Spatiotemporal distribution of regional landslides and erosion rates in Southeastern Tibet

The difficulty in estimating ages of regional landslides hampers to assess frequency of landslides and hence to quantitatively assess regional landslide hazard.In this study,we used radiocarbon dating of organic sediment on boulder rock varnish to estimate landslide ages in Langxian(LX)arid region in southeastern Tibet.Samples of rock varnish with organic sediment were collected on site for radiocarbon dating,leading to landslide ages from 1880±30 to 18,430±30 yr B.P.To measure surface roughness characteristics of 109 remotely-mapped large bedrock landslide deposits,we estimated average standard deviation of slope(SDS)over an area of~640 km^(2) by calculating the slope gradient of each raster cell and using a rectangular moving window method in Arc Map from a 5 m-resolution Digital Elevation Model generated from helicopterobtained photographs.Combing estimated landslide ages(t)with average surface roughness of mapped landslide deposits(R)quantified by SDS,we fit an exponential landslide deposits surface roughness-age function(t=1.47×10^(6)×e^(-1).46R,r2=0.63)that was used to estimate regional landslide ages in LX.We conclude that three periods with clusters of regional landslides in LX were revealed by different surface roughness of landslide deposits combing roughness-age function,with the values of 5563-7455 yr B.P.,1724-4151 yr B.P.,and 960-1287 yr B.P..Furthermore,we used our estimates of landslide ages to quantify landslide erosion rates of three corresponding hillslopes in LX ranging from 0.50 to 2.42 mm yr-1.Although rock varnish radiocarbon dating provides us a feasible option for timing regional landslides of arid regions,the epistemic uncertainty in the dating method should arouse our attention,which could be reduced by increasing the number of samples.

Spatiotemporal distribution and influencing factors of Ulva prolifera and Sargassum and their coexistence in the South Yellow Sea,China

Marine ecological disasters occurred frequently in recent years and raised widespread concerns about the ecological health of the ocean.We analyzed the spatiotemporal distributions of Ulva prolifera and Sargassum from April to July each year between 2016 and 2020 in the South Yellow Sea using multisource(GF-1 and HJ-1A/1B)remote sensing images,combined with the MODIS sea surface temperature(SST)data,photosynthetically active radiation(PAR)data,and Quick SCAT sea surface wind(SSW)data,to explore the potential influencing factors.The results show that(1)U.prolifera and Sargassum appeared mainly from May to July and April to June,respectively;(2)U.prolifera showed an impact in larger spatial scope than that of Sargassum.U.prolifera originated in the shoal area of northern Jiangsu and finally disappeared in the sea near Haiyang-Rongcheng area.The spatial scope of the impact of Sargassum tended to expand.Sargassum was first detected in the ocean northeast of the Changjiang(Yangtze)River estuary and disappeared near 35°N;and(3)correlation analysis showed that the SST influenced the growth rate of U.prolifera and Sargassum.PAR had varied eff ects on U.prolifera and Sargassum at different times.A moderate light conditions could accelerate the growth and reproduction of U.prolifera and Sargassum.High irradiance levels of ultraviolet radiation may cause photoinhibition and damage on U.prolifera and Sargassum.The southeast monsoon and surface currents promoted the drift of U.prolifera and Sargassum from the southeast to the northwest and north.Therefore,the spatial and temporal similarities and differences between U.prolifera and Sargassum were influenced by a combination of factors during their growth processes.

