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The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann–Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990–2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region. [ABSTRACT FROM AUTHOR]

Background: Urbanization greatly affects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases. Schistosomiasis, a common parasitic disease transmitted by the snail Oncomelania hupensis, is mainly found in areas with population aggregations along rivers and lakes where snails live. Previous studies have suggested that factors related to urbanization may influence the infection risk of schistosomiasis, but this association remains unclear. This study aimed to analyse the effect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China. Methods: County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected. The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the National Polar-Orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The geographically and temporally weighted regression model (GTWR) was used to quantify the influence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled. The regression coefficient of urbanization was tested for significance (α = 0.05), and the influence of urbanization on schistosomiasis infection risk was analysed over time and across space based on significant regression coefficients. Variables studied included climate, soil, vegetation, hydrology and topography. Results: The mean regression coefficient for urbanization (0.167) is second only to the leached soil area (0.300), which shows that the urbanization is the most important influence factors for schistosomiasis infection risk besides leached soil area. The other important variables are distance to the nearest water source (0.165), mean minimum temperature (0.130), broadleaf forest area (0.105), amount of precipitation (0.073), surface temperature (0.066), soil bulk density (0.037) and grassland area (0.031). The influence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year. During the study period, the significant coefficient of urbanization level increased from − 0.205 to − 0.131. Conclusions: The influence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous. The urbanization does reduce the risk of schistosomiasis infection to some extend, but the strength of this influence decreases with increasing urbanization. Additionally, the effect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors. This study provides scientific basis for understanding the influence of urbanization on schistosomiasis, and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk. [ABSTRACT FROM AUTHOR]

Water pollution, particularly non-point source pollution, poses a significant environmental challenge in river basins around the world. This complex and dynamic process is influenced by both human activities and natural processes. In this study, a quantitative analysis of ammonia-N and total phosphorus (TP) levels in the North Stream of the Jiulong River basin, China from 2010 to 2018 was conducted using the Soil & Water Assessment Tool (SWAT) model. The model was able to facilitate the simulation of spatio-temporal dynamics of concerned pollutants. Additionally, the GeoSOS-FLUS model was integrated with SWAT to predict land use patterns in 2040 and assess their impact on pollutant dynamics. The results demonstrated that the SWAT model effectively simulated the spatial and temporal dynamics of concerned pollutants in the study area, with satisfactory R2 and NS values for river discharges and pollutant loads. Notably, 2016 exhibited significant pollution levels, particularly in March. The study revealed distinct sources of ammonia-N and TP, originating from aquatic animal breeding areas and industrial wastewater discharge, respectively. Moreover, land use patterns influenced the spatial distribution of pollutants. These findings serve as a crucial data foundation for future endeavors in controlling and mitigating non-point source pollution in the Jiulong River basin. [ABSTRACT FROM AUTHOR]

As the largest freshwater lake in China, Poyang Lake is an internationally important wetland and the largest migratory bird habitat in Asia. Many sub-lakes distributed in the lake basin are seasonal lakes, which have a significant impact on hydro-ecological processes and are susceptible to various changes. In this study, using multi-source remote sensing data, a continuous time-series construction method of water coverage suitable in Poyang Lake was developed. That method combined the downscaling of the MNDWI (modified normalized difference water index) with the ISODATA (iterative self-organizing data analysis technique algorithm), and its accuracy can be up to 97% in the months when Landsat 8 is available or 87% when it is unavailable. Based on that method, the increasing variation in water coverage was observed in the sub-lakes of Poyang Lake during 2013–2020 to be within a range of 200–690 km2 normally. The center of the sub-lakes always remained inundated (>80% inundation frequency), while the surrounding areas were probably kept dry for seven months (except for June to September). The dominant influencing factors of water coverage variations were different in different hydrological periods (wet season and dry–wet season: discharge; dry season: temperature and wind speed; wet–dry season: temperature and precipitation). In addition, "returning farmland to lakes" affected the increase in the water area in the sub-lakes. This study is helpful for the management of water resources and the protection of migratory birds in the Poyang Lake region. [ABSTRACT FROM AUTHOR]

Shallow groundwater in coastal aquifers is a highly dynamic and complex system with a high risk of seawater intrusion. Analyzing the spatio-temporal dynamic patterns of groundwater can help to manage the groundwater resource and prevent it from degradation. Based on the groundwater level (GWL) and electrical conductivity (EC) monitoring data of 18 observation wells in the Yellow River Delta (YRD) from 2004 to 2010, this research analyses the groundwater dynamics using a robust seasonal trend decomposition technique (STL) and spatial interpolation method to detect the groundwater spatio-temporal dynamic patterns of groundwater level and salinity. Combined with hydro-climatic data, the Pearson correlation method and the Mann-Kendall (MK) trend analysis were used to further reveal the impacts that induce their trends and seasonal variations. Our analyses show that the risk of seawater intrusion into local shallow aquifers in this region is high, with the mean groundwater level over 42% of the region lower than the local sea level, and the mean groundwater EC over 96% of the region met the standards for seawater intrusion. In addition, the trends of groundwater level generally declined by 0.01~0.45 m/a and salinity increased by 1.153~25.608 μs/cm.a, which are consistent with the trend of precipitation decline. The seasonal dynamics of groundwater level and salinity are highly correlated with the seasonal components of rainfall and evaporation. It can be concluded that the extent of seawater intrusion will increase in the future with sea level rise. The approaches used in this study proved to be effective and can certainly serve as an example for the analysis of the spatio-temporal dynamics of groundwater in other coastal regions. [ABSTRACT FROM AUTHOR]

The evolution of the spatiotemporal relationship between urban economic growth and health resources within the Yangtze River Delta urban agglomeration provides an important context for understanding the regional development dynamics in China. Previous studies focused on equity in health-resource allocation and service efficiency, often overlooking the allometric growth relationships between health resources and economic variables. This study employs an allometric growth model to elucidate the changing interactions between the number of medical beds, doctors, and urban economic indicators in the Yangtze River Delta region from 2009 to 2022. Employing Zipf's law and allometric growth modeling, this study analyzed growth trends and revealed significant differences in resource allocation and size changes over time. The main findings suggest that, although resource centralization is a general trend, differences persist, especially in less economically developed regions. This study innovatively introduces an allometric growth model that offers a new perspective on understanding the mechanisms of regional health-resource growth and underscores the significant influence of economic factors on health-resource allocation. This study significantly contributes to the sustainability of urban health systems and provides theoretical support for policy formulations aimed at optimizing the allocation of health resources and strengthening regional economic strategies in the Yangtze River Delta region., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Jing et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model's Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study expands the original two-dimensional carbon footprint model into a three-dimensional model form. Introduce two indicators of carbon footprint depth (CF depth ) and size (CF size ) to form a three-dimensional carbon footprint model (CF 3D ), which is used to respectively represent the occupation and consumption of natural capital reserves by human activities' carbon emissions. Based on the 3D carbon footprint model, this paper calculated the CF size , CF depth , and CF 3D for four different urban agglomerations of China (BTH, YRD, PRD, and CY) spanning from 2000 to 2017. Building on this, the study analyzed the spatial-temporal and dynamic characteristics of the multivariate collaboration between CF size , CF depth , and GDP using a multivariate collaborative relationship model. The research findings reveal that (1) from 2000 to 2017, the utilization of natural capital stock in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Chengyu (CY) urban agglomerations were in an unsustainable development state, with their CF depth exceeding 1. Among these regions, the degree of natural capital consumption was PRD > BTH > YRD > CY. (2) There manifests an obvious regional complementary characteristic of CF size and CF depth . Regions coupled with abundant land resources (such as Chengde and Hangzhou) tend to have high CF size and low CF depth , whereas area with fewer land resources (such as Tianjin and Shanghai) exhibits the opposite pattern. (3) In four urban agglomerations, the relationship of temporal multivariate collaboration among CF size , CF depth , and GDP exhibits a declining trend from 2000 to 2017, with an average value ranging from 0.4 to 0.6. The change in their multivariate spatial collaboration was not pronounced throughout the course of the study., Competing Interests: Declarations. Ethical responsibilities of authors: All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors. Competing interests: The authors declare no competing interests., (© 2025. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Yunnan Province, located in the southwestern part of China and neighboring endemic dengue regions of Southeast Asia, has experienced annual autochthonous outbreaks of dengue fever from 2013 to 2023. This study examines the epidemiological and spatiotemporal clustering characteristics of dengue within the province., Methods: Descriptive epidemiological methods were used to analyse outbreak characteristics. Excel 2019 and ArcGIS 10.3 software were used to establish a case database and for mapping. Spatial autocorrelation and spatio-temporal clustering analysis were employed to study the features of spatial clustering., Results: From 2013 to 2023, 30,666 dengue cases were reported in Yunnan Province, of which 22,806 (74.37%) were indigenous and 7,860 (25.63%) were imported. Imported cases from Myanmar, Laos, and Vietnam were reported each year, with indigenous outbreaks occurring from June to December. The majority of cases occurred among young adults, mainly farmers, service workers, homemakers, and the unemployed. There was a significant temporal and spatial clustering of dengue incidence, with intense local clustering in the southwestern border areas of the province from July to November, particularly in Xishuangbanna, Dehong, Lincang, Pu'er, and Honghe prefectures., Conclusion: Autochthonous outbreaks of dengue fever in Yunnan Province occurred predominantly in the border areas adjacent to Myanmar, Laos, and Vietnam. The largest outbreak in the province's history occurred in 2023, related to the increase in imported cases following the reopening of borders after the COVID-19 pandemic. Dengue fever is considered primarily an imported disease in Yunnan, emphasizing the need for enhanced control of cross-border transmission and mosquito vector management., Competing Interests: Declarations. Ethics approval and consent to participate: This study has been approved by the Scientific Research Ethics Committee of Yunnan Center for Disease Control and Prevention. The researchers emphasized that no personal identity was recorded. Consent for publication: Not applicable. Clinical trial number: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Soil serves as a significant reservoir of selenium (Se) and plays a crucial role for the entry of Se into the food chain. Therefore, it is of utmost importance to gain a deep understanding of the spatial and temporal variation of total soil Se content in China, as well as its influencing factors. This understanding is essential for the rational and efficient utilization of Se resources, the maintenance of ecological balance, and the preservation of human health in the future. Through a comprehensive literature search, relevant studies were identified, and information regarding soil total Se content, soil available Se content, soil pH, and soil organic matter (SOM) was extracted. The Mann-Kendall (M-K) test was employed to analyze the variation of total soil Se content, while Moran's I was used to examine the global and local spatial clustering characteristics of soil Se. The results indicate that the total Se content in China has shown an increase at different spatial and temporal scales, particularly in Central China. Furthermore, there is a significant difference in total Se content between cultivated soil and natural soil in Central China (P < 0.05). Additionally, soil physicochemical properties have been found to impact soil total Se content. Specifically, pH is negatively correlated with soil total Se content, while SOM is positively correlated with it (P < 0.05). Overall, the findings suggest that the total Se content in Chinese soil is increasing over time, and human agricultural activities and physicochemical properties of the soil, such as soil pH and SOM, likely influence the bioavailability of Se or the overall soil total Se content through their interaction with Se speciation in the soil to some extent. It is important to note that changes in environmental conditions may also have some degree of impact on the total Se content., (© 2025. The Author(s), under exclusive licence to Springer Nature B.V.)

