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Background: In the context of public health emergencies, the presence of medical and health talents (MHT) is critically important for support in any country or region. This study aims to analyze the spatial and temporal distributions and evolution of MHT in China and propose strategies and recommendations for promoting a balanced distribution. Methods: This research used data from 31 provinces in China to construct a multidimensional index system for measuring the agglomeration level of MHT. The indices include talent agglomeration density (TAD), talent agglomeration scale (TAS), talent agglomeration intensity (TAI), and talent agglomeration equilibrium (TAE). Using provincial data from the years 1982, 1990, 2000, 2010, and 2020, a spatiotemporal analysis of the MHT agglomeration levels was conducted. Furthermore, the regional dynamic distribution of MHT was analyzed using kernel density estimation diagrams. The spatial autocorrelation of MHT was assessed through global and local Moran's I, and the spatial gap and decomposition of MHT were analyzed using the Dagum Gini coefficient. Results: From the temporal level, the TAD and TAI of MHT showed an increasing trend over the studied period, whereas TAS decreased and TAE first increased and then decreased from 1982 to 2020. At the spatial level, the TAD, TAS, TAI, and TAE of MHT exhibited varied patterns among the eastern, central, and western regions of China, showing significant geographical disparities, generally demarcated by the Hu Huanyong Line. The regional dynamic distribution level of MHT in the country and the three regions were expanding. Spatial autocorrelation analysis using global and local Moran's I for TAD, TAS, TAI, and TAE demonstrated significant regional differences. The Dagum Gini coefficient of TAD, TAS, TAI, and TAE revealed divergent trends in regional disparities, with overall declines in disparities for TAD and TAI, a slight increase for TAS, and fluctuating patterns for TAE. Conclusions: From a temporal perspective, the overall number of MHT in China has been increasing annually at the national and provincial levels. From the spatial perspective, TAD, TAS, TAI, and TAE exhibit significant differences among the three regions. Kernel analysis reveals that the distribution differences are gradually expanding in national level and varying in regional level. Moreover, the global and local Moran's I indices reveal varying spatial autocorrelation for TAD, TAS, TAI, and TAE. The Dagum Gini coefficients of TAD, TAS, TAI, and TAE show different patterns of decomposition. [ABSTRACT FROM AUTHOR]

Accurate prediction of spatial–temporal extreme wind gust is vital for the wind farm dynamic regulation, the floating wind turbine deployment and its early warning. Deep-learning approaches have been applied for wind prediction to alleviate the computational challenges of traditional numerical models. Yet, most previous studies emphasized the prediction accuracy only employing location-specific dataset, such methodologies are site-specific and ignore the importance of spatial–temporal fidelity. Furthermore, the Recurrent Neural Networks (RNN)-based approach previous employed exhibit low efficiency in terms of model convergence and on the aspect of practical engineering purposes. This study firstly proposed the wind gust prediction net (WGPNet), using residual learning with attention modulations to predict the instantaneous spatial–temporal wind gust in the West Pacific region with great potential wind-energy. And a public reanalysis dataset with very high resolution (0.25° x 0.25°) was employed to verify the proposed method under different criteria. The overall RMSE of predicted gust fields obtained by the proposed method dropped to 0.18 m/s. Comprehensive discussions with both temporal and spatial perspective, revealing that the proposed model can offer an accurate 2D wind gust prediction along timeline (the PCC equals to 0.98). [ABSTRACT FROM AUTHOR]

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 via mobile measurements exhibited more 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. [Display omitted] [ABSTRACT FROM AUTHOR]

With global environmental changes, lung cancer has become one of the most common types of cancer worldwide, posing a significant public health challenge. Jiangsu Province, located in the eastern part of China, is an economically and socially developed region. According to the latest cancer registration data in Jiangsu Province, lung cancer ranks first in both incidence and mortality of cancer in the province. Thus, studying the spatiotemporal distribution of lung cancer cases and analyzing the influence of various factors on this distribution are crucial for the effective prevention and control of the disease in Jiangsu Province. This study takes the statistical data of lung cancer patients in Jiangsu Province in 2020 as the research object, uses Geographic Information System (GIS) visualization and spatial analysis to study the spatial distribution characteristics of lung cancer patients in Jiangsu Province, and employs the geographical detector to numerically express the impact of various environmental factors on the distribution of lung cancer patients in Jiangsu Province. The results reveal a notable spatial clustering of lung cancer cases, with high-incidence areas concentrated in Suzhou, Nanjing, and Xuzhou cities. Among the seven environmental factors examined, PM2.5, SO2, and PM10 concentration exert the most significant influence. This study employs multifactorial spatial analysis to elucidate the intricate relationships between people's health and air quality, medical resource distribution, and lung cancer incidence in the process of pursuing sustainable development in cities and provides an important reference for the improvement in lung cancer prevention and control strategies. [ABSTRACT FROM AUTHOR]

This study investigated the influence of sea–land breezes on nocturnal spatial and temporal distribution of ozone (O3) and its potential effects on particulate nitrate formation in Qingdao, a coastal city in northern China. Observation campaigns were conducted to measure surface air pollutants and meteorological factors during a typical sea–land breezes event from 22 to 23 July 2022. A coherent Doppler lidar (CDL) system was employed to continuously detect three-dimensional wind fields. The results revealed that nocturnal ozone levels were enhanced by a conversion of sea–land breezes. Initially, the prevailing northerly land breeze transported high concentrations of O3 and other air pollutants from downtown to the Yellow Sea. As the sea breeze developed in the afternoon, the sea breeze front advanced northward, resulting in a flow of high O3 concentrations back into inland areas. This penetration of the sea breeze front led to a notable spike in O3 concentrations between 16:00 on 22 July and 02:00 on 23 July across downtown areas, with an average increase of over 70 μg/m3 within 10 min. Notably, a time lag in peak O3 concentration was observed with southern downtown areas peaking before northern rural areas. During this period, combined pollution of O3 and PM2.5 was also observed. These findings indicated that the nighttime increase in O3 concentrations, coupled with enhanced atmospheric oxidation, would likely promote the secondary conversion of gaseous precursors into PM2.5. [ABSTRACT FROM AUTHOR]

Single-season rice describes the area under rice cultivation from May–October of the year. Many scholars have used lower-resolution data to study single-season rice in different regions, but using high-precision and high-resolution single-season rice data can reveal new phenomena. This paper uses a long-time-series, high-precision, and high-resolution single-season rice cultivation dataset to conduct an in-depth analysis of the spatial–temporal variability characteristics of single-season rice in Jiangsu Province, China, from 2017 to 2021. It explores the correlation between meteorological factors and greenhouse gasses for single-season rice. It analyzes the driving role of social factors on single-season rice. The results showed that single-season rice was mainly grown in the central and northeastern regions of the study area. The single-season rice cultivation was significantly reduced in 2020 due to the impact of COVID-19. Single-season rice strongly correlates with meteorological factors in time but shows a weak spatial correlation. This is because human factors largely dominate the area under single-season rice cultivation. Methane emissions in the study area are mainly influenced by anthropogenic activities rather than single-season rice. Social factors are essential in controlling single-season rice cultivation in the study area. This study was conducted in Jiangsu Province, China. Still, the methodology and results have important implications for agricultural production and environmental management studies in other regions, and some findings have general applicability. [ABSTRACT FROM AUTHOR]

