at 60cm depth layer is higher than t hat at 30cm depth layer and surface is fertiliz-er and manure application;the metal elements mainly come from external environment;there is no metal pollut ion coming from mother material(coal mining wastes)in plough layer of covering soil.
基金funded by the National Key R&D Program of China(Grant No.2021YFD1500200)National Natural Science Foundation of China(Grant No.42077149)+4 种基金China Postdoctoral Science Foundation(Grant No.2019M660782)National Science and Technology Basic Resources Survey Program of China(Grant No.2019FY101300)Doctoral research start-up fund project of Liaoning Provincial Department of Science and Technology(Grant No.2021-BS-136)China Scholarship Council(201908210132)Young Scientific and Technological Talents Project of Liaoning Province(Grant Nos.LSNQN201910 and LSNQN201914)。
文摘Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.
基金Supported by the Natural Science Foundation of Shandong Province,China(ZR2010DM011)
文摘Using the daily precipitation data of 118 meteorological stations in Northwest China from January 1, 1961 to December 31,2010, we analyzed extreme precipitation events from prime precipitation data by applying R-language Climate Index （RClimDex）. The spatial-temporal change characteristics in the past 50 years have been examined using the method of trend analysis, Mann-Kendall and the spatial analysis module of Arcgis9.2. The results show that the spatial distribution of the indices for extreme precipitation in Northwest China is greatly influenced by geographic location, atmospheric circulation and topography, and the spatial difference of extreme precipitation events is very evident, while the indices reduce from the southeast to the northwest except Consecutive Dry Days （CDD）. In Xinjiang region, high values appear in Tianshan Mountains and decrease towards the south and north respectively. In the past 50 years, the temporal variation tendency of the indices for extreme precipitation in Northwest China has a great spatial distinction. It shows that the variation tendency is opposite between the east （decrease） and the west （increase）, and CDD has a decreasing tendency while other indices increase. For each region, it is found that the indices for extreme precipitation in Xinjiang and Qinghai Province shows an increasing trend, and it is remarkable in Tianshan Mountains, the north of Xinjiang and the northeast of Qinghai Province. The temporal variation tendency of the indices for extreme precipitation in Ningxia, Shaanxi and Gansu has a large spatial distinction. The stations which have an increasing tend are mainly found in the north of Ningxia, south of Shaanxi and Hexi Corridor of Gansu. However, the south of Ningxia, north of Shaanxi and Longnan of Gansu Province mainly present a decreasing trend. The temporal variation tendency of the indices for extreme precipitation in Inner Mongolia is not obvious. Overall, the east part of Northwest China has a dry tendency, while the west part has an opposite trend.
文摘As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.
基金Supported by the National Natural Science Foundation of China(Nos.31700425,91751202)the Innovation Plan of Science and Technology for Aoshan(No.2016ASKJ02)the Health Assessment and Decision Support System for Coastal Ecosystem(No.XDA19060204)
文摘To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytoplankton community structure and various environmental parameters were examined. The phytoplankton community in the bay was composed of mainly diatoms and dinofl agellates, and several other species of Chrysophyta were also observed. Diatoms were the most dominant phytoplankton group throughout the year, except in spring and winter, when Noctiluca scintillans was co-dominant. High Si/N ratios in summer and fall refl ect the high dominance of diatoms in the two seasons. Temporally, the phytoplankton cell abundance peaked in summer, due mainly to the high temperatures and nutrient concentrations in summer. Spatially, the phytoplankton cell abundance was higher in the northern part of the bay than in the other parts of the bay in four seasons. The diatom cell abundances show signifi cant positive correlations with the nutrient concentrations, while the dinofl agellate cell abundances show no correlation or a negative correlation with the nutrient concentrations but a signifi cant positive correlation with the stratifi cation index. This discrepancy was mainly due to the diff erent survival strategies between diatoms and dinofl agellates. The Shannon-Wiener diversity index ( H′) values in the bay ranged from 0.08 to 4.18, which fell in the range reported in historical studies. The distribution pattern of H′ values was quite diff erent from that of chlorophyll a , indicating that the phytoplankton community structure might have high biomass with a low diversity index. Compared with historical studies, we believe that the dominant phytoplankton species have been changed in recent years due mainly to the changing environment in the Jiaozhou Bay in recent 30 years.
文摘Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.
基金Supported by the National Key R&D Plan(2017YFD0300201,2020YFE 0201900).