Objective: To examine the characteristics and spatiotemporal changes in the phenotypes and genotypes of extended-spectrum β-lactamases (ESBLs) in Escherichia coli strains isolated from bloodstream infections (BSIs) across China between 2014 and 2021., Methods: 983 ESBL-positive E. coli strains were collected from BSIs in 66 hospitals across different geographic regions in China from 2014 to 2021. The phenotypic confirmation of ESBL was performed through the double-disc diffusion method. The genetic type was determined using polymerase chain reaction (PCR) followed by DNA sequencing., Results: Between 2014 and 2021, the prevalence of ESBL-positive E. coli steadily decreased from 61.2 to 49.6%. Among 983 phenotypically confirmed ESBL-positive E. coli, 763 (77.6%) were confirmed to carry ESBL genes, with the majority being of the CTX-M type, which is further divided into 23 subtypes and dominated by the CTX-M-9 and CTX-M-1 groups, with 457/763 and 333/763, respectively. Other ESBLs and ampC genes, such as bla OXA-1 , bla CMY , and bla DHA-1 , often coexisted with either the CTX-M-9 or CTX-M-1 groups. bla CTX-M-14 (34.3%, 157/457) and bla CTX-M-55 (45.9%, 153/333) were the dominant subtypes in the CTX-M-9 and CTX-M-1 groups, respectively. A notable increase in bla CTX-M-27 was observed, particularly from 2019 to 2021, with 26.4%, 23.1%, and 25.8% in all genotypes. Regarding the geographical distribution of the ESBLs, the highest rate of ESBL genetic positivity was observed in Southwest China, accounting for 84.9% (45/53), and the lowest was observed in Northeast China, with 73.2% (30/41). The abundance of the bla CTX-M-27 genotype, in particular, exhibited a notable increase in Southwest China, with 31.4% (14/45) of the strains exhibiting this genotype, followed by the CTX-M-55 genotype, with 13.6% (6/45) of the strains exhibiting this genotype., Conclusions: This study demonstrated a steadily decreasing trend in the incidence of ESBLs and predominant CTX-M type ESBLs, particularly the CTX-M-9 and CTX-M-1 groups, in E. coli strains across China, a notable increase in the bla CTX-M-27 genotype and regional variations in the ESBL gene distribution were detected., Competing Interests: Declarations. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

The evolutionary model of construction land serves as a fundamental pillar in national spatial development and planning research. However, previous studies have overlooked the "climbing" mode of construction land on three-dimensional terrains. To address this issue, utilizing elevation data and land use data from 2010 to 2020, this study employs slope analysis, intensity analysis, spatio-temporal transformation, and PLUS model to elucidate the spatial expansion process and driving forces of urban construction land in Chongqing from both two-dimensional and three-dimensional perspectives. The findings indicate that: (1) From a three-dimensional topographical standpoint, between 2010 and 2012, construction land gradually expanded towards low-slope areas, whereas between 2012 and 2020, it progressively extended into high-slope regions. (2) Regarding land type conversion patterns, the shift from arable land to construction land demonstrates a systematic inclination, while other transformations exhibit absolute or relative tendencies. Conversely, the conversion from construction land to arable land also displays a systematic pattern. (3) Since 2010, the growth process of construction land has transitioned from slow-equilibrium to rapid-disequilibrium with an expanding spatial disparity. (4) Most areas maintain relatively stable spatial conditions without significant jumps or transitions observed. (5) The expansion of construction land in Chongqing is primarily influenced by terrain, river, tunnel, rail transit, and other factors. The outcomes of this study can provide scientific foundations and decision-making references for rational planning in similar cities characterized by mountainous landscapes intersected by rivers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Facing the pressure of Sino-US strategic competition, countries in the Asia-Pacific region often adopt hedging strategies to minimize risk and protect their interests. If implemented, these strategies could impact relationships between countries and lead to political instability. Owing to a lack of theoretical evaluation frameworks and methods, few studies have examined the implementation effects of hedging strategies adopted by Asia-Pacific countries amid Sino-US competition. This study proposes a novel four-quadrant evaluation theoretical framework, and constructs a Geopolitical Relation Index and a Comparative Relation Index based on the Global Database of Events, Language, and Tone massive event data. Since 2000, the effects of hedging strategies in 19 Asia-Pacific countries against China and the US have been dynamically quantified. The research reveals that Asia-Pacific countries' dynamic performances over 24 years can be categorized into three groups: significantly closer to China, significantly closer to the US, and swinging. Since implementing the Belt and Road Initiative, countries close to China have deepened their ties, while those aligned with the US have strengthened their ties. Asia-Pacific countries have demonstrated similar characteristics from Obama's presidency to Biden's presidency. The results contribute to the dynamic assessment and ongoing monitoring of the execution effects of Asia-Pacific countries' diplomatic strategies towards China and the US, offering valuable insights for timely refinement of their foreign policies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Hu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ozone pollution was widely reported along with PM 2.5 reduction since 2013 in China. However, the meteorological drivers for ozone varying with different regions of China remains unknown using explainable machine learning, especially during the COVID-19 pandemic. Here we first analyzed spatiotemporal variations of PM 2.5 and ozone from 2015 to 2022 in eleven urban agglomerations of China. PM 2.5 decreased in all regions, with the largest drop in Beijing-Tianjin-Hebei (BTH). In contrast, ozone declined initially but rose during the pandemic in most regions, especially in Cheng-Yu. Probability density curves showed pronounced increase (24.7%) and slight change in the proportion of PM 2.5 and ozone meeting the pollution criterions during the pandemic, respectively. Leveraging Random Forest with SHAP analysis, we further established ozone models in typical urban agglomerations with good performance (CV-R 2  = 0.80-0.90; CV-RMSE = 8.52-19.20 μg/m 3 ) during the pandemic, and compared their relative importance of meteorological variables. Particularly, temperature and incoming shortwave flux at top of atmosphere were identified with high importance in high-ozone regions such as Middle Plain and BTH. Increasing importance of PM (e.g., PM 10 ) was found in southern China, e.g., Yangtze River Delta and Pearl River Delta regions. The western China was characterized with more importance of meteorology, especially in Tibet. Surface albedo and sensible heat flux from turbulence were noted distinctively with high importance in Tibet, partly due to their impacts on ozone formation by generating heat source and sink. In addition, sea level pressure (SLP) was revealed with the highest importance (25.2%) in Cheng-Yu, consistent with the fact that synoptic patterns characterized by SLP field could affect ozone pollution in Sichuan Basin. Our results not only provide an understanding of meteorological factors in regional ozone formation in China, but also highlight the feasibility of explainable machine learning in ozone studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: To understand the epidemiological characteristics and spatiotemporal distribution of genital herpes in China from 2010 to 2023 and provide evidence for the prevention and control of genital herpes. Methods: The reported data of genital herpes cases in 31 provinces (autonomous regions and municipalities) in China from 2010 to 2023 were collected from the National Notifiable Infectious Disease Reporting System of China Information System for Disease Control and Prevention. Software Joinpoint 5.2.0 was used to analyze the epidemiological characteristics of genital herpes, software ArcGIS 10.5 was used for spatial autocorrelation analysis, and software SaTScan 10.2.3 was used for spatiotemporal scanning analysis. Results: The reported incidence rate of genital herpes increased from 1.58/100 000 to 2.00/100 000 in China from 2010 to 2023, with an average annual percentage change of 0.90%. The upward trend of reported incidence rate was significant ( t =2.35, P =0.037). There was a positive spatial autocorrelation in the reported incidence of genital herpes with the global Moran's I ranging from 0.36 to 0.51 (all P <0.001). Local spatial autocorrelation analysis showed that the number of hotspots increased from 144 in 2010 to 232 in 2023, mainly distributed in provinces Zhejiang, Guangdong, Guangxi, Chongqing and Hunan. The number of hotspots in of Chongqing, Sichuan, Yunnan and Guizhou increased significantly from 7 to 57. A total of 67 spatiotemporal clusters were detected by spatiotemporal scanning analysis, mainly distributed in Guangdong from 2011 to 2015, in Zhejiang and Fujian from 2015 to 2019, and in Chongqing and Guizhou from 2019 to 2023. Conclusions: From 2010 to 2023, the reported incidence of genital herpes in China showed an upward trend, and there was an obvious spatiotemporal clustering of genital herpes. The distribution of hotspots was basically consistent with the distribution of spatiotemporal clustering areas, mainly distributed in the southeastern coastal area and southwestern region, and the spatiotemporal clustering areas gradually changed from the southeast coastal area to the southwest region.