The ecological water demand is of crucial importance for the health and sustenance of oasis ecosystems in arid and semi-arid regions. This study utilized the area quota method, phreatic evaporation method, and plant evapotranspiration method to estimate the ecological water demand of natural vegetation and analyze the temporal and spatial distribution characteristics of ecological water demand in the Aksu River Irrigation District. The results indicated that the current ecological water demand of forestland and grassland is 1.011–1.251 × 108 and 2.429–2.761 × 108 m3, respectively. Moreover, the ecological water demand of forestland and grassland under the restoration target was 2.243–2.776 × 108 and 2.594–2.948 × 108 m3, respectively. The vegetation ecological water demand exhibited a significant seasonal difference, with summer > spring > autumn > winter. The spatial distribution of vegetation ecological water demand was wide and significantly different, with noticeable high-value areas and low-value areas. The phreatic evaporation method and vegetation evapotranspiration method were deemed reasonable and reliable for calculating the appropriate ecological water demand and maximum ecological water demand of vegetation, respectively. The research results hold significant value in guiding natural vegetation restoration, regional water resources allocation and regulation of ecological water demand in the Aksu River Basin. [ABSTRACT FROM AUTHOR]

An investigation into the spatial–temporal distribution characteristics of ancient settlements and their relationship with the environment in the Sichuan Basin can enhance our understanding of the evolution of the regional human–land relationship. Utilizing kernel density analysis by GIS, this paper obtained the spatial distribution characteristics of 1100 settlements in the Neolithic, Shang–Zhou, and Qin to Southern Dynasties periods. Subsequently, a GIS spatial analysis was performed to examine the distribution of these settlements in relation to the natural environment, focusing on four aspects: elevation, slope, aspect, and water buffer zone. The results demonstrate that: (1) The distribution of settlements from the Neolithic to the Southern Dynasties has expanded from the Chengdu Plain in the west and the Xiajiang Area in the east to the hilly areas in the center. (2) The settlements in the Neolithic and Shang–Zhou periods are predominantly located at elevations between 300–600 m, slopes between 0–3°, aspects between 135–225°, distances to rivers between 0–1000 m, and soil choice on Luvisols, Cambisols, Regosols, and Anthrosols. The influence of aspect on settlements during the Qin–Southern Dynasties period was notably reduced. The settlements mainly grow in the Chengdu Plain and the smaller plains along the river from the Neolithic to the Southern Dynasties in the Sichuan Basin. (3) The emergence and advancement of primitive agriculture, the construction of early water conservancy facilities, commercial and trade exchanges, and the establishment of regimes led to a shift from a double core to a more dispersed distribution in the Sichuan Basin from the Neolithic to the Southern Dynasties periods. The evolution of settlements reflects the adaption and competition of the residents to the natural environment in the Sichuan Basin. Furthermore, it provides insights into the complex social development in the region, ranging from the formation of early states to the establishment of the Qin and Han Empires. [ABSTRACT FROM AUTHOR]

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In order to understand the community structure and distribution characteristics of macrobenthic shellfish in the coastal waters of Zhejiang, the fixed-point bottom trawl fishery resources survey was conducted from August 2020 to April 2021. The surveyed sea was divided into two areas, the northern and the southern part in Zhejiang, with 29°N as the boundary. A total of 41 species of shellfish belonging to 25 genera, 25 families and 6 orders were collected and identified. The absolute dominant species in all seasons were Bursa rana and Turritella terebra bacillum. There were obvious regional differences in number of species and shellfish biomass distribution in the north and the south areas during different seasons. The shellfish biomass for spring and autumn was higher than that for summer and winter, and it decreased from the north to south area in other seasons except summer. In summer, differences in the average biomass of shellfish were not found in the north region and the south areas. In terms of diversity analysis, The richness index (D) and the diversity index (H') were the highest in spring and the lowest in summer, and the evenness index (J') was the highest in winter and the lowest in spring. Hierarchical Cluster analysis (Cluster) results showed that the shellfish communities were divided into 3 groups at 60% similarity level in Zhejiang coastal waters. Group Ⅰ was in the southern area in spring, summer and autumn, Group Ⅱ was in the northern area in spring, summer and autumn, and Group Ⅲ was the whole area in the winter, and there were differences in the north and the south areas in spring, summer and autumn. The stress value of non-metric multidimensional analysis was 0.08, which had explanatory significance. CCA analysis showed that depth and bottom sea temperature had significant effects on benthic shellfish distribution. This study can provide some reference for shellfish biodiversity conservation and sustainable use for shellfish resources in the coastal waters of Zhejiang. [ABSTRACT FROM AUTHOR]

Absorbing aerosols can absorb solar radiation, affect the atmospheric radiation balance, and further have a profound influence on the global and regional climates. The absorption aerosol optical depth (AAOD) as well as the absorption Angstrom exponent (AAE) across China over 2005–2018 were systematically studied through the Ozone Monitoring Instrument (OMI) dataset. The monthly AAOD samples from the OMI generally showed a good correlation (~0.55) compared to the monthly data from AERONET at four typical sites (North: Xianghe, East: Taihu, South: Hongkong Polytechnic Univ; Northwest: Sacol) across China. The ensemble annual average of the OMI AAOD at 388 and 500 nm is 0.046 and 0.022, with minor changes during 2005–2015, and a relatively fast increase after that. The winter and spring seasons depict the maximum mean AAODs, followed by autumn, whereas summer shows minimum levels. On the contrary, the high AAE values appear in summer and low values in winter. The order of the annual average AAOD500 from 2005 to 2018 is the Tarim Basin (TB, 0.041) > the Yellow River Basin (YRB, 0.023) > Beijing and Tianjin (BT, 0.026) > the Sichuan Basin (SB, 0.023) > Nanjing and Shanghai (NS, 0.021) > the Pearl River Delta (PRD, 0.017), whereas the AAE388–500 exhibits the opposite trend except for the TB (3.058). From 2005 to 2018, the AAOD rises by nearly 1.5–2.0 fold in the six typical regions, implying a severe situation of dust and/or BC aerosol pollution in the last several years. The monthly mean AAOD388 over the TB, the SB, the YRB, BT, the PRD, and NS is estimated to be smallest at 0.072, 0.024, 0.026, and 0.027 in July, 0.024 in June, and 0.025 in September, respectively, whilst largest in January for NS, the YRB and BT, April for the TB, February for the SB, and March for the PRD with 0.055, 0.077 and 0.067, 0.123, and 0.073 and 0.075, respectively. The monthly averaged AAOD500 in each region is consistently about half of the AAOD388. The highest AAE appears in June while the lowest values are in December and January, and the daily AAE values in episode days slightly decrease as compared to non-episode days. Our study indicates that northwestern China plays an important role in the overall AAOD as a result of dust aerosols stemming from desert areas. Moreover, the meteorological conditions in winter and early spring are associated with more energy consumption conducive to the accumulation of high black carbon (BC) aerosol pollution, causing high alert levels of AAOD from November to the following March. [ABSTRACT FROM AUTHOR]

Abstract The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment.