Remote Sensing-based Spatiotemporal Distribution of Grassland Aboveground Biomass and Its Response to Climate Change in the Hindu Kush Himalayan Region

The grassland in the Hindu Kush Himalayan(HKH) region is one of the large st and most biodiverse mountain grassland types in the world,and its ecosystem service functions have profound impacts on the sustainable development of the HKH region.Monitoring the spatiotemporal distribution of grassland aboveground biomass(AGB) accurately and quantifying its response to climate change are indispensable sources of information for sustainably managing grassland ecosystems in the HKH region.In this study,a pure vegetation index model(PVIM) was applied to estimate the long-term dynamics of grassland AGB in the HKH region during 2000-2018.We further quantified the response of grassland AGB to climate change(temperature and precipitation) by partial correlation and variance partitioning analyses and then compared their differences with elevation.Our results demonstrated that the grassland AGB predicted by the PVIM had a good linear relationship with the ground sampling data.The grassland AGB distribution pattern showed a decreasing trend from east to west across the HKH region except in the southern Himalayas.From 2000 to 2018,the mean AGB of the HKH region increased at a rate of 1.57 g/(m~2·yr) and ranged from 252.9(2000) to 307.8 g/m~2(2018).AGB had a positive correlation with precipitation in more than 80% of the grassland,and temperature was positively correlated with AGB in approximately half of the region.The change in grassland AGB was more responsive to the cumulative effect of annual precipitation,while it was more sensitive to the change in temperature in the growing season;in addition,the influence of climate varied at different elevations.Moreover,compared with that of temperature,the contribution of precipitation to grassland AGB change was greater in approximately 60% of the grassland,but the differences in the contribution for each climate factor were small between the two temporal scales at elevations over 2000 m.An accurate assessment of the temporal and spatial distributions of grassland AGB and the quantification of its response to climate change are of great significance for grassland management and sustainable development in the HKH region.

Validation and Spatiotemporal Distribution of GEOS-5-Based Planetary Boundary Layer Height and Relative Humidity in China

Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height （PBLH） and relative humidity （RH） data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions--North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows： Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China （less than 30%）. Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.

Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model

The spatiotemporal distribution and relationship between nominal catch-per-unit-ef fort(CPUE) and environment for the jumbo flying squid( Dosidicus gigas) were examined in of fshore Peruvian waters during 2009–2013. Three typical oceanographic factors aff ecting the squid habitat were investigated in this research, including sea surface temperature(SST), sea surface salinity(SSS) and sea surface height(SSH). We studied the CPUE-environment relationships for D. gigas using a spatially-lagged version of spatial autoregressive(SAR) model and a generalized additive model(GAM), with the latter for auxiliary and comparative purposes. The annual fishery centroids were distributed broadly in an area bounded by 79.5°–82.7°W and 11.9°–17.1°S, while the monthly fishery centroids were spatially close and lay in a smaller area bounded by 81.0°–81.2°W and 14.3°–15.4°S. Our results show that the preferred environmental ranges for D. gigas offshore Peru were 20.9°–21.9°C for SST, 35.16–35.32 for SSS and 27.2–31.5 cm for SSH in the areas bounded by 78°–80°W/82–84°W and 15°–18°S. Monthly spatial distributions during October to December were predicted using the calibrated GAM and SAR models and general similarities were found between the observed and predicted patterns for the nominal CPUE of D. gigas. The overall accuracies for the hotspots generated by the SAR model were much higher than those produced by the GAM model for all three months. Our results contribute to a better understanding of the spatiotemporal distributions of D. gigas off shore Peru, and off er a new SAR modeling method for advancing fishery science.

Spatiotemporal distribution model for zinc electrowinning process and its parameter estimation

This paper focuses on the distributed parameter modeling of the zinc electrowinning process(ZEWP)to reveal the spatiotemporal distribution of concentration of zinc ions(CZI)and sulfuric acid(CSA)in the electrolyte.Considering the inverse diffusion of such ions in the electrolyte,the dynamic distribution of ions is described by the axial dispersion model.A parameter estimation strategy based on orthogonal approximation has been proposed to estimate the unknown parameters in the process model.Different industrial data sets are used to test the effectiveness of the spatiotemporal distribution model and the proposed parameter estimation approach.The results demonstrate that the analytical model can effectively capture the trends of the electrolysis reaction in time and thus has the potential to implement further optimization and control in the ZEWP.