The Taihangshan-Yanshan Region is an important ecological barrier area in Beijing-Tianjin-Hebei, and it is of great importance to investigate the spatial distribution pattern and driving mechanism of net primary productivity （NPP） of vegetation for ecological restoration. The MOD17A3HGF.061 NPP dataset was obtained using the Google earth engine（GEE）, and Sen trend, coefficient of variation, partial correlation, complex correlation, and residual analysis were applied to investigate the spatial and temporal patterns of vegetation NPP in the study area and to quantitatively isolate the relative contributions of climate change and human activities. The results showed that： ① The vegetation NPP in the study area showed an overall increasing trend from 2003 to 2021, with a rate of（C-based）2.57 g·（m 2 ·a） -1 and the distribution characteristics of "low in the surroundings and high in the middle" in the Taihangshan area, "high in the north and low in the south" in the Yanshan area, and "low in the north and low in the south" in the Yanshan area. At the same time, the spatial distribution characteristics of "low around and high in the middle" in the Taihangshan area and "high in the north and low in the south" in the Yanshan area were shown. Nearly 70% of the regions had medium or low volatility of vegetation NPP, and 80% of the regions had the opposite trend of future changes. ② The vast majority of NPP changes were positively correlated with precipitation and negatively correlated with temperature, but the significance was not strong； only 23% of the area had a strong correlation between vegetation NPP changes and meteorological factors, and it was concentrated in the central Yanshan Mountains, while the rest of the area was mainly driven by reasons other than climatic factors. ③ Potentially improved （NPP H &gt;0） and potentially degraded （NPP H &lt;0） areas were roughly equally distributed, but human activities played a positive role in most of the areas （79%）； 76% of the areas were dominated by human activities in the actual improved areas and 58% in the actual degraded areas, and human activities were the main factor dominating the NPP succession of vegetation in the study area. The results of this study provide an important reference for the formulation of precise vegetation ecological protection and restoration policies in the Beijing-Tianjin-Hebei ecological barrier area.

Exploring the trend of long time-series ecological quality evolution and spatial differentiation of influencing factors in Guiyang is of great significance for realizing regional ecological protection and high-quality development strategies. Based on the 7-period Landsat remote sensing images from 1991 to 2020, the remote sensing ecological index （RSEI） of Guiyang from 1991 to 2020 was calculated using the GEE remote sensing big data platform, and a geodetector, Hurst index, and coefficient of variation with different random sampling quantities and classification strategies were used to analyze the evolutionary pattern of ecological quality, change trends, and spatial differentiation influencing factors. The results showed that ① The ecological quality of Guiyang in the past 30 years was mainly medium and good, showing a wave-like pattern of change, with the highest and lowest values occurring in 2020 （mean value 0.58） and 2010 （mean value 0.47）, respectively, and the overall trend of the RSEI in the past ten years was good, with a spatial trend of decreasing distribution from the northeast to the southwest. ② The domain of values of the coefficient of variation for the RSEI in Guiyang was in the range of （0-2）, of which 46.61% of the area was in high fluctuation change, and the overall volatility of the RSEI was large； the mean value of the Hurst index was 0.59, and the area greater than 0.5 accounted for 73.98%, most of which showed weak persistence, and the future trend of change was the same as that of the past 30 years. ③ Different classification methods and random samples affect the q -value results of the geodetector, but the trend of the size ordering of the explanatory power of different factors was generally consistent. Land use, nighttime lighting index, slope, and population density indicators had stronger explanatory power for RSEI spatial differentiation； factor interaction detection was two-factor enhancement and nonlinear enhancement； and the interaction between land use and other factors was most favorable for explaining RSEI spatial differentiation.

Introduction: The primary aim of this study is to investigate and predict the prevalence and determinants of tuberculosis disease burden in China. Leveraging high-quality data sources and employing a methodologically rigorous approach, the study endeavors to enhance our understanding of tuberculosis control efforts across different regions of China. First, through nationwide spatio-temporal cluster analysis, we summarized the status of tuberculosis burden in various regions of China and explore the differences, thereby providing a basis for formulating more targeted tuberculosis prevention and control policies in different regions; Subsequently, using a time series-based forecasting model, we conducted the first-ever national tuberculosis burden trend forecast to offer scientific guidance for timely adjustments in planning and resource allocation. This research seeks to contribute significantly to China's existing tuberculosis prevention and control system., Materials and Methods: This research draws upon publicly available pulmonary tuberculosis (PTB) incidence and mortality statistics from 31 provinces and municipalities of mainland China between 2004 and 2018. We organized and classified these data according to province, month, year, and patient age group. Overall, the sample included 14,816,329 new instances of PTB and 42,465 PTB-related fatalities. We used spatiotemporal cluster analysis to record the epidemiological characteristics and incidence patterns of PTB during this period. Additionally, a time series model was constructed to forecast and analyze the incidence and mortality trends of PTB in China., Results: This study reveals significant regional variations in PTB incidence and mortality in China. Tibet (124.24%) and Xinjiang (114.72%) in western China exhibited the largest percentage change in tuberculosis (TB) incidence, while Zhejiang Province (-50.45%) and Jiangsu Province (-51.33%) in eastern China showed the largest decreases. Regions with significant percentage increases in PTB mortality rates (>100%) included four western regions, six central regions, and five eastern regions. The regions with relatively large percentage decreases in the mortality rate of PTB include Tianjin (-52.25%) and Shanghai (-68.30%). These differences are attributed to two main factors: (1) economic imbalances leading to poor TB control in underdeveloped areas, and (2) differences in TB-related policies among provinces causing uneven distribution of disease risks. Consequently, China may still face challenges in achieving the World Health Organization's 2030 tuberculosis control goals. Nationwide, the mortality rate of PTB in China increased between 2004 and 2018 (percentage change: 105.35%, AAPC: 4.1), while the incidence of PTB showed a downward trend (percentage change: -20.59%, AAPC: -2.1). Among different age groups, the 0-19 age group has the smallest disease burden. While incidence and mortality from TB were primarily found in adults 60 years of age or older, the age group of 0-19 years has the smallest burden of TB, highlighting obvious differences in age characteristics. It is predicted that the mortality rate of TB in China will continue to increase. In summary, the TB epidemic in China has been largely controlled due to the implementation of many public health programs and policies targeting specific groups and geographical areas. Finding and supporting effective health programs will make it possible to achieve the World Health Organization's goal of controlling tuberculosis in China., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Guo, Liu, Liu, Zhou, Ma, Zhang and Luo.)

Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries. It also aims to analyze the spatiotemporal distribution pattern of litter in the research area by estimating and analyzing the spatiotemporal pattern of litterfall along the desert riparian forests of the lower Qarqan and Tarim Rivers from 2001 to 2021. The results show that the initiation of the ecological water transfer project has facilitated the decomposition of litterfall, leading to an initial decline. Subsequently, the vegetation gradually recovered, leading to an increase in leaf litter input. Since 2001, litterfall initially decreased until reaching its lowest value of 4.39 × 10 9 kg in 2005, followed by a subsequent increase, reaching its highest value of 12.5 × 10 9 kg in 2021. The study concludes that ecological water conveyance promotes both the decomposition and increase of litterfall. Initially, it accelerates litterfall decomposition, while later stages foster an increase in Litterfall load. Meanwhile, due to the ecological water transfer project and the higher vegetation cover along the Tarim River compared to the Qarqan River, the Tarim River basin experiences higher average Litterfall load and variation., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

This paper aims to investigate the trend, spatio-temporal distribution, and socioeconomic inequality of the low birthweight rate (LBWR) in China from 1992 to 2021 and to project the LBWR to 2030. We performed a secondary analysis of data from the China Health Statistics Yearbook. LBWR refers to the ratio of the number of infants born with a birth weight less than 2,500 grams to the number of live births in a given year. We used joinpoint regression models to estimate LBWR trends from 1992 to 2021 for the whole country and from 2002 to 2021 for the three regions (eastern, central, and western regions) and each province. The slope index of inequality (SII) and relative index of inequality (RII) were calculated for each year from 2002 to 2021 based on provincial data. LBWR increased from 2.52% (1992) to 3.70% (2021), and the average annual percentage change (AAPC) (95% confidence interval [CI]) was 1.35% (0.22%, 2.49%) in China. The overall LBWR from 2002 to 2021 was greatest in the Eastern region, but LBWR had the fastest increase in the Western region, with an AAPC (95% CI) of 3.15% (2.59%, 3.12%). There were spatio-temporal differences in the LBWR and trends between provinces. The SII and RII increased linearly from -0.15 and 0.94 to 0.53 (B = 0.035%, p < 0.001) and 1.16 (B = 0.011, p < 0.01), respectively, over the past 20 years. The results of the ARIAM model showed that the National LBWR will be increasedfrom 3.70% in 2021 to 5.28% in 2030. The LBWRs in the eastern, central and western regions in 2030 will be 4.93%, 6.02% and 5.82%, respectively. National and local governments must prioritize disadvantaged groups to mitigate the rapid prevalence of LBWR, reduce regional disparities, and improve perinatal and infant health and health equity in China., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Evidence has shown that the incidence of bacillary dysentery (BD) is associated with climatic factors. However, the lagged effects of climatic factors on BD are still unclear, especially lacking research evidence from arid and semi-arid regions. Therefore, this study aims to add new insights into this research field., Methods: Spatial autocorrelation, time series analysis and spatiotemporal scans were used to perform descriptive analyses of BD cases from 2009 to 2019. On the basis of monthly data from 2015 to 2019, multivariable distributed lag non-linear models were used to investigate the lagged effects of climatic factors on BD., Results: The hot spots for BD incidence are gradually decreasing and becoming increasingly concentrated in the southern part of Gansu Province. The maximum cumulative relative risks for monthly average temperature, sunshine duration, average relative humidity and precipitation were 3.21, 1.64, 1.55 and 1.41, respectively. The lagged effects peaked either in the current month or with a 1-month lag, and the shape of the exposure-response curve changed with the increase in maximum lag time. After stratification by per capita gross domestic product, there were differences in the effects., Conclusions: Climatic factors can influence the incidence of BD, with effects varying across different lag times. It is imperative to vigilantly track the disparities in the incidence of BD attributable to economic factors., (© The Author(s) 2024. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

Objectives: To investigate the spatiotemporal variations in body mass index among Han adolescents aged 18 years across 27 provinces of China from 1985 to 2019., Study Design: Cross-sectional epidemiological study., Methods: A total of 141,406 adolescents aged 18 years were included from eight Chinese National Surveillance on Students' Constitution and Health from 1985 to 2019. Body mass index data were extracted from 27 provinces in each CNSSCH. All provinces were categorized into seven regions. Linear regression was used to assess the trends., Results: The population-based national body mass index of boys and girls aged 18 years from 27 provinces increased by 2.35 kg/m 2 and 1.40 kg/m 2 , respectively (all p < 0.001). Body mass index has been greater and the increase was larger in North China and East China during the 34-year period. Body mass index has been smaller and the increase was smaller in South China and Southwest China. The Northeast China had the largest increase in body mass index, becoming the region with the largest body mass index through 2019., Conclusion: The body mass index among Chinese adolescents aged 18 years across provinces increased from 1985 to 2019. Further national and local efforts are needed to address spatiotemporal variations in body mass index., (Copyright © 2024 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Extreme air pollution poses global health and environmental threats, necessitating robust policy interventions. This study first analyses the surface mass concentration of major aerosols (such as black carbon, organic carbon, dust, sea salts, and sulphates) to estimate global PM 2.5 concentrations from 1980 to 2023. The developed model-estimated PM 2.5 database was validated against data from 526 cities worldwide, showing strong accuracy, with RMSE, r, and R 2 values of 7.47 μg/m³, 0.87, and 0.75, respectively. The motivation arises from the need to understand whether recent pollution increases are driven by rising emissions or natural variability, given the significant impacts on life and property. To assess both short-and long-term pollution trends, magnitudes, and risks, we proposed twelve novel extreme pollution indices, which comprehensively characterize the spatial and temporal variations in pollution. The highest PM 2.5 concentrations were observed in regions near the Saharan Desert, reaching up to 90,000 μg/m³. However, significant PM 2.5 TOT (total pollution) concentrations were also found in the Indo-Gangetic Plain (IGP) and eastern China, ranging from 20,000 to 40,000 μg/m³. Persistent pollution burdens North Africa for approximately 350 days annually, while the IGP and eastern China experience extreme pollution for over 200 days yearly. Other pollution indices highlight the intensity and frequency of pollution in regions such as North Africa, IGP, Eastern Russia, Western USA, and Eastern China, revealing critical regional air quality challenges. Our analysis identifies cities in low-income and middle-income countries, such as New Delhi, Lahore, Dhaka, and Dammam, as being at extreme risk scores above 90 out of 100. Meanwhile, cities like Ghaziabad, Chongqing, Kolkata, Mumbai, and East London fall into the high-risk category, scoring between 60 and 80. Conversely, most cities in the EU, USA, and Canada are at very low risk, a result of the effective implementation of strategic air pollution norms and policies. The study promotes a phased approach for low- and middle-income regions, emphasizing achievable air quality standards, low-cost monitoring, targeted interventions, urban greening, public awareness, and innovative financing for improvements., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Groundwater pollution of the loess plateau regions has become a global concern due to its vulnerability to natural and anthropogenic influences. In this study, 146 water samples were investigated to identify the spatiotemporal variability in groundwater chemistry, pollution sources and nitrate health risks in two interconnected river basins of a typical loess region. The results showed that except for bicarbonate, spatiotemporal variability of hydrochemical components in Malian River Basin (ML) was generally greater than that in Upper Jinghe River basin (JH-U) due to the hydrogeological conditions, and the hydrochemical facies in two river basins transformed from SO 4 ·Cl and Cl·SO 4 types to HCO 3 and HCO 3 ·SO 4 types. The results of integrated-weight quality index (IWQI) showed that 77.8 % (1970s), 33.3 % (2004), 34.3 % (2015) of samples in ML exceeded the standard limits of Class IV groundwater quality, displaying a high pollution level with an improvement trend, while groundwater quality in JH-U indicated a very low pollution level with a deterioration trend. The geogenic source was identified as a main factor affecting groundwater quality, with contributions of 59.2 % and 48.7 % in JH-U and ML (2015), respectively. The anthropogenic sources including agricultural activities (20.7 % and 21.8 % in JH-U and ML) and coal mining activities (20.1 % and 29.5 % in JH-U and ML) also played a role in affecting groundwater quality. The nitrate health risk assessment demonstrated that 39.1 % and 20.3 % of groundwater samples (2015) significantly exceeded the standard threshold (Hazard Index = 1), implying a higher health risk to children than adults, and the nitrate health risk in ML was obviously greater than that in JH-U. This study provides novel insight into the spatiotemporal variability in groundwater chemistry, quality and health risk in loess regions under the influence of geogenic and anthropogenic factors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Although the relationship between urbanization and influenza has received increasing attention, previous studies have often examined this relationship based on single indicators, neglecting the multi-dimensions of urban development and their integrated impact on influenza incidence in neighboring cities., Methods: A multidimensional urbanization evaluation framework was developed based on social, economic, and ecological dimensions to comprehensively assess urbanization. Then, we analyzed the impact of urbanization development on influenza incidence within and across cities using Bayesian spatiotemporal models and spatial Durbin models. Regional heterogeneity analysis was performed to investigate the impact of urbanization on influenza incidence within cities., Results: From 2014 to 2019, there were 5,062,254 influenza cases in 283 prefecture-level cities in China. Each standard deviation increment in comprehensive, social, and economic indexes of urbanization was associated with a 14.9% (95% CI: 6.1%, 24.3%), 9.9% (95% CI: 3.5%, 16.3%), and 13.4% (95% CI: 4.5%, 23.7%) increase in influenza incidence, respectively. The effects of urban development on influenza incidence varied significantly across regions, with the greatest impact found in southern China. Additionally, a significant positive spatial spillover effect of urbanization was observed on influenza incidence in surrounding cities., Conclusions: Urbanization and its various dimensions were linked to increased risk of local influenza incidence, which also showed substantial positive spatial spillover effect to surrounding areas. During the rapid urbanization process in China, local governments should prioritize equity and accessibility in healthcare services and strengthen the coordinated prevention and control of influenza epidemics across cities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The occurrence of steroid hormones in small river ecosystems raises environmental alarms due to their limited dilution capacity, heightened susceptibility to diverse pollution sources, and their substantial contribution to the contamination of larger river systems. Here, we investigated the occurrence of 40 steroid hormones over 10 months in 10 first-order tributaries (n = 250) of Guangzhou City, China. The observed concentrations of Σsteroid hormones ranged from 30.5 to 450 ng/L (mean: 55.6 ± 35.4 ng/L). No substantial variation in steroid hormone concentrations was observed between the flood and dry seasons, reflecting an intricate balance of dilution dynamics, agricultural runoff, and wastewater releases. Further correlation analysis underscored wastewater discharge as a consistent source of steroid hormone occurrence, with spikes coinciding with concurrent fertilizer application and rainfall intervals. Steroid hormone concentrations displayed significant spatial variations. Correlation analyses connected steroid hormone levels to nutrients in tributaries and agricultural ditch water and land usage, highlighting the joint effect of runoff and various wastewater types on steroid hormone distribution. Interestingly, steroid hormone levels displayed minimal variation along the tributaries, suggesting uniform and continuous pollution sources. Source attribution analysis revealed that 51.7 % of steroid hormones originated from untreated domestic wastewater, followed by treated wastewater, livestock wastewater, and runoff. Notably, 92.0 % of the sampling sites registered at least one steroid hormone level exceeding the risk quotient threshold of 1, indicating widespread ecological hazards. Our research emphasizes the persistent and stable nature of steroid hormone-related risks across seasons and along the tributaries, highlighting the imperative for vigilant monitoring. We further advocate for intensified surveillance efforts during pivotal periods (e.g., fertilization periods and low rainfall intervals), to better address these environmental challenges., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Oxygenated polycyclic aromatic hydrocarbons (OPAHs) have garnered significant scientific attention due to their heightened toxicity and mobility compared to their parent PAHs. This study investigated the occurrence of 11 OPAHs and 16 PAHs within agricultural ditch sediment of Guangzhou City, China. The ΣPAH and ΣOPAH concentrations ranged from 63.8-3955 ng/g and 16.5-522 ng/g, respectively. Notably, concentrations were elevated during the rainy season, attributed to intensified atmospheric deposition and surface runoff during the rainy season. Spatially, Pearson correlation and path analysis disclosed a linkage between OPAHs and high-molecular-weight PAHs and adjacent agricultural practices, whereas low-molecular-weight PAHs were associated with human and industrial operations. This disparity was linked to the restricted mobility of high-molecular-weight PAHs, rendering them particularly susceptible to proximal sources. Diagnostic ratios and principal component analysis-multiple linear regression (PCA-MLR) implicated fossil fuel combustion and vehicle emissions as major contributor to the sedimentary OPAHs and PAHs. Further correlations between estimated source contributions and water quality, strengthened by spatial interpolation, clearly identified agricultural activities, and atmospheric deposition associated with traffic emissions and fossil fuel combustion as primary contributor to sedimentary OPAHs and PAHs. Secondary sources encompassed coal combustion, road runoff, and wastewater from both industrial and shipping activities. The risk quotients (RQs) for PAH and OPAH mixtures indicated moderate to high ecological hazards. This study demonstrated the importance of employing the integrated approach, combining PCA-MLR, diagnostic ratios, and correlation of source contributions with water quality in precisely delineating the origins of OPAHs and PAHs in agricultural ditch sediment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