Due to coastal development expansion, an increasing influx of pollutants enters the sea through riverine input and land runoff, threatening coastal ecosystems and posing a risk of eutrophication. In this study, trace metals (Fe, Mn, Cu, and Zn), and nutrients (constituents of N, P, and Si) were assessed in the summer surface seawater of Yantai Sishili Bay (YSB), Northern China focusing on the determination of concentration, spatial-temporal distribution and sources identification, while exploring their correlations. It also aimed to clarify the eutrophication status and evaluate the linear relationships between eutrophication, trace metals, and nutrients in YSB. Over three years (2021-2023), the total dissolved concentrations of Fe, Mn, Cu, and Zn ranged from 4.79-26.71, 0.19-6.41, 0.26-1.53, and 0.74-13.12 µg/L, respectively. Concurrently, nutrient concentrations including NO2-, NO3-, NH4+, PO43-, and DSi exhibited a range of 0.37-11.66, 2.04-178.30, 1.69-70.01, 0.02-16.68, and 0.02-0.71 µg/L respectively. These concentrations revealed a gradual decrease from nearshore to offshore and the temporal variation also showed significant patterns from year to year, indicating distinct regional variations. The primary contributors to the trace metals and nutrients in the study region were recognized as external contributions stemming from natural, anthropogenic, and atmospheric deposition through correlation and principal component analysis. More specifically, riverine input and coastal farming contributed large amounts of nutrients to coastal waters, threatening a potential risk of eutrophication. The eutrophication evaluation expressed below the mild eutrophication level and was far lower than the other global and Chinese bays. The linear correlation between eutrophication and trace metals revealed a weak positive correlation but a significant correlation with nutrients. Despite the absence of significant eutrophication in the bay, potential risks were identified due to identifiable sources of nutrient and trace metal inputs. The findings provided insights to guide efforts in preventing and mitigating coastal eutrophication, as well as nutrient and trace metal pollution, in coastal cities. [ABSTRACT FROM AUTHOR]

The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment. [ABSTRACT FROM AUTHOR]

The current interaction of pedestrian flow and environmental pollutants in high-occupancy public areas of apartment and the risks of residents being exposed to environmental pollutants are issues that are often overlooked but urgently need to be addressed. In this study, we provide a comprehensive of pedestrian flow-environmental pollutants interactions and health risks to residents in first-floor public areas of apartment with high-occupancy. The main findings indicate that under closed management conditions, there is a significant increase in TVOC and noise levels during the peak periods of nighttime pedestrian flow. In the correlation analysis, the significant impact of time granularity selection in clarifying the correlation between pedestrian flow and environmental pollutants has been highlighted, with larger time granularities generally showing stronger correlations, while finer time granularities may help identify specific risks in areas directly connected to the external environment. There is a significant correlation exists between pedestrian flow and environmental pollutants (TVOC, ozone, and noise), with higher concentrations of these pollutants observed during peak pedestrian flow periods, thereby increasing the risk of residents being exposed to adverse environmental conditions. To mitigate the risks associated with TVOC pollution and noise exposure, it is crucial to maintain proper ventilation, avoid conducting cleaning or maintenance activities during peak hours, and implement noise-reducing measures, such as distancing noise sources from residential areas or installing soundproofing barriers. Additionally, the study identifies total volatile organic compounds originating from property maintenance activities and clarifies their dispersion patterns, emphasizing the importance of developing robust, standardized maintenance protocols for indoor environmental quality assurance. This research can improve the environmental sustainability of apartment buildings and provide a theoretical basis for the development of environmental health strategies for high-occupancy public areas of apartment buildings.

The adverse effects of antimony (Sb) pollution on ecosystems and human health caused by its use, enrichment, and bioaccumulation have become global environmental problems, particularly in China. Based on a scientometric analysis of the research topics and evolution of Sb pollution, 210 peer-reviewed articles across 264 locations in China were selected to analyze Sb concentrations, changes, and risks in different environments (i.e., soil, sediment, and water). Substantially elevated concentrations were reported in the chosen environments throughout the studied literature, with approximately 36.6%, 41.3% and 20.8% of the soil, water and sediment sampling sites, respectively, exceeding the national and international guidelines. Although Sb concentrations were stable in water and sediment, those in soil slightly increased slightly over the past two decades. The majority of studies and the highest Sb concentrations were typically concentrated in Hunan, Guangxi, and Guizhou, where most Sb deposits and intensive mining and smelting activities are concentrated. A temporal analysis over three crucial periods of the Sb industry further indicated that Sb concentrations and pollution had increased in several provinces in recent years. The estimated risk quotient, using Monte Carlo simulations, indicated that species were markedly affected by Sb contamination, with 21.6% of events occurring in the high-risk category. The ingestion of contaminated soils posed the highest potential health risk to the population, with 47.9% of the events indicated to represent at least a low risk. Risks of water ingestion were estimated to exist in 4.9% of the simulated exposure events. More environmental campaigns for Sb pollution control are urgently needed, especially in Sb hotspots, to reduce environmental pressure and avoid direct and indirect hazards to organisms and populations. [ABSTRACT FROM AUTHOR]

Soil salinization is one of the main hazards affecting the sustainable development of agriculture in the Hetao Irrigation District (HID) of Inner Mongolia. To grasp the water and salt transport patterns and spatial–temporal distribution characteristics of the HID at the regional scale, the improved Soil and Water Assessment Tool with a salinity module (SWAT-Salt) model was used to establish the distributed water and salt transport model for the watershed in this study. The results demonstrated that the modified model could more accurately represent the process of water and salt changes in the HID. The coefficient of determination (R2) in the simulation of streamflow and discharge salt loading was 0.83 and 0.86, respectively, and the Nash–Sutcliffe efficiency (NSE) was 0.80 and 0.74, respectively. Based on this, different hydrological processes (surface runoff, lateral flow, groundwater, soil seepage) as well as spatial–temporal distribution characteristics of water salinity in groundwater and soil were analyzed in the HID. Differences in groundwater and soil salinity in different land uses and soil types were also compared. Of these, surface runoff and lateral flow salt discharge loading are concentrated in the southwestern portion of the basin, while groundwater salt discharge loading is concentrated in the eastern as well as southwestern portions of the basin. The salt discharge loading from groundwater accounts for about 98.7% of the total salt discharge loading from all hydrological pathways and is the major contributing part of salt discharge from the irrigation area. Soil salinity increases gradually from west to east. Groundwater salinity (2946 mg/L) and soil water electrical conductivity (0.309 dS/m) were minimized in the cropland. Meanwhile, rational allocation of irrigation water can appropriately increase the amount of salt discharge loading. In conclusion, the model could provide a reference for the investigation of soil salinization and water–salt management measures in irrigation areas. [ABSTRACT FROM AUTHOR]

Japanese anchovy (Engraulis japonicus) is a small pelagic fish with commercial and ecological importance. In spite of its importance, in recent years, specific research on anchovy in the Shandong Peninsula area has been relatively scarce and outdated. This study aims to estimate the age and growth characteristics of anchovy through year-round seasonal sampling from 2016 to 2017, utilizing length–frequency and otolith microstructure analysis. The higher coastal abundance and larger size observed in the spring and summer suggest a potential peak spawning period for anchovies dominated by larger-sized individuals. Based on otolith analysis, anchovies range in age from 0 to 4 years, with a limited presence at age 0 and dominance in the age-1 group. The length–weight relationship (LWR) equation shows hyper-allometric growth for each season, with a mean relative condition factor (Kn) of 1.025 ± 0.005, indicating good health. Additionally, the von Bertalanffy growth equation of can be expressed as Lt = 154.40 [1 − e−0.604 (t + 0.965)], suggesting a medium growth rate (K = 0.604). These findings contribute to the understanding of anchovy age and growth patterns, emphasizing the continuous need for research and monitoring to support rational and sustainable fisheries management and conservation efforts. [ABSTRACT FROM AUTHOR]