SPATIOTEMPORAL DISTRIBUTION CHARACTERISTICS AND VARIATION TRENDS OF HIERARCHICAL PRECIPITATION IN GUANGDONG PROVINCE OVER THE PAST 50 YEARS

The climatic characteristics of the precipitation in Guangdong province over the past 50 years were analyzed based on the daily rainfall datasets of 86 stations from 1961 to 2010. The rainfall was divided into five categories according to its intensity, and their spatiotemporal characteristics and variation trends were investigated. The annual rainfall amount was within 1,500 to 2,000 mm over most parts of Guangdong, but substantial differences of rainfall amount and rainy days were found among different parts of the province. There were many rainy days in the dry seasons （October to March）, but the daily rainfall amounts are small. The rainy seasons （April to September） have not only many rainy days but also heavy daily rainfall amounts. The spatial distributions of light rainy days （1 mm〈P〈 10 mm） and moderate rainy days （10 mm〈P〈 25 mm） resemble each other. The heavy rainy days （25 mm〈P〈 50 mm）, rainstorm days （50 ram〈P〈 100 mm） and downpour days （P〉 100 mm） are generally concentrated in three regions, Qingyuan, Yangjiang, and Haifeng/Lufeng. The average rainfall amount for rainy days increases form the north to the south of Guangdong, while decreasing as the rainfall intensity increases. The contributions from light, moderate and heavy rain to the total rainfall decreases form the north to the south. The annual rainy days show a decreasing trend in the past 50 years. The light rainy days decreased significantly while the heavy, rainstorm and downpour rainy days increased slightly. The annual total rainfall amount increased over the past 50 years, which was contributed by heavy, rainstorm and downpour rains, while the contribution from light and moderate rains decreased. Key words： spatiotemporal distribution; rainfall amount; rainy days; rainfall contribution rate

Cardiac resident macrophages: Spatiotemporal distribution, development, physiological functions, and their translational potential on cardiac diseases

Cardiac resident macrophages (CRMs) are the main population of cardiac immune cells. The role of these cells in regeneration, functional remodeling, and repair after cardiac injury is always the focus of research. However, in recent years, their dynamic changes and contributions in physiological states have a significant attention. CRMs have specific phenotypes and functions in different cardiac chambers or locations of the heart and at different stages. They further show specific differentiation and development processes. The present review will summarize the new progress about the spatiotemporal distribution, potential developmental regulation, and their roles in cardiac development and aging as well as the translational potential of CRMs on cardiac diseases. Of course, the research tools for CRMs, their respective advantages and disadvantages, and key issues on CRMs will further be discussed.

A comprehensive fluid-solid coupling dynamic simulation for spatiotemporal distribution of regression rate in hybrid rocket motors

The spatiotemporal distribution characteristics of the regression rate are crucial aspects of the research on Hybrid Rocket Motor(HRM). This study presents a pioneering effort in achieving a comprehensive numerical simulation of fluid dynamics and heat transfer in both the fluid and solid regions throughout the entire operation of an HRM. To accomplish this, a dynamic grid technique that incorporates fluid–solid coupling is utilized. To validate the precision of the numerical simulations, a firing test is conducted, with embedded thermocouple probes being used to measure the inner temperature of the fuel grain. The temperature variations in the solid fuel obtained from both experiment and simulations show good agreement. The maximum combustion temperature and average thrust obtained from the simulations are found to deviate from the experimental results by only 3.3% and 2.4%, respectively. Thus, it can be demonstrated that transient numerical simulations accurately capture the fluid–solid coupling characteristics and transient regression rate. The dynamic simulation results of inner flow field and solid region throughout the entire working stage reveal that the presence of vortices enhances the blending of combustion gases and improves the regression rate at both the front and rear ends of the fuel grain. In addition, oscillations of the regression rate obtained in the simulation can also be well corresponded with the corrugated surface observed in the experiment. Furthermore, the zero-dimension regression rate formula and the formula describing the axial location dependence of the regression rate are fitted from the simulation results, with the corresponding coefficients of determination(R^(2)) of 0.9765 and 0.9298, respectively.This research serves as a reference for predicting the performance of HRM with gas oxygen and polyethylene, and presents a credible way for investigating the spatiotemporal distribution of the regression rate.

Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor responsiveness.To address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and cleanness.Based on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system operator.Then,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both considered.To achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear relationships.Subsequently,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and feasibility.Finally,the simulation verification based on the IEEE 33-bus DN is conducted.The simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to respond.Meanwhile,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

Distribution and Formation Causes of PM_(2.5) and O_(3) Double High Pollution Events in China during 2013–20

Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribution of DHP events in China during 2013–20 is analyzed.The synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification method.The meteorological and chemical causes of DHP events controlled by the main synoptic types are further investigated.Results show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central China.The occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–20.The main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP day.Three pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,respectively.The results of this study can be informative for future decisions on the management of DHP events.

Spatiotemporal mapping of(ultra‐)mafic magmatic mine areas:Implications of economic and political realities in China

The spatiotemporal extension/expansion of mine areas is affected by multiple factors.So far,very little has been done to examine the interaction between mine areas and political or economic realities.The(ultra‐)mafic magmatic mines in China played a specific role in supporting national development and providing an ideal research subject for monitoring their interrelationship.In this study,remote sensing and mining‐related GIS data were used to identify and analyze 1233(ultra‐)mafic magmatic mine area polygons in China,which covered approximately 322.96 km2 of land and included a V–Ti–Fe mine,a copper–nickel mine,a chromite mine,an asbestos mine,and a diamond mine.It was found that(1)the areal expansion of mines is significantly related to the mine types,perimeter,topography,and population density.(2)The mine area variation also reflects market and policy realities.The temporal expansion of the mine area from 2010 to 2020 followed an S‐shaped pattern(with the turning point occurring in 2014),closely related to iron overcapacity and tightened mining policies.(3)The complexity(D)of the mine area may reflect mine design and excavation practices.To be specific,lower D indicates early‐stage or artisanal/small‐scale mining,whereas higher D represents large‐scale mining.This study demonstrates that the detailed mapping of mine land can serve as an indicator to implement miningrelated market and policy changes.The(ultra‐)mafic mines area data set can be accessed at https://zenodo.org/record/7636616#.Y-p0uXaZOa0.

Spatial and Temporal Distribution Characteristics of Solar Energy Resources in Tibet

The Tibet Plateau is one of the regions with the richest solar energy resources in the world.In the process of achieving carbon neutrality in China,the development and utilization of solar energy resources in the region will play an important role.In this study,the gridded solar resource data with 1km resolution in Tibet were obtained by spatial correction and downscaling of SMARTS model.On this basis,the spatial and temporal distribution characteristics of solar energy resources in the region in the past 30 years(1991–2020)are finely evaluated,and the annual global horizontal radiation resource is calculated.The results show that:1)The average annual global horizontal radiation amount in Tibet is 1816 kWh/m^(2).More than 60%of the area belongs to the“Most abundant”(GHI≥1750 kWh/m^(2))area of China’s solar energy resources category A,and nearly 40%belongs to the“Quite abundant”(1400≤GHI<1750)area of China’s solar energy resource category B.2)In space,the solar energy resources in Tibet increased gradually from north to south and from east to west.Lhasa,Central and Eastern Shigatse,Shannan,and Southwestern Ali are the most abundant cities,with a maximum annual radiation level of 2189 kWh/m2.3)In terms of time,the total horizontal radiation in Tibet was the highest in May and the lowest in December.74%of the total area belongs to the“Very stable”(R_(w)≥0.47)area of solar resource stability category A,and 26%belongs to the“stable”(0.36≤R_(w)<0.47)area of solar resource stability category B.Solar energy resources in the region show the characteristics of both strong and stable.Average solar energy resources in the region have shown a fluctuating downward trend over the past 30 years,with an average decline of about 12.86(kWh/m2)per decade.4)In terms of solar radiation resources reaching the earth’s surface,the theoretical total amount of annual horizontal radiation in Tibet is about 240.07 billion tons of standard coal or 222.91 billion kilowatts on average.