China's electric power industry has made significant efforts to reduce environmental externality in the past two decades. However, the extent of the reduction, the driving factors behind it, and the regional performance are not well clarified. This study constructs a comprehensive framework that integrates the impact pathway approach with index decomposition analysis to explore the driving factors behind the reduction of environmental externality from a spatial-temporal perspective. First, the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model is adopted in the impact pathway approach to assess the environmental losses in China's electric power industry. Second, the temporal index decomposition analysis is used to explore the driving factors behind the reduction in environmental losses during 2005-2020. Third, the spatial index decomposition analysis is employed to investigate the differences in environmental performance across regions and the driving forces behind these differences. The results show that the environmental losses caused by China's electric power industry have been significantly reduced from 3082.1 thousand years of life lost (YLL) in 2005 to 892.3 thousand YLL in 2020, mainly due to the reduction in air pollutant emissions, followed by the cleaner power structure and the adjustment of the spatial layout of electricity. While, increases in power generation scale, population size, and aging have played a negative role in reducing environmental losses. The gaps in environmental losses per unit of electricity between different provinces can be tens or even hundreds of times. The primary drivers of these gaps, apart from the power structure, are atmospheric dispersion conditions and population density. While, the differences in emission intensity effects among provinces are relatively small. Thus, the orientation of policy design needs to shift from setting stricter emission concentration limits to adjusting energy structure and enhancing the construction of electricity transfer channels. Government departments should consider the implicit environmental externality from a more macro perspective when conducting power planning and management., Competing Interests: Declaration of competing interest No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Obtaining the high-resolution distribution characteristics of urban air pollutants is crucial for effective pollution control and public health. In order to fulfill it, mobile monitoring offers a novel and practical approach compared to traditional fixed monitoring methods. However, the sparsity of mobile monitoring data still makes it a challenge to recover the high-resolution pollutant concentration across an entire area. To tackle the sparsity issue and fulfill a prediction of the spatiotemporal distribution of PM 2.5 , a high-resolution urban PM 2.5 prediction method was proposed based on mobile monitoring data in this study. This method enables prediction with a spatial resolution of 500m × 500m and a temporal resolution of 1 h. First, a Light Gradient Boosting Machine (LightGBM) was trained using mobile monitoring of PM 2.5 concentration and exogenous features to obtain complete spatiotemporal PM 2.5 concentration. Second, a model consisting of Convolutional Neural Network and Transformer (CNN-Transformer) with a customised loss function was established to predict high-resolution PM 2.5 concentration based on complete spatiotemporal data. The method was validated using real-world data collected from Cangzhou, China. The numerical results from cross-validation showed an R 2 of 0.925 for imputation and 0.887 for prediction, demonstrating this method is suitable for high-resolution spatiotemporal prediction of PM 2.5 concentration based on mobile monitoring data., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The livestock sector is a major source of non-CO 2 greenhouse gas (GHG). As China has the world's largest livestock production, analyzing factors influencing GHG emission intensity of livestock (GEIL) is crucial for guiding its emission reduction policies. Yet, most current studies on livestock GHG focus on emission amount (GEAL) over GEIL, neglecting comprehensive utilization of spatial econometric models. Furthermore, the influencing factors mainly focus on population, economic level, urbanization, and industrial structure, while the exploration of factors such as technological innovation, consumers' age structure, and industrial agglomeration remains insufficient. This study first applied the standard deviation ellipse (SDE) model to describe the spatiotemporal evolution of GEAL and GEIL across 31 Chinese provinces from 2006 to 2022. Then, using extended STIRPAT theory, we analyzed GEIL's influencing factors with exploratory spatial data analysis (ESDA) and the geographically and temporally weighted regression (GTWR) model. The results showed that: (1) GEAL was concentrated in resource-rich grassland pastoral and grain-producing areas. Provincial GEAL trends varied, while national GEAL declined rapidly and then fluctuated slightly. Cattle, pigs, and sheep/goats contributed the most to GEAL. (2) GEIL significantly decreased nationwide and provincially, with Tibet having the highest reduction rate but still leading in GEIL. (3) GEAL followed a northeast-southwest distribution, whereas GEIL exhibited an east (slightly north) to west (slightly south) pattern. (4) Spatial analysis revealed significant GEIL clustering, with higher values in western provinces and lower in central and eastern regions. (5) Population scale, urbanization, age structure, proportion of ruminant animal production value, location quotient of livestock, employment income per capita of agricultural personnel, patent-granted intensity, and educational level in rural areas had diverse spatiotemporal impacts on GEIL across provinces. Tailored emission reduction policies and regional collaborative governance are recommended., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: The allocation of resources in elderly care institutions is directly linked to the well-being, quality of life and sustainable development of public health for the elderly. However, a disparity in elderly care resources between urban and rural areas exists. Therefore, this study aimed to explore resource allocation efficiency in China's urban and rural institutional elderly care., Study Design: Employing a mixed-methods approach, the research integrated quantitative analysis with spatial-temporal assessments to investigate spatial-temporal evolution patterns of resource allocation efficiency., Methods: A Projection Pursuit Evaluation Model (PPM) utilising an Accelerated Genetic Algorithm was applied to measure the input and output of urban and rural elderly care institutions. Data Envelopment Analysis (DEA) was used to visualise the static and dynamic efficiency. Spatial analysis techniques determined the spatial evolution of resources., Results: Significant disparities in resource allocation between urban and rural areas were identified, with rural areas facing declining numbers of elderly care institutions despite having a larger ageing population. The efficiency analysis revealed room for improvement in both urban and rural settings, emphasising the need to strengthen management and technology in elderly care institutions., Conclusions: Addressing the challenges of elderly care in China requires policy reform, enhanced government support and stimulation of private investment, particularly in rural areas. A shift towards quality-focused elderly care and strategic investments is crucial for equitable and efficient service provision across China., (Copyright © 2024 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