To investigate the spatial-temporal distribution characteristics of Harpadon nehereus in the Yangtze River Estuary (YRE) and its relationship with environmental factors, this study used the data from resource and environmental surveys conducted in the YRE and adjacent waters during August (summer) and November (autumn), 2017-2022. Generalized additive models (GAM) were employed to analyze the relationships between the relative resources of H. nehereus and environmental factors and to predict the spatial-temporal distribution of H. nehereus resources in 2022. Our results revealed that the best model deviance explained in summer and autumn was 64.89% and 49.90%, with average effect sizes of 0.75 and 0.70, respectively, for cross-validated regression slopes. Water temperature and salinity were identified as the key environmental factors influencing the relative resources of H. nehereus in the YRE. Overall, there were notable seasonal differences in the relationship between the relative resources of H. nehereus and environmental factors. The relative resources of H. nehereus in the YRE were higher in the summer than in autumn. In summer, both water temperature and salinity exhibited multi-wave nonlinear relationships with the relative resources of H. nehereus, while in autumn, the relative resources of H. nehereus showed a positive linear relationship with water temperature and a nonlinear relationship with salinity. Additionally, the predicted and observed values of the relative resources of H. nehereus in 2022 showed similar spatial distribution patterns. The relative resources of H. nehereus was higher in the northern branch than in the southern branch and the offshore regions compared to the near-estuary regions. Altogether, our study provides a scientific basis for conservation management and sustainable utilization of H. nehereus resources in the YRE, thereby contributing to the restoration and management of fishery resources in the region. [ABSTRACT FROM AUTHOR]

Due to coastal development expansion, an increasing influx of pollutants enters the sea through riverine input and land runoff, threatening coastal ecosystems and posing a risk of eutrophication. In this study, trace metals (Fe, Mn, Cu, and Zn), and nutrients (constituents of N, P, and Si) were assessed in the summer surface seawater of Yantai Sishili Bay (YSB), Northern China focusing on the determination of concentration, spatial-temporal distribution and sources identification, while exploring their correlations. It also aimed to clarify the eutrophication status and evaluate the linear relationships between eutrophication, trace metals, and nutrients in YSB. Over three years (2021–2023), the total dissolved concentrations of Fe, Mn, Cu, and Zn ranged from 4.79–26.71, 0.19–6.41, 0.26–1.53, and 0.74–13.12 µg/L, respectively. Concurrently, nutrient concentrations including NO2-, NO3-, NH4+, PO43-, and DSi exhibited a range of 0.37–11.66, 2.04–178.30, 1.69–70.01, 0.02–16.68, and 0.02–0.71 µg/L respectively. These concentrations revealed a gradual decrease from nearshore to offshore and the temporal variation also showed significant patterns from year to year, indicating distinct regional variations. The primary contributors to the trace metals and nutrients in the study region were recognized as external contributions stemming from natural, anthropogenic, and atmospheric deposition through correlation and principal component analysis. More specifically, riverine input and coastal farming contributed large amounts of nutrients to coastal waters, threatening a potential risk of eutrophication. The eutrophication evaluation expressed below the mild eutrophication level and was far lower than the other global and Chinese bays. The linear correlation between eutrophication and trace metals revealed a weak positive correlation but a significant correlation with nutrients. Despite the absence of significant eutrophication in the bay, potential risks were identified due to identifiable sources of nutrient and trace metal inputs. The findings provided insights to guide efforts in preventing and mitigating coastal eutrophication, as well as nutrient and trace metal pollution, in coastal cities.

Study region: Mihe River Basin, China. Study focus: The composite interaction of natural and anthropogenic factors has increased the complexity of hydrological variation and pollutant transformation in rivers, making it challenging to effectively analyze the spatial and temporal distribution characteristics of pollution sources. We combined two empirical models to quantitatively assess the spatial-temporal distribution of pollution sources in a high-flow variable river such as the Mihe River, providing a scientific basis and methodological support for watershed management. New regional hydrological insights: The findings show that: (1) The average nitrogen and phosphorus loading of the river during 2015–2021 were 13.08 × 103 and 38.03 t·a-1, respectively, exhibiting significant fluctuations with flow; (2) a load apportionment model (LAM) revealed that nonpoint sources were primary pollution sources for most of the period, and average contributions of nitrogen and phosphorus loading accounted for 81.7 and 99.6%, respectively; (3) an export coefficient model (ECM) revealed that nutrient loading was concentrated in the middle and lower reaches, which was highly consistent with the distribution of cropland and urban land. (4) The results of the two methods were consistent. However, LAM and ECM underestimate and overestimate total nutrient loading, respectively. Combining these two methods facilitates the accurate determine of spatial and temporal distribution of pollution sources in a high-flow variable river.

Using the surface meteorological observation data of 76 national meteorological stations in Hubei Province from 1961 to 2022, the drought and flood processes based on the meteorological drought composite index (MCI) and effective precipitation index (EP) are first identified. Then we analyze the spatial-temporal distribution of the frequency of the drought-flood processes, the characteristics of the drought-flood year, the drought-flood transitions over the past 62 years, and the characteristics of drought and flood processes since 2010. The results show that the frequent occurrence area of droughts and floods in Hubei Province is generally characterized by the flaky distribution with floods in the east and droughts in the west, while floods in the south and droughts in the north. The occurrence frequency of droughts and rainstorm floods shows a fluctuating decreasing and increasing trend, respectively. The droughts mainly occur in spring and summer-autumn with a decreasing trend in frequency, but an increasing trend is found in the summer-autumn droughts and extreme droughts. Comparatively, the rainstorms mainly concentrate in summer and show an increasing trend in frequency. The annual variation of drought-flood year is characterized by continuous droughts for 2-4 years, continuous floods for 2-3 years, or alternation of droughts and floods. In some years, droughts and floods coexist in the same year, while abrupt drought-flood transitions are also found. However, there has been no drought-flood coexistence in the same year since 2010. The annual variation of the number of stations with drought-flood transition fluctuates greatly, showing a five-stage increasing characteristic with the maximum value of each stage decreasing. Since 2010, the drought and flood events show characteristics of extreme enhancement, sudden increases, and successive droughts and floods.

An investigation into the spatial–temporal distribution characteristics of ancient settlements and their relationship with the environment in the Sichuan Basin can enhance our understanding of the evolution of the regional human–land relationship. Utilizing kernel density analysis by GIS, this paper obtained the spatial distribution characteristics of 1100 settlements in the Neolithic, Shang–Zhou, and Qin to Southern Dynasties periods. Subsequently, a GIS spatial analysis was performed to examine the distribution of these settlements in relation to the natural environment, focusing on four aspects: elevation, slope, aspect, and water buffer zone. The results demonstrate that: (1) The distribution of settlements from the Neolithic to the Southern Dynasties has expanded from the Chengdu Plain in the west and the Xiajiang Area in the east to the hilly areas in the center. (2) The settlements in the Neolithic and Shang–Zhou periods are predominantly located at elevations between 300–600 m, slopes between 0–3°, aspects between 135–225°, distances to rivers between 0–1000 m, and soil choice on Luvisols, Cambisols, Regosols, and Anthrosols. The influence of aspect on settlements during the Qin–Southern Dynasties period was notably reduced. The settlements mainly grow in the Chengdu Plain and the smaller plains along the river from the Neolithic to the Southern Dynasties in the Sichuan Basin. (3) The emergence and advancement of primitive agriculture, the construction of early water conservancy facilities, commercial and trade exchanges, and the establishment of regimes led to a shift from a double core to a more dispersed distribution in the Sichuan Basin from the Neolithic to the Southern Dynasties periods. The evolution of settlements reflects the adaption and competition of the residents to the natural environment in the Sichuan Basin. Furthermore, it provides insights into the complex social development in the region, ranging from the formation of early states to the establishment of the Qin and Han Empires.