Spatiotemporal distribution and historical evolution of polders in the Dongting Lake area, China

Dongting Lake is the largest lake in the middle reaches of the Yangtze River in China. For centuries, people inhabiting the Dongting Lake area have been reclaiming land and constructing dams for flood resistance, agricultural production, and rural settlement, forming geographical entities known as polders. In this study, the regional spatial distributions of polders in the Dongting Lake area in 1949, 1998, and 2013 were obtained using historical maps and modern remotely sensed data, revealing changes since the establishment of the People's Republic of China. Nanxian County was then selected to demonstrate polder changes at the county level, because it has undergone the most dramatic changes in the area. Different polder change models for the Datonghu, Yule, and Renhe polders were analyzed for eight periods: 1644(the early Qing Dynasty), 1911(the late Qing Dynasty), 1930(the Republic of China), 1949(the People's Republic of China), 1963, 1970, 1998, and 2013. Three resulting polder evolution models are: 1) reclaiming polders from lakes, 2) integrating polders by stream merging, and 3) abandoning polders for flood release. The polder evolution models demonstrate the wisdom of local people in using land resources according to the specific regional conditions. Throughout their long-term historical evolution, the spatial distribution of polders in the Dongting Lake area tended to be homogeneous, and the degree of human disturbance tended to be stable. However, a shift occurred, from pure polder area growth or removal to more comprehensive management and protection of the regional environment.

Spatiotemporal distribution of protists in the Yarlung Zangbo River,Tibetan Plateau

Protists,which include eukaryotic algae and protozoa,are crucially important for biogeochemical cycling and the aquatic food web but are sensitive to environmental fluctuations.Despite investigations in the 1970s,protist diversity and biogeographic characteristics in the Tibetan Plateau are poorly understood.Within the framework of a regional survey of protist diversity,we used high-throughput amplicon sequencing to investigate the composition and spatiotemporal turnover of protist communities along the Yarlung Zangbo River,a representative aquatic habitat of the Tibetan Plateau.In total,we detected 9,959 amplicon sequence variants in protist communities along the river and associated lakes and wetlands.The alpha diversity of protists was highest in spring and declined in the autumn.Moreover,alpha diversity was much higher in the middle and upstream reaches and tributaries than in the connected lakes and wetlands.We discovered spatiotemporal heterogeneity in the composition of protist communities across the seasons.Bacillariophyta predominated in protist communities in cold seasons(spring and autumn)and colder(high-altitude)areas,whereas Ciliophora and Cercozoa species predominated in the warm season(summer)and warmer(low-altitude)areas.Of the environmental factors,altitude,turbidity and salinity correlated with spatiotemporal dissimilarities among protist communities.The breadth of the habitat niche was restricted by turbidity and altitude in river areas and by salinity in lake and wetland areas.Co-occurrence network analysis suggested that protist communities in the Yarlung Zangbo River were substantially more complex in the warm season than in the cold seasons,and that amplicon sequence variants belonging to Ochrophyta,Chlorophyta,and Ciliophora contributed greatly to the stability of the cooccurrence network.In summary,this study provides a comprehensive overview of the spatiotemporal dynamics of protist diversity in the Yarlung Zangbo River and improves our understanding of the environmental adaptation of protists living in aquatic habitats of the Tibetan Plateau.

Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.

GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems

Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.