文摘Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 national meteorological stations during 1961-2017,trend analysis,mutation analysis,partial correlation analysis,and Mann-Kendall mutation analysis were used to analyze the temporal and spatial variation characteristics of sunshine duration in different regions of China,and the influence of main climatic factors and human activities.The results showed that:the sunshine duration in China showed a significant decreasing trend with a rate of-45.8 h/10 a,and the sunshine duration in 7 regions of Northwestern China,Northern China,Northeastern China,Center China,Eastern China,Southern China,and Southwestern China also showed a significant decrease.The spatial distribution of sunshine duration in China was characterized by"less in the south and more in the north",and the sunshine duration in the northern region was significantly higher than those in the southern region.The sunshine duration in Tibet,Qinghai,Gansu and west Inner Mongolia was higher,while it was obviously lower in Sichuan Basin.Through M-K mutation test analysis,it was found that sunshine duration in the whole country decreased significantly,but there was no mutation station,while mutation occurred at 1989 in Southwestern China,1983 in Northwestern China,1985 in Northeastern China.Seasonally,there was the highest sunshine duration in summer,followed by spring,autumn,and winter;the decline rate was also the highest in summer,followed by autumn,winter,and spring.Sunshine duration had a highly negative correlation with total cloud amount,visibility,haze,and precipitation,while had a strongly positive correlation with wind speed,and had no significant correlation with fog.
文摘By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.
基金The National Natural Science Foundation of China under contract Nos 41306116 and 41506217the Basic Research of the National Department of Science and Technology under contract No.GASI-01-02-04the Polar Science Strategic Research Foundation of China under contract No.20140309
文摘Marine biodiversity is changing in response to altered physical environment, subsequent ecological changes as well as anthropogenic disturbances. In this study, phytoplankton samples in situ collected in the Bering Sea in July of 1999 and 2010 were analyzed to obtain phytoplankton community structure and spatial-temporal variation between the beginning and end of this decade, and the correlation of phytoplankton community dynamics and environmental factors was investigated. A total of 5 divisions, 58 genera and 153 species of phytoplankton belonging to 3 ecological groups were identified. The vast majority of phytoplankton consisted of diatoms accounting for 66.7% of the total species and 95.2% of the total abundance. Considering differentiation in spatial extent and phytoplankton sample types, there were subtle changes in species composition, large altering in abundance and significant variation in spatial distribution between two surveys. The abundance peak area was located at the Bering Strait while sub peak was found at the Bering Sea Basin. The boreal-temperate diatom was the dominant flora, which was subsequently replaced by eurythermal and frigid-water diatom. Phytoplankton community in the Bering Sea was not a simplex uniform community but composed of deep-ocean assemblage and neritic assemblage. The deep-ocean assemblage was located in the northwestern Pacific Ocean and Bering Sea Basin, dominated by boreal-temperate species（Neodenticula seminae, Thalassiothrix longissima, Amphiprora hyperborean, Chaetoceros atlanticus, Thalassiosira trifulta, etc.） and eurychoric species（Thalassionema nitzschioides, Ch. compressus, Rhizosolenia styliformis, etc.）, and characterized by low abundance, even interspecies abundance allocations, diverse dominant species and high species diversity. The neritic assemblage was distributed on the continental shelf and slope of Bering Sea and was mainly composed of frigid-water species（Th.nordenski？ldii, Ch. furcellatus, Ch. socialis, Bacteriosira fragilis, etc.） and eurythermal and euryhaline species（L.danicus, Ch. curvisetus, Coscinodiscus curvatulus, etc.）, and it was characterized by high abundance, uneven interspecies allocations, prominent dominant species and low species diversity. Spatial-temporal variation of species composition and abundance of phytoplankton in the Bering Sea was directly controlled by surface circulation,nutrient supply and ice edge.
基金supported by the Opening Foundation of the State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating,Gansu Desert Control Research Institute (GSDC201503)the National Natural Science Foundation of China (41271024,31260129,31360204)+1 种基金the Program for Innovative Research Group of Gansu Province,China (1506RJIA155)Lanzhou University for providing Arc GIS technical support in the data processing
文摘Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies （GIMMS） NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer （MODIS） NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax （the maximum NDVI during the growing season） for desert vegetation in Hexi region increased at the rate of 0.65x10-3/a （P〈0.05） from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin （an extremely arid area）, indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.
基金supported by the National Natural Science Foundation of China(Grant No.52107091)the Fundamental Research Funds for the Central Universities(Grant No.2022MS017)the Science and Technology Project of CHINA HUANENG(Offshore wind power and smart energy system,Grant No.HNKJ20-H88)。
文摘Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density to assess wind resource.The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China.The air density at 100 m height is accurately calculated by using air temperature,pressure,and humidity.The spatial-temporal variation features of air density are firstly analyzed.Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,respectively.Usingρstoverestimates the annual wind energy production(AEP)in 93.6%of the study area.Humidity significantly affects AEP in central and southern China areas.In more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated.Usingρsitesignificantly reduces the estimation error in AEP.But AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in winter.Except for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρsite.Usingρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as well.The impacts of air density on assessing wind resource are almost independent of the wind turbine types.