A statistical analysis is conducted on the hourly precipitation at 105 national meteorological stations in the Xinjiang region of China from 2011 to 2020. The purpose of this analysis is to determine the total quantity of precipitation during the warm and cold seasons, as well as the precipitation frequency at each station. The results of the analysis indicate that there is a more pronounced inter-annual variation in precipitation during the warm and cold seasons in Xinjiang, where the total amount of precipitation during the warm season is significantly higher than that during the cold season, with the warm season experiencing at least twice as much precipitation. In terms of the inter-annual incremental amount of precipitation, both the warm and cold seasons exhibit a trend of increasing and then decreasing over the years. However, the curvature change is more prominent in the cold season compared to the warm season, suggesting that the inter-annual variation in precipitation during the warm season remains relatively stable. The spatial distribution characteristics of the total precipitation in Xinjiang indicate that warm-season precipitation is more scattered, while cold-season precipitation is mainly concentrated in the northern region of the territory. This pattern holds true at low, medium, medium–high, and high altitudes. The cumulative precipitation during the warm season is always higher than that in the cold season, and this difference becomes more prominent with increasing altitude. This indicates that warm-season precipitation in Xinjiang is closely related to its complex topographic structure, particularly the convective weather generated by topographic clouds. On the other hand, precipitation in the cold season is mainly concentrated in the low- and medium-altitude stations, and there is not much correlation between precipitation and altitude. Precipitation is mainly affected by the mesoscale and the direct influence of large-scale weather systems. Analysis of precipitation in extreme moments reveals that during the warm season, extreme precipitation events occur mainly from the evening to early morning (19:00–03:00 the next day), accounting for 75.24% of the 105 stations. In contrast, during the cold season, extreme precipitation events occur between 03:00 and 18:00, corresponding to 74.29% of the stations. The relationship between precipitation and altitude differs in the warm and cold seasons. In the warm season, there is a linear relationship between precipitation and altitude, with a slope of 0.72 and a correlation coefficient of 0.52, indicating that precipitation increases with increasing altitude. However, in the cold season, the linear relationship between precipitation and altitude is very inconspicuous, with a slope of −0.05 and a correlation coefficient of −0.05, suggesting that there is no significant relationship between precipitation and altitude during this season. These findings provide valuable insights into the changing patterns of precipitation gradients at different altitudes and seasons in Xinjiang. This information can be used for the site selection of smokestack operations in high-altitude areas and for ground and air weather modification operations in low-altitude areas. Additionally, these data contribute to the understanding of precipitation patterns in Xinjiang, further improving the effectiveness of weather modification efforts and increasing the utilization of airborne water resources.

The Selenga River provides about half of the water and chemical runoff into Lake Baikal and plays an important role in the sustainability of the ecosystem of this large natural freshwater lake. Phthalate esters (PAEs) are organic compounds that can disrupt reproductive and endocrine systems. This study focused on investigating the distribution of six priority phthalates in the Selenga River and its delta utilizing SPE-GC/MS. The study found that the highest levels of Σ6PAE were observed during the high-water years, 2021 and 2023, and were evenly distributed along the river from the sampling sites upstream of Ulan-Ude to the delta channels. In contrast, the mean annual Σ6PAE content was relatively low in the low water period of 2022. Dibutyl phthalate (DBP) and di-(2-ethylhexyl) phthalate (DEHP) are the two dominant phthalates found in the surface waters of the Selenga River and delta channels. In 2021, the average total concentration of six phthalates (Σ6PAE) ranged from 8.84 to 25.19 µg/L, while in 2022 it ranged from 0.45 to 4.01 µg/L, and in 2023 it ranged from 5.40 to 21.08 µg/L. The maximum level for the sum of phthalates was 61.64 µg/L in 2021, 13.57 µg/L in 2022, and 30.19 µg/L in 2023. The wastewater treatment facilities in Ulan-Ude were identified as a stable local source of phthalates. In some cases, PAE concentrations exceeded maximum allowable concentrations, particularly for DEHP. This could have adverse effects on aquatic organisms. [ABSTRACT FROM AUTHOR]

Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations and oceanographic factors within the northern Indian Ocean from March 2020 to February 2023. Frequency analysis and the empirical cumulative distribution function (ECDF) were used to calculate the optimum ranges of two oceanographic factors for fishing operations. The results revealed a substantial influence of the northeast and southwest monsoons significantly impacting fishing operations in the northern Indian Ocean, with extensive and active operations during the period from October to March and a notable reduction from April to September. Spatially, fishing vessels were mainly concentrated between 20° N and 6° S, extending from west of 90° E to the eastern coast of Africa. Observable seasonal variations in the distribution of fishing vessels were observed in the central and southeastern Arabian Sea, along with its adjacent high sea of the Indian Ocean. Concerning the marine environment, it was observed that during the northeast monsoon, the suitable SST contributed to high CPUEs in fishing operation areas. Fishing vessels were widely distributed in the areas with both mid-range and low-range Chl-a concentrations, with a small part distributed in high-concentration areas. Moreover, the monthly numbers of fishing vessels showed seasonal fluctuations between March 2020 and February 2023, displaying a periodic pattern with an overall increasing trend. The total number of fishing vessels decreased due to the impact of the COVID-19 pandemic in 2020, but this was followed by a gradual recovery in the subsequent two years. For fishing operations in the northern Indian Ocean, the optimum ranges for SST and Chl-a concentration were 27.96 to 29.47 °C and 0.03 to 1.81 mg/m3, respectively. The preliminary findings of this study revealed the spatial–temporal distribution characteristics of fishing vessels in the northern Indian Ocean and the suitable ranges of SST and Chl-a concentration for fishing operations. These results can serve as theoretical references for the production and resource management of off-shore fishing operations in the northern Indian Ocean. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is one of the most serious atmospheric heavy metal pollutants in China. PM2.5, PM10, and total suspended particle (TSP) are all important media for population Cd exposure. However, no studies so far have systematically explored the spatial and temporal distribution of atmospheric Cd bound to all these media in China, and the specific industrial sectors that contribute to the airborne Cd level are still unclear at present. In this study, we constructed the spatial and temporal distribution of PM (PM2.5, PM10, and TSP) binding Cd concentrations in China. Quantitative source apportionment of atmospheric Cd was carried out by analyzing the association of 23 industrial or energy-consuming sectors with Cd concentrations. Our results showed PM2.5, PM10, and TSP binding Cd concentrations decreased by 5.8%, 5.9%, and 6.1% per year at the national level, respectively. High PM-Cd concentrations were concentrated and distributed mainly in central and northwestern China. In addition, the medians of atmospheric PM2.5, PM10, and TSP binding Cd concentrations at the national level were 0.0026 μg/m3, 0.0036 μg/m3, and 0.0042 μg/m3, respectively. The main sources of PM-Cd include nonferrous metal smelting (Zn, Pb, Al) (47%), glass production (13%), pesticide production (12%), cement production (10%), and coal consumption (9%). This study analyzes comprehensively the atmospheric PM-bound Cd pollution, identifies the major industrial sectors that affect atmospheric Cd concentrations at the macroscale for the first time, and provides a basis for further reduction in the atmospheric Cd pollution. [ABSTRACT FROM AUTHOR]