The declining birth rate is one of the world's major challenges. There is much literature on birth rate research in China. However, there are few studies on spatial distribution and influencing factors of birth rate in the Yangtze River Basin. In this study, data from 11 regions of the Yangtze River Basin from 2006 to 2023 were used to analyze the spatial and temporal distribution characteristics of birth rates using GIS spatial visualization and four-quadrant diagram. At the same time, 13 factors affecting birth rates were combined to carry out research. The results show that: (1) In 2023, five regions reported birth rates above 7‰, with Tibet faring the best, while six regions had rates below 7‰, with Hunan being the least favorable. (2) The first type of birth rate area shows a process of slow increase-slight decrease-accelerated growth-rapid decrease; the second type of birth rate area shows a process of gradual decrease-moderate increase-rapid decrease-rapid increase-rapid decrease; the third type of birth rate area has increased rapidly since 2021. The three types of birth rate areas show the characteristics of the spatiotemporal pattern of continuous spread and development. (3) The aging rate, per capita GDP, proportion of primary industry output value, proportion of tertiary industry output value, female illiteracy rate, per capita disposable income, per capita consumption expenditure, urbanization rate, proportion of higher education, juvenile dependency ratio, and elderly dependency ratio have different degrees of influence on the birth rate., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study explores the intricate dynamics of volatility within high-frequency financial markets, focusing on 225 of Chinese listed companies from 2016 to 2023. Utilizing 5-minute high-frequency data, we analyze the realized volatility of individual stocks across six distinct time scales: 5-minute, 10-minute, 30-minute, 1-hour, 2-hour, and 4-hour intervals. Our investigation reveals a consistent power law decay in the auto-correlation function of realized volatility across all time scales. After constructing cross-correlation matrices for each time scale, we analyze the eigenvalues, eigenvectors, and probability distribution of Cij based on Random Matrix Theory. Notably, we find stronger correlations between stocks at higher frequencies, with distinct eigenvector patterns associated with large eigenvalues across different time scales. Employing Planar Maximally Filtered Graphs method, we uncover evolving community structures across the six time scales. Finally, we explore reaction speed across multiple time scales following big events and compare industry-specific reactions. Our findings underscore the faster reaction speed at higher frequency scales, shedding light on the multifaceted dynamics of high-frequency financial markets., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ouyang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Sustainable development is a hot topic of global concern and sustainable human settlements (HS) are crucial to people's happiness. Thus, strengthening the construction of HS will help enrich human settlements geography with theories of HS interactions, clarify the existing problems of the Chengdu-Chongqing urban agglomeration (CC), promote the harmonization of the human-land relationship, and realize the SDGs. The results were as follows. (1) the quality of HS exhibited an upward trend with diminishing disparities in PLE functions. (2) A spatial layout featuring the high quality of HS in the east and west and low quality in the central areas was identified, with Chengdu and Chongqing serving as two high-value core areas. (3) The evolution of the quality of HS levels to achieve a leapfrog shift was challenging and the spatial spillover effect and phenomenon of "club convergence" were evident. (4) Living function was a primary obstacle at the criterion layer and indicators within production function became major obstacle factors at the element layer. These findings have enriched the research scope of human settlements geography from the scale of urban agglomerations, and provided scientific decisions for the SDGs., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Objectives: This study aimed to explore the spatial and temporal distribution of hepatitis C and its influencing factors in Chongqing, providing a scientific basis for the relevant departments to formulate targeted preventive measures for the high prevalence of hepatitis C in the region and population., Design: We collected data on hepatitis C cases in Chongqing (located in the southwest of China) from 2014 to 2020, and analysed the spatiotemporal heterogeneity of hepatitis C incidence in different populations and identified factors that might influence the incidence of hepatitis C by constructing a Bayesian spatiotemporal model., Settings: The study subjects included clinically diagnosed cases and confirmed cases of hepatitis C with current address in Chongqing and onset date between 1 January 2014 and 31 December 2020., Participants: The study used aggregated data, including 33 900 clinically diagnosed cases and confirmed cases of hepatitis C., Results: From 2014 to 2020, the high-risk areas of hepatitis C were primarily concentrated in the main and new urban areas of Chongqing. In contrast, the low-risk areas were mainly found in southeast and northeast Chongqing. There was also an increasing trend in the risk of incidence in the low-risk areas. Analysis of different populations revealed that men aged 45-59 years had a higher risk of developing hepatitis C in the main urban area compared with other age groups. Additionally, the risk for this population group showed an increasing trend in the southeast and northeast of Chongqing as well as the main urban area. Among women, the rising trend of hepatitis C risk was stronger for those aged 30-44 years in southeast Chongqing and for those aged 45-59 years in northeast Chongqing compared with other age groups. The analysis of influencing factors found that gross domestic product per capita, population density and the proportion of tertiary industry were associated with an increased risk of hepatitis C., Conclusions: High-risk areas for hepatitis C virus were mainly located in the main and new urban areas of Chongqing, where the male prime-age population was the focus of prevention and treatment. In the future, the relevant authorities should concentrate on high-risk areas and at the same time strengthen screening and serological surveys for hepatitis C in low-risk areas and various populations, and raise public awareness of prevention, so as to reduce the incidence of hepatitis C., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public's concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies., Methods: Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient., Results: The following findings are presented. First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". The spatial correlation of attention has been strengthened, and the high-high clusters are mainly distributed in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Greater Bay Area (GBA) urban agglomerations. Third, regional differences in overall public attention narrowed in China, with intra-regional differences narrowing in seven regions (Northwest China, Central China, and so on), and intra-regional differences increasing in East China. The dominant role in the Gini coefficient changes from transvariation intensity to inter-regional differences., Conclusion: Major public health emergencies stimulate the public's attention to health topics. Although the short-term increase in vaccination-related public attention was not observed to translate into a long-term increase in public vaccine literacy, the seasonal and regional differences in vaccination-related public attention in China have significantly narrowed before and after COVID-19, suggesting that the imbalance between public health literacy levels has improved., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The water-level fluctuation zone (WLFZ) is a unique riparian region that forms in response to the operation of the reservoir. The periodic submersion-exposure conditions severely affect the properties of soil and vegetation, thus also change the spatial and temporal development of soil aggregate stability. Nonetheless, the changes in both space and time concerning soil aggregate stability and the factors influencing it during the exposure period in the WLFZ are still unclear. Consequently, the WLFZ within the Three Gorges Reservoir area (TGRA) was taken as the research object, soil and plant samples were obtained from various elevations along the slope at different times to capture the spatial and temporal changes in soil and plant characteristics throughout the exposure period. Moreover, the wet sieving method was utilized to measure the aggregate size distribution and stability of soil aggregates. To further analyze the effects of both individual and mutual variables on the spatial and temporal changes in aggregate stability, methods such as Pearson ' s correlation analysis, redundancy analysis (RDA), variation partitioning analysis (VPA), and partial least squares path modeling (PLS-PM) were employed. The findings revealed that aggregate stability increased with increasing elevation until peaking and then decreased spatially, whereas the passage of time contributed to enhanced aggregate stability. The spatial variation in aggregate stability was greater than temporal variation. RDA revealed that soil properties (bulk density, soil water content in mass, clay, silt, sand, pH and soil organic matter), environmental factors (elevation, water level, submersion duration and exposure duration) and plant characteristics (shoot and root biomass) contributed 53.6 %, 45.4 % and 0.9 %, respectively, to the spatiotemporal variability in aggregate stability. VPA and PLS-PM analysis further revealed that the main factors controlling the aggregate stability were soil chemical properties. These results provide a basis for further studies on the soil and water conservation in the WLFZ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Studying the spatial relationship and driving forces between grain production and economic development in China can assist in the coordinated development of economic growth and grain production in both China and other developing countries. Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China's county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. The results show that (1) from 2000 to 2019, China's SDIGE showed a development trend of "up-down-up," and the highest SDIGE was in the northeast region, the lowest in the east region, and the spatial pattern of "high in the northeast-low in the east coast" was increasingly prominent. (2) In terms of spatial difference, the overall difference of SDIGE in China from 2000 to 2019 showed a rising trend of development; The average contribution rate of the regional difference to the overall difference was the lowest, maintained at about 17.82%; The average contribution rate of intra city and inter-county differences to the overall difference is the highest, which is about 34.20%. (3) In terms of the driving force, the level of economic development hurts SDIGE, while population density, industrial structure, fiscal decentralisation, and terrain fluctuation have a positive and negative impact on SDIGE. To alleviate the imbalance between China's economic development and grain production, it is necessary to implement differentiated policy measures tailored to the specific characteristics of different regions to assist agricultural producers and enhance the stability of grain production., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright: © 2024 Chen, Zhang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: By monitoring arsenic levels in rural drinking water in Inner Mongolia Autonomous Region from 2013 to 2022 and evaluating their health risks, this study provides a basis for further developing strategies to promote public health., Methods: One stable centralized water supply point was randomly selected in each township of Inner Mongolia Autonomous Region. One finished water sample and 1-3 tap water samples were collected at each supply point. Water samples were collected once during the dry season (May) and once during the rainy season (August-September). Mann-Whitney U test was used to compare arsenic concentrations in drinking water from different types of water sources, and Kruskal-Wallis test was used to compare arsenic concentrations in drinking water across different years. Environmental health risk assessment was conducted using the health risk assessment model recommended by the US Environmental Protection Agency (USEPA)., Results: Overall, arsenic concentrations in rural drinking water were higher in the central-western part of Inner Mongolia Autonomous Region compared to the eastern part. From 2013 to 2022, there was a notable decreasing trend in arsenic concentrations in rural drinking water, with over 98% of water samples meeting arsenic standards by 2022. During 2013-2019, arsenic concentrations in drinking water sourced from groundwater were consistently higher than those from surface water sources (P < 0.05). Hazard quotient (HQ) values for the entire population were below 1, and lifetime cancer risk (LCR) values exceeded 1 × 10 - 6 . Sensitivity analysis indicated that drinking water arsenic concentration contributed the most to health risks for the population., Conclusion: During 2013-2022, through concerted efforts by the government and the people, excessive arsenic levels in rural drinking water have been significantly reduced, resulting in decreased health risks for the population. However, some carcinogenic risks still exist.Therefore, the next critical step in improving water quality in the region involves further optimizing methods such as coagulation, adsorption, or ion exchange to remove arsenic from drinking water., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Marine yeasts play a crucial role in marine microbial ecology, facilitating the biogeochemical cycling of carbon and nitrogen in marine ecosystems, while also serving as important reservoirs of bioactive compounds with extensive applications in pharmaceuticals, agriculture, and various industries. Intertidal flats, characterized by their complex ecological dynamics, are postulated to harbor a wealth of yeast resources. This study employed a culture-dependent approach to assess the diversity, spatio-temporal distribution, and biotechnological potential of yeast communities residing within the intertidal sediments and seawater of Aoshan Bay. A total of 392 yeast strains were identified from 20 distinct genera, encompassing 43 recognized species and four candidate novel species. Notably, 17 of these species were identified as novel occurrences in marine environments, underscoring the rich yeast biodiversity of the Aoshan Bay ecosystem, with Candida emerging as the dominant genus in both sedimentary and aqueous habitats. Yeast community composition exhibited significant spatial and temporal variation, with peak diversity and abundance observed in autumn, the subtidal zone, and the surface soil layer. No clear pattern, however, emerged linking these shifts to specific changes in community composition, highlighting the complex interactions between microbial communities, environmental variables, and anthropogenic disturbance. Although several yeast species isolated here have been previously recognized for their biotechnological potential, their diverse and abundant extracellular enzyme profiles were characterized, further highlighting their crucial role in organic matter decomposition and nutrient cycling within the tidal ecosystem, as well as their potential applicability in the food, fine chemical, textile, and pharmaceutical industries.IMPORTANCEThis study presents groundbreaking insights into the yeast diversity of Aoshan Bay, offering invaluable information on their spatial and temporal distribution patterns, as well as their biotechnological potential in the tidal environment. The findings reveal that the eutrophic intertidal flat is a rich repository of yeasts with abundant extracellular enzymatic activity and an important role in nutrient cycling and decomposition processes. Also, these yeasts serve as crucial indicators of ecosystem health and function and are excellent candidates for biotechnological and industrial applications. Collectively, this study not only expands our knowledge of the diversity and distribution of intertidal yeasts but also highlights their promising potential for biotechnological applications., Competing Interests: The authors declare no conflict of interest.