文摘Using sea ice concentration dataset covering the period of 1968-2002 obtained from the Hadley Center of UK, this paper investigates characters of Antarctic sea ice variations .The finding demonstrates that the change of mean sea-ice extent is almost consistent with that of sea-ice area, so sea-ice extent can be chosen to go on this research. The maximum and the minimum of Antarctic sea ice appear in September and February respectively. The maximum and the maximal variation of sea ice appear in Weddell Sea and Ross Sea, while the minimum and the minimal variation of sea-ice appear in Antarctic Peninsula. In recent 35 years, as a whole, Antarctic sea ice decreased distinctly. Moreover, there are 5 subdivision characteristic regions considering their different variations. Hereinto, the sea-ice extent of Weddell Sea and Ross Sea regions extends and area increases, while the sea-ice extent of the other three regions contracts and area decreases. They are all of obvious 2-4 years and 5-7 years significant oscillation periods. It is of significance for further understanding the sea-ice-air interaction in Antarctica region and discussing the relationship between sea-ice variation and atmospheric circulation.
基金supported by the National Natural Science Foundation of China(Grant Nos.42027804,41775026,and 41075012)。
文摘Cirrus clouds play a crucial role in the energy balance of the Earth-atmosphere system.We investigated the spatiotemporal variations of cirrus over the South China Sea(SCS)using satellite data(MOD08,MYD08,CALIPSO)and reanalysis data(MERRA-2)from March 2007 to February 2015(eight years).The horizontal distribution reveals lower cirrus fraction values in the northern SCS and higher values in the southern region,with minima observed in March and April and maxima sequentially occurring in August(northern SCS,NSCS),September(middle SCS,MSCS),and December(southern SCS,SSCS).Vertically,the cirrus fraction peaks in summer and reaches its lowest levels in spring.Opaque cirrus dominates during summer in the NSCS and MSCS,comprising 53.6%and 55.9%,respectively,while the SSCS exhibits a higher frequency of opaque cirrus relative to other cloud types.Subvisible cirrus clouds have the lowest frequency year-round,whereas thin cirrus is most prominent in winter in the NSCS(46.3%)and in spring in the MSCS(45.3%).A case study from September 2021 further explores the influence of ice crystal habits on brightness temperature(BT)over the SCS.Simulations utilizing five ice crystal shapes from the ARTS DDA(Atmospheric Radiative Transfer Simulator Discrete Dipole Approximation)database and the RTTOV 12.4 radiative transfer model reveal that the 8-column-aggregate shape best represents BT in the NSCS and SSCS,while the large-block-aggregate shape performs better in the SSCS.
文摘Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive degeneration of upper and lower motor neurons in the brainstem and spinal cord,leading to muscle weakness,paralysis,and respiratory failure (Morgan and Orrell,2016).
基金National Science-technology Support Plan Project, No.2012BAC 19B07 National Natural Science Foundation of China, No.41071044+2 种基金 No.41261016 No.41190084 Youth Teacher Scientific Capability Promoting Project of Northwest Normal University, No.NWNU-LKQN- 10-35
文摘As one of the areas with numerous lakes on the Tibetan Plateau, the Hoh Xil region plays an extremely important role in the fragile plateau eco-environment. Based on topographic maps in the 1970s and Landsat TM/ETM＋ remote sensing images iin the 1990s and the period from 2000 to 2011, the data of 83 lakes with an area above 10 km2 each were obtained by digitization method and artificial visual interpretation technology, and the causes for lake variations were also analyzed. Some conclusions can be drawn as follows. （1） From the 1970s to 2011, the lakes in the Hoh Xil region firstly shrank and then expanded, in particular, the area of lakes generally decreased during the 1970s-1990s. Then the lakes expanded from the 1990s to 2000 and the area was slightly higher than that in the 1970s. The area of lakes dramatically increased after 2000. （2） From 2000 to 2011, the lakes with different area ranks in the Hoh Xil region showed an overall expansion trend. Meanwhile, some regional differences were also discovered. Most of the lakes expanded and were widely distributed in the northern, central and western parts of the region. Some lakes were merged together or overflowed due to their rapid expansion. A small number of lakes with the trend of area decrease or strong fluctuation were scattered in the central and southern parts of the study area. And their variations were related to their own supply conditions or hydraulic connection with the downstream lakes or rivers. （3） The increase in precipitation was the dominant factor resulting in the expansion of lakes in the Hoh Xil region. The secondary factor was the increase in meltwater from glaciers and frozen soil due to climate warming.