The recognition on the trend of wind energy stability is still extremely rare, although it is closely related to acquisition efficiency, grid connection, equipment lifetime, and costs of wind energy utilization. Using the 40-year (1979–2018) ERA-Interim data from the European Center for Medium-Range Weather Forecasts, this study presented the spatial-temporal distribution and climatic trend of the stability of global offshore wind energy as well as the abrupt phenomenon of wind energy stability in key regions over the past 40 years with the climatic analysis method and Mann-Kendall (M-K) test. The results show the following 5 points. (1) According to the coefficient of variation (Cv) of the wind power density, there are six permanent stable zones of global offshore wind energy: the southeast and northeast trade wind zones in the Indian, Pacific and Atlantic oceans, the Southern Hemisphere westerly, and a semi-permanent stable zone (North Indian Ocean). (2) There are six low-value zones for both seasonal variability index (Sv) and monthly variability index (Mv) globally, with a similar spatial distribution as that of the six permanent stable zones. Mv and Sv in the Arabian Sea are the highest in the world. (3) After Cv, Mv and Sv are comprehensively considered, the six permanent stable zones have an obvious advantage in the stability of wind energy over other sea areas, with Cv below 0.8, Mv within 1.0, and Sv within 0.7 all the year round. (4) The global stability of offshore wind energy shows a positive climatic trend for the past four decades. Cv, Mv and Sv have not changed significantly or decreased in most of the global ocean during 1979 to 2018. That is, wind energy is flat or more stable, while the monthly and seasonal variabilities tend to shrink/smooth, which is beneficial for wind energy utilization. (5) Cv in the low-latitude Pacific and Mv and Sv in both the North Indian Ocean and the low-latitude Pacific have an obvious abrupt phenomenon at the end of the 20th century. [ABSTRACT FROM AUTHOR]

The intensive use of pesticides in the North China Plain (NCP) has resulted in widespread contamination of pesticides in the local atmosphere, posing risks to air quality and human health. However, the occurrence and distribution of atmospheric pesticides in the NCP as well as their risk assessment have not been well investigated. In this study, 300 monthly samples were collected using passive air samplers with polyurethane foam at ten rural sites with different crop systems in Quzhou county, the NCP, from June 2021 to May 2022. The pesticides were quantified using mass-spectrometric techniques. Our results revealed that chlorpyrifos, carbendazim, and atrazine were the most frequently found pesticides in the air samples, with detection frequencies of ≥ 87 % across the samples. The average concentrations of atmospheric pesticides during spring (7.47 pg m−3) and summer (16.05 pg m−3) were significantly higher than those during autumn (2.04 pg m−3) and winter (1.71 pg m−3), attributable to the intensified application of pesticides during the warmer seasons. Additionally, cash crop sites exhibited higher concentrations (10.26 pg m−3) of atmospheric pesticides compared to grain crop (5.59 pg m−3) and greenhouse sites (3.81 pg m−3), primarily due to more frequent pesticides spraying events in cash crop fields. These findings indicate a distinct spatial–temporal distribution pattern of atmospheric pesticides influenced by both seasons and crop systems. Furthermore, the model-based inhalation risk assessment indicates that inhalation exposure to atmospheric pesticides is unlikely to pose a significant public concern.

After Buddhism spread to the Zhejiang, it underwent sinicization, giving rise to Chinese Buddhist architecture and forming a secularized character. The spatial-temporal distribution of historical Buddhist architecture in Zhejiang is strongly representative of Buddhist architecture. From the perspective of religious cultural geography, this study takes 11 prefecture-level cities of Zhejiang as the basic research units, and employs the spatial-analysis method of ArcGIS to analyze the spatial-temporal evolution characteristics of representative historical Buddhist architectural samples, and to explore the factors affecting their distribution. The research results indicate that the spatial distribution of representative historical Buddhist architectural samples in the Zhejiang is extensive, with a distinct single-core clustering characteristic. The mean-center movement of the representative historical Buddhist architectural samples in Zhejiang during different historical periods manifests in four distinct directional phases, overall moving from north to south. Natural, transportation, political, technological, economic, and religious cultural transmission factors collectively influence the spatial-temporal distribution of Buddhist architecture in Zhejiang. Especially the secularization of Buddhism and the syncretism of Confucianism, Daoism, and Buddhism have been the primary drivers in the spatial-temporal distribution evolution of Buddhist architecture. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of temperature trends is vital for assessing the impacts of climate change on a regional scale. In this context, the present study focuses on Madhya Pradesh state in Central Indian region to explore the spatial-temporal distribution patterns of temperature changes from 1951 to 2021. Gridded temperature data obtained from the Indian Meteorological Department (IMD) in 1° × 1° across the state are utilised to analyse long-term trends and variations in temperature. The Mann-Kendall (MK) test and Sen’s slope (SS) estimator were used to detect the trends, and Pettitt’s test was utilised for change point detection. The analysis reveals significant warming trends in Madhya Pradesh during the study period during specific time frames. The temperature variables, such as the annual mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin), consistently increase, with the most pronounced warming observed during winter. The trend analysis reveals that the rate of warming has increased in the past few years, particularly since the 1990s. However, Pettitt’s test points out significant changes in the temperature, with Tmean rising from 25.46 °C in 1951–2004 to 25.78 °C in 2005–2021 (+0.33 °C), Tmax shifting from 45.77 °C in 1951–2010 to 46.24 °C in 2011–2021 (+0.47°C), and Tmin increasing from 2.65 °C in 1951–1999 to 3.19 °C in 2000–2021 (+0.46 °C). These results, along with spatial-temporal distribution maps, shed important light on the alterations and variations in monthly Tmean, Tmax, and Tmin across the area, underlining the dynamic character of climate change and highlighting the demand for methods for adaptation and mitigation. [ABSTRACT FROM AUTHOR]

The water quality status, spatial and temporal change processes, and water environment improvement process of urban rivers are valuable lessons to be learned under the sustainable development strategy. This study aims to reveal the water environment improvement process of intensively developed urban rivers, elucidate the spatial and temporal distribution characteristics of major pollutants, and provide recommendations for their water environment management. Water quality data from eight monitoring sites (2007–2020) in the Longgang River basin in Shenzhen, China, and comprehensive pollution index method (CPI), modified comprehensive pollution index method (M-CPI), and Pearson correlation analysis method were used for comprehensive analysis. The study shows that TN, TP, NH3-N, and COD have the greatest influence on the water quality of Longgang River, with the average pollution contribution of 53.39%, 14.49%, 11.66%, and 4.92%, in order. In 2015–2020, the water quality of the main stream of the Longgang River in the wet season was worse than that in the dry season, while the water quality of the tributaries Dingshan River and the Huangsha River in the dry season was worse than the wet season. The spatial distribution characteristics based on M-CPI indicate that the water quality of the lower reaches of Longgang River, the tributaries Dingshan River and Huangsha River, is relatively poor. In addition, the water environment improvement process of Longgang River can be divided into 3 stages: engineering stage (2007–2013, rating changed from heavily polluted to basically qualified), bottleneck stage (2013–2017, rating fluctuated slightly above and below basically qualified), and ecological restoration stage (2017–2020, rating reached qualified in 2019). [ABSTRACT FROM AUTHOR]