Grassland plays a crucial role in the global cycles of matter, energy, water and, climate regulation. Biomass serves as one of the fundamental indicators for evaluating the ecological status of grassland. This study utilized the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP) from meteorological data and the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) remote sensing data for northern China's temperate and alpine grasslands from 1981 to 2015. NPP was subsequently converted into aboveground biomass (AGB). The dynamic changes in grassland AGB were analyzed, and the influence of climate change was examined. The results indicate strong agreement between AGB estimations from the CASA model and Gill method based on field-measured AGB, confirming the model's reliability for these regions. The dynamic changes in AGB exhibited a significant increasing trend of 1.31 g/m2. Grazing intensity (GI), soil moisture, and mean annual precipitation are identified as key factors influencing changes in grassland AGB. Our findings indicate that precipitation and soil moisture are the primary drivers of AGB accumulation during the growing season (spring, summer, and autumn), while temperature plays a critical role in supporting biomass accumulation during winter. Higher temperatures in winter contributes to increased AGB in the following spring, particularly in desert steppe and alpine meadow ecosystems. These insights highlight the complex interaction between climate factors and human activities in shaping grassland productivity across different seasons., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Human-induced interventions have altered the local characteristics of the lake ecosystems through changes in hydraulic exchange, which in turn impacts the ecological processes of antibiotic resistance genes (ARGs) in the lakes. However, the current understanding of the spatiotemporal patterns and driving factors of ARGs in water-diversion lakes is still seriously insufficient. In the present study, we investigated antibiotic resistome in the main regulation and storage hubs, namely Nansi Lake and Dongping Lake, of the eastern part of the South-to-North Water Diversion project in Shandong Province (China) using a metagenomic-based approach. A total of 653 ARG subtypes belonging to 25 ARG types were detected with a total abundance of 0.125-0.390 copies/cell, with the dominance of bacitracin, multidrug, and macrolide-lincosamide streptogramin resistance genes. The ARG compositions were sensitive to seasonal variation and also interfered by artificial regulation structures along the way. Human pathogenic bacteria such as Acinetobacter calcoaceticus, Acinetobacter lwoffii, Klebsiella pneumoniae, along with the multidrug resistance genes they carried, were the focus of risk control in the two studied lakes, especially in summer. Plasmids were the key mobile genetic elements (MGEs) driving the horizontal gene transfer of ARGs, especially multidrug and sulfonamide resistance genes. The null model revealed that stochastic process was the main driver of ecological drift for ARGs in the lakes. The partial least squares structural equation model further determined that seasonal changes of pH and temperature drove a shift in the bacterial community, which in turn shaped the profile of ARGs by altering the composition of MGEs, antibacterial biocide- and metal-resistance genes (BMGs), and virulence factor genes (VFGs). Our results highlighted the importance of seasonal factors in determining the water transfer period. These findings can aid in a deeper understanding of the spatiotemporal variations of ARGs in lakes and their driving factors, offering a scientific basis for antibiotic resistance management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The high-quality development of tourism is crucial to the sustainable development of regional economy. To evaluate high-quality tourism development, this paper has developed an index system with 6 second-level indicators and 24 third-level indicators and used methods of entropy-weight, AHP, and TOPSIS to empirically assess the high-quality tourism development of 9 cities in Fujian Province. According to the results, there are obvious regional differences in the development of high-quality tourism in Fujian Province. From 2016 to 2019, the overall development trend of cities in Fujian Province was consistent, showing a steady upward trend. Green development in tourism has the best performance, which was less affected by the COVID-19. Fuzhou and Xiamen contribute most to the tourism development of Fujian Province, while other cities are lagging behind for various reasons and the lack of innovation and shared development are two of them. Based on the results of the research, we put forward the following suggestions: Fujian should coordinate the planning of the province's green eco-tourism resources to maximize the use of resources. It should combine the advantages of the primary, secondary and tertiary industries and fully develop both advanced regions and under-developed regions. It should also explore areas of potential growth in the tourism sector, such as Sanming, Longyan, and Nanpin, by strengthening digital innovation and sharing resources with Xiamen, Fuzhou, Quanzhou and other highly-developed tourism regions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Scrub typhus is a life-threatening zoonotic infection. In recent years, the endemic areas of scrub typhus have been continuously expanding, and the incidence rate has been increasing. However, it remains a globally neglected disease. Yunnan Province is a major infected area, and the study of spatiotemporal and seasonal variation scrub typhus in this region is crucial for the prevention and control of the disease., Methods/results: We collected surveillance data on scrub typhus cases in Yunnan Province from 2006 to 2022. Using methods such as spatial trend analysis, Moran's I, and retrospective temporal scan statistics, the spatial and seasonal changes of scrub typhus were analyzed. The study period recorded 71,068 reported cases of scrub typhus in Yunnan Province, with the annual incidence rate sharply increasing (P<0.001). Approximately 93.38% of cases are concentrated in June to November (P = 0.001). Nearly 98.0% of counties were affected. The center of gravity of incidence migrates in a south and west direction. The incidence of scrub typhus was positively correlated spatially, and the spatial clustering distribution was significant. The most likely spatial cluster of cases (relative risk = 14.09, P<0.001) was distributed in Lincang, Dehong, Baoshan, Banna, and Puer. Significant positive correlations between the number of scrub typhus cases and average temperature, precipitation and relative humidity., Conclusions: In Yunnan Province, scrub typhus is widely transmitted, with an increasing incidence, and it exhibits distinct seasonal characteristics (from June to November). The center of gravity of incidence has shifted to the south and west, with higher incidence rates observed in border regions. The risk clustering regions encompass all border prefectures. This pattern is significantly correlated with climatic factors such as average temperature, precipitation, and relative humidity. The relevant departments should strengthen the monitoring of scrub typhus, formulate prevention and control strategies, and provide health education to local residents., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