基金supported by National Natural Science Foundation of China (Grant Nos. 40730105, 40673067, and 40973057)National Key Technology Research and Development Program (Grant No. 2007BAC03A11)
文摘Grassland is the largest terrestrial ecosystem in China. It is of great significance to measure accurately the soil respiration of different grassland types for the contribution evaluation of the Chinese terrestrial ecosystem’s carbon emission to the atmospheric CO2 concentration. A three-year (2005-2007) field experiment was carried out on three steppes of Stipa L. in the Xilin River Basin, Inner Mongolia, China, using a static opaque chamber technique. The seasonal and interannual variations of soil respiration rates were analyzed, and the annual total soil respiration of the three steppes was estimated. The numerical models between soil respiration and water-heat factors were established respectively. Similar seasonal dynamic and high annual and interannual variations of soil respiration were found in all of the three steppes. In the growing season, the fluctuation of soil respiration was particularly evident. The coefficients of variation (CVs) for soil respiration in different growing seasons ranged from 54% to 93%, and the annual CVs were all above 115%. The interannual CV of soil respiration progressively decreased in the order of Stipa grandis (S. grandis) steppe 】 Stipa baicalensis (S. baicalensis) steppe 】 Stipa krylovii (S. krylovii) steppe. The annual total soil respiration for the S. baicalensis steppe was 223.62?299.24 gC m-2 a-1, 150.62-226.99 gC m-2 a-1 for the S. grandis steppe, and 111.31–131.55 gC m-2 a-1 for the S. krylovii steppe, which were consistent with the precipitation gradient. The variation in the best fitting temperature factor explained the 63.5%, 73.0%, and 73.2% change in soil respiration in the three steppes at an annual time scale, and the corresponding Q10 values were 2.16, 2.98, and 2.40, respectively. Moreover, the Q10 values that were calculated by soil temperature at different depths all expressed a 10 cm 】 5 cm 】 surface in the three sampling sites. In the growing season, the soil respiration rates were related mostly to the surface soil moisture, and the 95.2%, 97.4%, and 93.2% variations in soil respiration in the three steppes were explained by the change in soil moisture at a depth of 0-10 cm, respectively.
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This work is partly supported by the National Key Research and Development Program of China(Grant No.2020YFB1805403)the National Natural Science Foundation of China(Grant No.62032002)the 111 Project(Grant No.B21049).
文摘In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.
基金supported by the National Natural Science Foundation of China(Nos.42030707,72394404)the International Partnership Program of the Chinese Academy of Sciences(No.121311KYSB20190029)the Fundamental Research Fund for the Central Universities(Nos.20720210083,20720210082).
文摘Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,but the regional sources of halocarbons in China are not yet well comprehended.To investigate the characteristics,emissions,and source profiles,this study conducted a field campaign in Xiamen,a coastal city in southeastern China.Higher enhancements were found in the unregulated halocarbons(CH_(3)Cl,CH_(2)Cl_(2),CHCl_(3))than in the MP eliminated species(CCl_(4),CH_(3)Br)and theMP controlled species(HCFCs,HFCs).Many of the measured halocarbons varied seasonally and regionally,depending on the anthropogenic sources and atmospheric transport.Backward trajectory analysis showed that the air masses from inland were polluted over Shandong,Hebei,and northern Fujian in the cold season,while the air masses fromthe sea in the warm season were clean.Different air masses in two seasons were associated with the halocarbon patterns in the study area.Industrial activities,especially solvent usage,were the primary sources of halocarbons.The emission hot spots in Fujian Province were concentrated in Sanming,Fuzhou,and Xiamen,and the unregulated halocarbons made the largest contribution.This study provides an insight for a deep understanding of the characteristics and potential sources of halocarbons,and for strengthened management of halocarbons in China.
基金supported by funding from the National Key R&D Program of China(2023ZD0407304)the Sci-Tech Innovation 2030 Agenda(2022ZD0115703)Fundamental Research Funds for Central Non-Profit of Chinese Academy of Agricultural Sciences(Y2023PT20).
文摘Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional breeding methods raise concerns about reduced genetic diversity,epibreeding propels crop improvement through epigenetic variations that regulate gene expression,ultimately impacting crop yield.Epigenetic regulation in crops encompasses various modes,including histone modification,DNA modification,RNA modification,non-coding RNA,and chromatin remodeling.This review summarizes the epigenetic mechanisms underlying major agronomic traits in maize and identifies candidate epigenetic landmarks in the maize breeding process.We propose a valuable strategy for improving maize yield through epibreeding,combining CRISPR/Cas-based epigenome editing technology and Synthetic Epigenetics(SynEpi).Finally,we discuss the challenges and opportunities associated with maize trait improvement through epibreeding.