Noctiluca scintillans is one of the most common harmful algal species and widely known due to its bioluminescence. In this study, the spatial distribution, seasonal variations, and long‐term trends of N. scintillans blooms in China and the related drivers were analyzed and discussed. From 1933 to 2020, a total of 265 events of N. scintillans blooms were recorded in Chinese coastal waters, with a total duration of 1052 days. The first N. scintillans bloom occurred in Zhejiang in 1933, and only three events were recorded before 1980. From 1981 to 2020, N. scintillans caused harmful algal blooms (HABs) almost every year, both the average duration and the proportion of multiphase HABs showed an increasing trend. 1986–1992, 2002–2004, and 2009–2016 were the three peak periods with a frequency of no less than five events of N. scintillans blooms per year. In terms of spatial distribution, N. scintillans blooms spread from the Southeast China Sea to the Bohai Sea after 2000, Guangdong, Fujian, and Hebei were the three provinces with the highest numbers of recorded events of N. scintillans blooms. Moreover, 86.8% of the events of N. scintillans blooms occurred in spring (March, April, and May) and summer (June, July, and August). Among environmental factors, the dissolved inorganic phosphate, dissolved silicate and chemical oxygen demand were significantly correlated with the cell density of N. scintillans during N. scintillans blooms, and most of N. scintillans blooms were recorded in the temperature range of 18.0–25.0°C. Precipitation, hydrodynamics, water temperature, and food availability might be the main factors affecting the spatial–temporal distribution of N. scintillans blooms along the Chinese coast. [ABSTRACT FROM AUTHOR]

For the problems of unreasonable layout location and low charging utilization rate of electric vehicle (EV) charging stations, this paper proposed a spatial-temporal demand model (STDM) for location optimization of charging stations under spatial-temporal demand. By mining the spatial-temporal distribution characteristics of EV travel data and combining the travel and charging behaviors of EVs, a charging demand prediction model is to obtain the spatial-temporal demand distribution in the region. The method based on spatial-temporal statistics obtained the demand hotspot areas, and the charging coverage rate as the model evaluation parameter considered the service coverage of charging stations. A comprehensive model included the perspectives of users, operators and society with EV distance cost to the station, charging station construction and operation cost and carbon emission cost. Finally, simulation results based on actual data show the feasibility and validity of the model. The results show that the model has set up 12charging stations in the region to reduce the comprehensive cost, while determining the layout location and the number of charging piles. The optimization model results effectively reduce the EV arrival distance and improve the arrival coverage compared with other methods. [ABSTRACT FROM AUTHOR]

【Objective】The spatial-temporal variation characteristics of soil pH and its driving factors were clarified to provide a basis for the improvement of soil acidification in southwest cigar area.【Method】Based on soil pH data of 26 sample points of the second general soil survey in Sichuan Province in 1984, 391 sample points of soil testing and fertilizer recommendation survey in Sichuan Province in 2009, and 164 sample points of cultivated land quality survey in Sichuan Province in 2019, Multi-statistics and Geostatistics were used to analyze the spatial-temporal variation characteristics of soil pH, and Random Forest model was used to explore the main driving factors of soil pH change.【Result】The mean values of pH in Shifang City in 1984, 2009 and 2019 were 6.40, 6.24 and 5.97, respectively, and the average annual value decreased by 0.01 from 1984 to 2009 and by 0.02 from 2009 to 2019. From 1984 to 2019, except for Jiandi Town and Yinghua Town, where the average soil pH value showed an upward trend, the rest of the towns were on the decline, with the largest decrease of 30.62% in Hefeng Town and the smallest decrease of 0.30% in Shigu Town. The overall soil pH in 1984 was dominated by weakly acidic and neutral properties, with alkaline soils accounting for 2.59% of the total area planted with tobacco, and the spatial distribution was characterized by higher soil pH in three areas: Luoshui Town, Hefeng Town and Majing Town. In 2009, only weakly acidic and neutral soils existed in the study area, and soil pH was spatially high in the centre and low in the north and south. In 2019, the area of weakly acidic and neutral soils accounted for 95.25%, and the area of acidic soils (pH < 5.5) accounted for 4.75%, which were mainly distributed in the towns of Majing, Mazu, Hefeng, Nanquan and Shigu. And soil pH in the south was spatially lower than that in the north. Soils planted with tobacco over the past 35 years have generally shown changes in acidification, with about 53.51% of the soil was acidified (ΔpH < -0.3), mainly distributed in the towns of Majing, Hefeng and Mazu, and about 11.63% of the soil was alkaline (ΔpH > 0.3), mainly in the towns of Yinghua and Jiandi; The pH of 44.98% tobacco growing soils ranged from -1.0 to -0.3, 34.86% ranged from -0.3 to 0.3, and tobacco growing soils with ΔpH ≤ -1.0 accounted for 8.54%. The random forest results showed that mean annual precipitation and soil organic matter were the main factors causing soil acidification.【Conclusion】Over the past 35 years, the acidification of tobacco growing soils in Shifang City was aggravated. Some measures should be taken to adjust the situation in production, such as creating new special fertilizer and applying soil conditioner.

To quantify the consumption of water resources for winter wheat, the spatial-temporal distribution and variation of water footprint for winter wheat were quantitatively analyzed based on the water footprint theory and method at the county scale in the Huang-Huai-Hai farming region from 1985 to 2015, and the distribution of cold and hot spot of water footprint were analyzed. The results showed that the total water footprint of winter wheat was 1 168.54X108 m³, and its spatial distribution was high in the south and low in the north. The blue water footprint of winter wheat was high in the north and low in the south, while the green water footprint and gray water footprint were high in the south and low in the north. From 1985 to 2015, the total water footprint for winter wheat increased by 54.8%. The blue and green water footprint changed little, while the grey water increased by 29.1%. The spatial distribution of blue, green and grey water footprints decreased in the north and increased in the south. The gravity center of the total water footprint for winter wheat moved to the southwest, while the overall change of which was small. In recent 30 years, the water footprint for winter wheat showed a spatial agglomeration trend in the global and local areas. The hot spot area expanded in the 2.5 sub-zone, and the cold spot area expanded in the 2.2 sub-zone. These results provided scientific basis for optimizing winter wheat distribution and efficient utilization and management of agricultural water resources in Huang-Huai-Hai farming region. [ABSTRACT FROM AUTHOR]