PM 2.5 bound mercury (PBM 2.5 ) in the atmosphere is a major component of total mercury, which is a pollutant of global concern and a potent neurotoxicant when converted to methylmercury. Despite its importance, comprehensive macroanalyses of PBM 2.5 on large scales are still lacking. To explore the driving factors, spatiotemporal pollution distribution, and associated health risks, we compiled a comprehensive dataset consisting of PBM 2.5 concentrations and spatiotemporal information across China from 2000 to 2023 that was collected from the published scientific literature with valid data. By incorporating corresponding multidimensional predicting variables, the best-fitted random forest model was applied to predict PBM 2.5 concentrations with a high spatial resolution of 0.25° × 0.25°, and the health risk assessment model was used for subsequent health risk assessment. Our results indicated that population density and PM 2.5 emissions from power generation were the main contributors to PBM 2.5 concentrations. In 2020, the pollution was primarily concentrated in northern, central, and eastern China, with the highest annual average concentration of 815.91 pg/m 3 in Shanghai. Beijing experienced the most significant seasonal increase, with PBM 2.5 concentrations rising by 146.92 % from summer to winter. Nationally, the annual average PBM 2.5 pollution decreased extensively and markedly from 2015 to 2020. The non-carcinogenic risk of PBM 2.5 alone was negligible in 2020, with HQ values generally <0.02 in winter. This study may provide an important assessment of the effectiveness of China's measures against mercury pollution and offer valuable insights for future prevention and control of PBM 2.5 pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To identify the spatial clustering and its temporal trends among newly reported HIV/AIDS cases in Henan Province during 1995-2020, and to provide evidence for strategies on prevention and control of the disease. Methods: Information about newly reported HIV/AIDS cases in Henan between 1995 and 2020 were obtained from China Information System for Disease Control and Prevention and to describe their demographic characteristics, spatial autocorrelation and changing trends. This program was conducted at county level, using the ArcGIS 10.2. Results: A total of 96 528 HIV/AIDS cases with complete current address information in counties (districts) were newly reported during 1995-2020 in Henan, and the spatial autocorrelation analysis showed that Global Moran's I index was 0.249, Z G value of the Global Getis-Ord G coefficient was 6.472 (all P <0.001), indicating that there was a high clustered positive spatial autocorrelation of HIV/AIDS. The newly reported HIV/AIDS cases from 1995 to 2000, 2001 to 2005, 2006 to 2010, 2011 to 2015, and 2016 to 2020 in Henan Province all exhibited high values of global spatial clustering. Their Moran's I indices were 0.197, 0.103, 0.491, 0.411 and 0.383, respectively. The Z G values of the Global Getis-Ord G coefficient were 4.580, 3.386, 10.246, 8.378 and 8.093, respectively. All of global spatial correlation were statistically significant (all P <0.001). The results of local spatial autocorrelation analysis showed that newly reported HIV/AIDS cases in Henan Province had high-high clustering areas at each time stage mentioned above. The number of high-high clustering counties/districts gradually increased from 6 in 2001-2005 to 21 in 2016-2020, spreading from Zhumadian City and Zhoukou City in southeast Henan to Nanyang City in southwest Henan, Zhengzhou City and its surrounding counties/districts in central Henan. Conclusions: In Henan Province, an increasing trend of clusters appeared on HIV epidemic among newly reported HIV/AIDS cases from 1995 to 2020, and high-high clustering areas gradually expanded from Zhumadian City and Zhoukou City to Nanyang City, Zhengzhou City and its surrounding counties/districts, indicating that it is necessary to strengthen the AIDS prevention and control programs in these areas in Henan.

The Chang-Zhu-Tan ecological Green Heart area is the largest urban agglomeration Green Heart area in China. To clarify the spatiotemporal changes and driving factors of net primary productivity （NPP） of vegetation in the Chang-Zhu-Tan Green Heart area, an improved Carnegie Ames Stanford Approach （CASA） model was used to estimate the monthly vegetation NPP from 2011 to 2020 based on measured and remote sensing data. With the help of ArcGIS 10.2 software, linear regression and spatial partial correlation analysis were used to explore the spatiotemporal variations in monthly vegetation NPP and its responses to climate and terrain factors. The results showed that the monthly vegetation NPP in the Chang-Zhu-Tan Green Heart area showed an overall trend of first increasing and then decreasing, with an average vegetation NPP growth rate （measured in C, the same below） of 5.75 g·（m 2 ·month） -1 from January to July and a monthly decrease rate of 2.64 g·（m 2 ·month） -1 from August to December. The spatial distribution of monthly vegetation NPP in the Green Heart area showed a significant difference, with a coefficient of variation ranging from 34.52% to 48.76%. The high values of vegetation NPP in each month were concentrated in the ecological core areas of the central and eastern parts in the Green Heart area, whereas the low values were mainly distributed along the Xiangjiang River in the western part and in the narrow and elongated areas in the southern part of the Green Heart Area. The impact of climate and terrain factors on the monthly NPP of vegetation in the Green Heart area had both positive and negative inhibitory effects. Among climate factors, solar radiation was the major controlling factor for monthly vegetation NPP changes. The impact of terrain factors on vegetation NPP was relatively weak, with slope orientation having a greater positive impact on vegetation NPP than altitude and slope.

Sichuan Province is widely recognized as a highly representative and complex geomorphic region, where the structural contradiction of the ecological environment is prominent. The in-depth study of the spatio-temporal differentiation characteristics and identification of the driving mechanism of ecological vulnerability from a spatial differentiation perspective in Sichuan Province is of great importance to the regional ecological environment management and protection. Here, the Sichuan Province was selected as the research area and 15 indicators from the natural and social environment aspects were used to establish an evaluation system based on the "sensitivity-recovery-pressure" framework. The spatio-temporal differentiation characteristics of the ecological vulnerability in the study area were comprehensively analyzed by spatial principal component analysis, spatial autocorrelation, and optimal parameters-based geographical detector. Additionally, the driving mechanism behind the spatial differentiation of ecological vulnerability was revealed through the optimization of continuous variable discretization. The results showed that： ① From 2000 to 2020, a gradual decrease was observed in the ecological vulnerability index from 0.422 to 0.398, suggesting an overall upward trend in the ecological environment. The general ecological vulnerability level was moderately fragile, with a slightly better trend over time. A distinct pattern of "high in the east and low in the west," was observed indicating significant regional differences. ②The spatial pattern of ecological vulnerability in the Sichuan Province remained relatively stable and exhibited strong spatial agglomeration characteristics. High-high clustering areas were mainly distributed in the rapid development of urbanization and densely populated eastern region and low-low clustering areas were primarily distributed in the western, northwestern, and southwestern regions with a good ecological environment and a sparse population. ③The major driving factors of ecological vulnerability were land use, habitat quality, and biological abundance in Sichuan Province. Interactions among these factors amplified their impact on ecological vulnerability. Consequently, ecological vulnerability was the result of the combined effects of various factors, requiring the implementation of customized strategies for the protection and management of the ecological environment.

The neurotoxin β-N-methylamino-L-alanine (BMAA) has been widely detected in aquatic environments and got the public's attention due to its potential risk to human neurodegenerative diseases. Three cruises in spring, summer and autumn seasons were carried out in Laizhou Bay (LZB), Sishili Bay (SSLB), Sanggou Bay (SGB), Jiaozhou Bay (JZB) and Haizhou Bay (HZB) in 2023. Results showed that the temporal distribution pattern of BMAA in plankton varied in the survey bays. In LZB, the highest average concentration of BMAA in phytoplankton occurred in spring. The highest average concentration of BMAA in phytoplankton was detected in summer in SSLB, JZB and HZB. However, BMAA was only detected in phytoplankton at the R2 station in SGB in spring. The highest average concentration of BMAA in zooplankton was observed in spring in LZB, SSLB and SGB. Zooplankton accumulated the highest average concentration of BMAA in JZB and HZB in summer and autumn, respectively. The BMAA was widely detected in marine mollusks throughout the investigative period. In addition, Mantel test and RDA analysis results indicated that DIN/DIP strongly impacted on the spatiotemporal distribution of BMAA in phytoplankton, in JZB and SSLB. The spatiotemporal distribution of BMAA in plankton was correlated with temperature and DO in JZB. More field cruises should be conducted to explore the environmental drivers of the neurotoxin BMAA in marine ecosystems in future studies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study aimed to analyze the epidemiological characteristics and spatiotemporal clustering of hepatitis A in mainland China from 2004 to 2019 and to evaluate the practical impact of integrating hepatitis A vaccines into the Expanded Program on Immunization (EPI). Spatial and temporal autocorrelation and spatiotemporal scanning statistics were used to perform spatial and temporal characterization to quantify the spatial similarity or degree of aggregation of geographic data, and Geographical and Temporal Weighted Regression (GTWR) models were used to reveal spatial and temporal heterogeneity in the relationships between variables to test for spatial and temporal outbreaks of disease and other factors, such as socio-economic factors. Spatially, the incidence rates exhibited a west-high and east-low spatial differentiation, with the High-High (HH) clusters predominantly located in the western regions, maintaining stability butgradually diminishing. Hepatitis A prevalence peaked during the initial study period (2004-2008) showing significant spatial clustering. However, since the inclusion of hepatitis A vaccine in the immunization program in 2008, the incidence rates of hepatitis A in mainland China significantly decreased demonstrating the positive impact of immunization strategies. In addition to the effects of vaccination, socio-economic factors such as education level, water resources and age groups showed significant associations with hepatitis A incidence rates. Increased vaccine coverage and improved social conditions are crucial for controlling hepatitis A in China.