Abrupt change of winter temperature over the Mongolian Plateau during 1961-2017

Studying the abrupt change of winter temperature(ACWT)over the Mongolian Plateau(MP,including Inner Mongolia Autonomous Region and State of Mongolia)is of great significance for understanding the spatiotemporal distribution of temperature and the mechanism of global climate change.Monthly temperature data during 1961–2017was collected,and the abrupt change point was determined by the Mann–Kendall test and sliding ttest,to analyze the characteristics and causes of ACWT.The results showed that(a)The winter temperature has rapidly increased with a trend of 0.41℃/10a,which was significantly higher than that of the rest area of Chinese mainland,indicating that climate change in the MP was more sensitive to global warming.(b)The abrupt change point occurred in 1988,with temperature of-15.5℃and-14.1℃before and after abrupt change,respectively.The ACWT in 50°N was 1–3 years later than that in 40°N,and the isotherms of different temperatures moved northward by 10–200 km,especially-16℃isotherms moved approximately 200 km northward after 1988.(c)The Arctic Oscillation(AO)and Mongolian High(MH)anomaly affects winter temperature over the MP.When the AO is unusually strong,the MH and East Asian winter monsoon are weak,and southerly winds prevail in most regions,which is not conducive to the cold air developing southward,leading to higher winter temperature in the MP.Overwise,abnormally northerly winds prevail and temperature is low.Meanwhile,the abrupt change time of AO occurred in 1987 before winter temperature.It shows that the AO indirectly causes winter temperatures to rise by influencing the MH and is also the main driving factor of ACWT.

Distribution characteristics and removal rate of antibiotics and antibiotic resistance genes in different treatment processes of two drinking water plants

Emerging pollutants,such as antibiotics and antibiotic-resistance genes,are becoming increasingly important sources of safety and health concerns.Drinking water safety,which is closely related to human health,should receive more attention than natural water body safety.However,minimal research has been performed on the efficacy of existing treatment processes in water treatment plants for the removal of antibiotics and antibiotic resistance genes.To address this research gap,this study detected and analyzed six main antibiotics and nine antibiotic resistance genes in the treatment processes of two drinking water plants in Wuhan.Samples were collected over three months and then detected and analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry and fluorescence quantitation.The total concentrations of antibiotics and antibiotic resistance genes in the influent water of the two water plants were characterized as December>March>June.The precipitation and filtration processes of the Zou Maling Water Plant and Yu Shidun Water Plant successfully removed the antibiotics.The ozone-activated carbon process increased the removal rate of most antibiotics to 100%.However,a large amount of antibiotic resistance gene residues remained in the effluents of the two water plants.The experiments demonstrated that the existing ozone-activated carbon processes could not effectively remove antibiotic resistance genes.This study provides a reference for the optimization of drinking water treatment processes for antibiotics and antibiotic resistance gene removal.

Spatiotemporal characteristics and Monte Carlo simulationbased human health risk of heavy metals in soils from a typical coal-mining city in eastern China

Mining activities typically discharge considerable amounts of heavy metals into the environment,raising concerns about soil metal pollution,environmental security,and human well-being.Therefore,a systematic regional-scale investigation of soil heavy metal pollution in mining areas is necessary for soil management.In this study,5817 soil samples from the Huainan coal mining area collected for studies conducted from 2000 to 2021 were compiled to quantify the pollution level and spatiotemporal variation of heavy metals(Cu,Pb,Zn,Cr,Cd,As,Hg,Ni,and Mn).The associated ecological health risk of heavy metals in soil was assessed using the Hakanson ecological hazard index,Monte Carlo simulation in conjunction with the total hazard quotient,and the hazard index.Cd was the top contaminant,followed by Hg.In terms of spatial distribution,heavy metal contamination was more severe in the eastern area of Fengtai and Datong districts,because these districts of Anhui Province are significant industrial regions.In addition,the results of the Monte Carlo evaluation of human health risks showed that the total noncarcinogenic risk of heavy metals in soil is below the acceptable level,while the carcinogenic risk was 5.97%for adults and 15.53%for children.As accounted for 57.4%of noncarcinogenic risk,Cr contributed 36.1%of carcinogenic risk.Compared with adults,children are more vulnerable to the carcinogenic and noncarcinogenic risks posed by heavy metals,with oral consumption being the primary exposure route.This research can provide useful details for protecting the environment and managing soil in a coal mining area.