In order to ascertain the spatial and temporal changes in the air quality in Temuco City, Chile, we created and installed a network of inexpensive sensors to detect PM2.5 particulate matter. The 21 measurement points deployed were based on a low-cost Sensiron SPS30 sensor, complemented with temperature and humidity sensors, an Esp32 microcontroller card with LoRa and WiFi wireless communication interface, and a solar charging unit. The units were calibrated using an airtight combustion chamber with a Grimm 11-E as a reference unit. The calibration procedure fits the parameters of a calibration model to map the raw low-cost particle-material measurements into reliable calibrated values. The measurements showed that the concentrations of fine particulate material recorded in Temuco present a high temporal and spatial variability. In critical contamination episodes, pollution reaches values as high as 354 µg/m 3 , and at the same time, it reaches 50 µg/m 3 in other parts of the city. The contamination episodes show a similar trend around the city, and the peaks are in the time interval from 07:00 PM to 1:00 AM. In the winter, this time of day coincides with when families are usually home and there are low temperatures outside. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the distribution of microplastics (MPs) within the Shiwuli River in Hefei, a Chinese inland city. Water and sediment samples were collected during flood season (from May to September) and non-flood season (from October to April) at 10 representative points along the truck stream. The electron microscope, the laser direct infrared chemical imaging system (LDIR), and the scanning electron microscope (SEM) were used to observe and quantify the colour and shape of the MPs, to identify the number, size, and polymer composition of the MPs, and to observe the microstructures of typical MP particles, respectively. The polymer risk index (RI) model and the pollution load index (PLI) model were used to assess the polymer-related risks and the overall extent of MP pollution in the river, respectively. Analysis of MP abundance for different sampling points showed that the water of Shiwuli River had an average abundance of MPs of 8.4 ± 2.5 particles/L during the flood season and 5.8 ± 1.7 particles/L during the non-flood season; the sediment had an average abundance of MPs of 78.9 ± 8.3 particles/kg during the flood season and 63.9 ± 7.1 particles/kg during the non-flood season. The abundance of MPs of different points was investigated. Result show that the more abundances of MPs were found at confluences with tributaries (S4, S5, and S6), where they are also close to the residential and industrial development, while lower values were found in agricultural areas (S8) and wetland ecological regions (S9 and S10). In water, the maximum appeared at S5 with 21.7 ± 4.6 particles/L during the flood season and 15.9 ± 4.2 particles/L during the non-flood season, respectively; the minimum appeared at S9 with 1.8 ± 1.0 particles/L during the flood season and 2.2 ± 0.4 particles/L during the non-flood season, respectively. In sediment, the maximum appeared at S5 with 174.1 ± 10.1 particles/kg during the flood season and 143.6 ± 10.4 particles/kg during the non-flood season, respectively; the minimum appeared at S8 with 10.3 ± 2.8 particles/kg during the flood season and at S9 with 12.1 ± 3.2 particles/kg during the non-flood season, respectively. MP characteristics were also studied. Results show that the MPs mainly exhibited a fibroid morphology (27.90–34%), and red-coloured particles (19.10%) within the smaller size less than 500 μm (38.60%) were more prevalent. Additionally, the result of LDIR scanning shows that a total of eleven types of MP polymers were found in the river water and sediment, including acrylates (ACR), chlorinated polyethylene (CPE), ethylene vinyl acetate (EVA), polyethylene (PE), polyethylene terephthalate (PET), polypropylene (PP), polystyrene (PS), polyurethane (PU), polyvinylchloride (PVC), polyamide (PA), and silicon. The most common particle was PE (19.3–21.6%). Furthermore, the environmental risk assessment demonstrated that the PS polymer posed a Level-III risk in the water samples and a Level-II risk in the sediment samples from the Shiwuli River. The remaining polymer types exhibited Level-I risk. The PLIzone value for water was 2.24 during the flood season, indicating heavy pollution, and 1.66 during the non-flood season, indicating moderate pollution. Similarly, the PLIzone value for sediments was 2.34 during the flood season and 1.91 during the non-flood season, both suggesting a heavy pollution. These findings highlight the potential risk posed by MP pollution in the Shiwuli River to the quality of drinking water sources in Chaohu Lake in Hefei. They provide valuable insights into management, pollution control, and integrated management strategies pertaining to MPs in urban inland rivers in Hefei. [ABSTRACT FROM AUTHOR]

The planning of urban transportation infrastructure and land-related policies has a significant impact on the living conditions of urban residents and socio-economic development, particularly in emerging economies. As urbanization continues to advance, Metropolitan Areas (MAs) have become crucial for achieving industrial coordination, functional complementarity between cities, and integrated regional development. Applying Social Network Analysis (SNA), the gravity model, and Quadratic Assignment Procedure (QAP) analysis, this study investigated the spatial-temporal distribution patterns of High-Speed Railway (HSR) networks and economic networks in MAs in China and the dynamic coupling relationship between these two networks. The findings revealed that, although core cities in the Yangtze River Delta MA in China exert varying degrees of radiation and driving effects on the economic development of surrounding cities, the overall development remains immature with a noticeable disequilibrium phenomenon. The coupling relationship between the HSR networks and the economic networks also differs significantly among different MAs. It is expected that the findings and suggestions of this study will contribute to the improvement of urban planning and governance and facilitate coordinated development between urban transportation infrastructure and the economy in emerging economies. [ABSTRACT FROM AUTHOR]

Online monitoring of the spatial-temporal distribution of harmful gases has always been a complex problem in the environmental field. This paper proposes a novel mathematical method for online monitoring of the spatial-temporal distribution of reactants by machine learning, which can help to remove harmful gases efficiently. In this model, we take the advanced oxidation of NO as an example to evaluate the model performance. The spatial features were extracted by CNN, and GRU extracted the temporal features in the sequence of spatial features. Five physical field variables (mass fraction of ozone, velocity, temperature, the wind direction of the horizontal plane, and the wind direction of the vertical plane) were put into the network to predict NO's spatial-temporal mass fraction distribution. Furthermore, the impact of sampling time interval on monitoring performance was also evaluated. The results show that both the instantaneous and continuous CFD (Computational Fluid Mechanics) and predicted values show high consistency, which indicates that the model can online monitor the spatial-temporal distribution of reactants successfully. In addition, the most suitable sampling time interval is 0.5 s, with low training error (RMSE=0.06 and nRMSE=0.3) and high relation coefficient (r=0.99), which shows the model has great perceived and predicted performance under this condition.

ObjectiveThis study attempts to analyze the spatial clustering and spatial-temporal distribution characteristics of hepatitis E (HE) at the county (city and district) level in Jiangsu province to provide a scientific basis for the prevention and control of HE.MethodThe information on HE cases reported in the Chinese Center for Disease Control and Prevention Information System from 2005 to 2020 was collected for spatial autocorrelation analysis and spatial-temporal clustering analysis.ResultFrom 2005 to 2020, 48,456 HE cases were reported in Jiangsu province, with an average annual incidence rate of 3.87/100,000. Male cases outnumbered female cases (2.46:1), and the incidence was highest in the 30–70 years of age group (80.50%). Farmers accounted for more than half of all cases (59.86%), and in terms of the average annual incidence, the top three cities were all in Zhenjiang city. Spatial autocorrelation analysis showed that Global Moran's I of HE incidence varied from 0.232 to 0.513 for the years. From 2005 to 2020, 31 counties (cities and districts) had high and statistically significant HE incidence, and two clustering areas were detected by spatial-temporal scanning.ConclusionHE incidence in Jiangsu province from 2005 to 2020 was stable, with age and gender differences, regional clustering, and spatial-temporal clustering. Further investigation of HE clustering areas is necessary to formulate corresponding targeted prevention and control measures.

As the largest contributor to global carbon emissions (CEs), construction industry (CI) is regarded as one of the most significant sources in China. Previous studies on carbon emission (CE) of CI, however, are often limited to the quantitative level and provincial or local administrative unit scales, lacking relevant studies at the spatial raster resolution scale, due to data limits. Here, using the energy consumption, social economic data, and a series of remote sensing data from EU EDGAR, this study explored the spatial–temporal distribution and changing characteristics of CEs from CI in typical years of 2007, 2010, and 2012. This study found, from 2007 to 2010, then 2012, in addition to subtle differences, that the direct, indirect, and total CEs of CI all showed an increasing trend overall. In all provincial units except Tianjin and Guangdong, indirect CEs took up more than 50% of the total CEs, which can clearly indicate the "dominant low carbon, recessive high carbon" characteristics of CI. The direct, indirect, and total CEs of the CI in 2007, 2010, and 2012 all showed a positive spatial clustering. Specifically, hot spots were mainly distributed in Beijing-Tianjin-Hebei and Yangtze River Delta, and cold spots were mainly focused in the west and northeast of China, presenting a similar distribution pattern with population-economy characteristics. These findings can provide references for the policy formulation of regional differentiated emission reduction. [ABSTRACT FROM AUTHOR]