Effects of different water and fertilizer treatments on the matrix properties and plant growth of tailings waste.

Vegetation ecological restoration technology is widely regarded as an environmentally sustainable and green technology for the remediation of mineral waste. The appropriate ratio of amendments can improve the substrate environment for plant growth and increase the efficiency of ecological restoration. Herbs and shrubs are preferred for vegetation restoration in abandoned mines because of their rapid establishment and easy management.

Trajectories of Nutritional Quality, Diet-Related Environmental Impact, and Diet Cost in China: How Much Does Ultra-Processed Food and Drink Consumption Matter?

Background: Rapid socio-economic developments confront China with a rising consumption of ultra-processed foods (UPFs) and ultra-processed drinks (UPDs). This study aims to evaluate their potential impact on diet transformation towards sustainability including nutrition, environmental sustainability, and diet-related cost.

Methods: Dietary intake was assessed by 24 h recalls in 27,311 participants (age: 40.

Rare earth elements in the Yellow River estuary, China: Composition, distribution, and pollution insights.

Rare earth elements (REE) are emerging aquatic trace pollutants. A total of 191 sediment samples were analyzed from the Yellow River estuary to study the REE geochemical behavior and environmental impact. The results showed that the samples contained high REE levels, and the average total amount of REE was 195.

Effect and mechanism of the moisture content on the kinetic retardation of LNAPL pollutant migration by the capillary zone.

Light nonaqueous-phase liquids (LNAPLs) are the main source of organic pollution in soil and groundwater environments. The capillary zone, with varying moisture contents, is the last barrier against the infiltration of LNAPL pollutants into groundwater and plays an important role in their migration and transformation. However, the effect and mechanism of the moisture content in the capillary zone on LNAPL pollutant migration are still unclear.

Experimental and modeled analysis of contaminant mobility in coal fly ash landfills under continuous rainfall regimes.

In China, a significant amount of coal fly ash is stored or used for landfill reclamation. The contaminants in coal fly ash (CFA) leachate can cause regional soil and groundwater contamination during long-term storage. This paper focuses on a coal gangue comprehensive utilisation power plant in Fenyang City, Shanxi Province, China, where the leaching characteristics of CFA were investigated by leaching tests.

Using machine learning to predict selenium content in crops: Implications for soil health and agricultural land utilization in longevity regions.

Selenium (Se) is an indispensable trace element to human health, yet its biological tolerance threshold is relatively narrow. The potential application of machine learning methods to indirectly predict the Se content in crops across regional areas, thereby validating the reasonableness of soil health thresholds, remains to be explored. This study analyzed the factors influencing Se absorption in crops from longevity regions and employed machine learning models to predict the bioconcentration factor of Se, thereby obtaining selenium content in these crops and ultimately estimated the Se threshold for healthy soils.

[Prediction of potential geographic distribution of in Yunnan Province using random forest and maximum entropy models].

Objective: To predict the potential geographic distribution of in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into surveillance and control in Yunnan Province.

Methods: The snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population).

Health Risk of Heavy Metal and Implication for Ecological Threat in Soils Weathered from the Black Shale.

Heavy metals were analyzed in rhizosphere soils and rice grains collected from typical black shale areas. The concentrations of As, Cd, Cu, and Zn in the rhizosphere soil exceeded the current soil environmental quality standards. Cd exhibited the highest bioaccumulation capacity, with 45% of rice grains exceeding food safety limit.

Soil total nitrogen content and pH value estimation method considering spatial heterogeneity: Based on GNNW-XGBoost model.

Soil nitrogen content and pH value are two pivotal factors that critically determine soil fertility and plant growth. As key indicators of soil health, they each play distinct yet complementary roles in the soil ecosystem. Nitrogen is one of the essential nutrients for plant growth, while soil pH directly influences the activity of soil microorganisms.

Heavy metals impact environmental capacity of oasis soils in Qinghai-Tibet Plateau dry zone.

The Tibetan Plateau is known as the "third pole of the world," and plateau oases are a key component of plateau ecosystems. Under natural conditions, the ecosystems on the Tibetan Plateau contain relatively low levels of heavy metals. However, the overexploitation of resources by humans for production and living has affected the quality of soils in the Qinghai-Tibet region, whereby the environmental capacity is decreasing.

Integrating spatial clustering and multi-source geospatial data for comprehensive geological hazard modeling in Hunan Province.

This study presents an integrated framework that combines spatial clustering techniques and multi-source geospatial data to comprehensively assess and understand geological hazards in Hunan Province, China. The research integrates self-organizing map (SOM) and geo-self-organizing map (Geo-SOM) to explore the relationships between environmental factors and the occurrence of various geological hazards, including landslides, slope failures, collapses, ground subsidence, and debris flows. The key findings reveal that annual average precipitation (Pre), profile curvature (Pro_cur), and slope (Slo) are the primary factors influencing the composite geological hazard index (GI) across the province.

Geographical impact on the distribution of polycyclic aromatic hydrocarbons (PAHs) in hilly terrain topsoil: A case study at Chongqing, SW, China.

The distribution and transport of polycyclic aromatic hydrocarbons (PAHs) in urban environments are influenced by both anthropogenic sources and natural landscape features. While previous research has primarily focused on human activities as drivers of PAH pollution, the role of terrain-especially in cities with complex topographies-remains underexplored. To investigate the effect of terrain features on PAH distribution and transport, we analyzed topsoil samples evenly distributed in Chongqing, a city with hilly terrain (elevation: 48-2300 m).

Lightweight Deep Learning Model, ConvNeXt-U: An Improved U-Net Network for Extracting Cropland in Complex Landscapes from Gaofen-2 Images.

Extracting fragmented cropland is essential for effective cropland management and sustainable agricultural development. However, extracting fragmented cropland presents significant challenges due to its irregular and blurred boundaries, as well as the diversity in crop types and distribution. Deep learning methods are widely used for land cover classification.

InSAR-YOLOv8 for wide-area landslide detection in InSAR measurements.

InSAR monitoring technology is widely used in investigating landslide hazards. Leveraging object detection algorithms to quickly extract landslide information from Wide-Area InSAR measurements is of great significance. Our InSAR-YOLOv8, an algorithm that automatically detects landslides from InSAR measurements, addresses the low accuracy and suboptimal detection performance of existing network models.

Weighted comprehensive risk assessment and pollution analysis of long-term printing and dyeing sludge landfills in an industrialized Chinese city.

Sludge landfilling is widely used in China, accounting for approximately 65% of total sludge disposal, due to its simplicity and cost-effectiveness. However, with increasing land scarcity and stricter environmental regulations, the Chinese government has emphasized reducing sludge landfilling. Despite these efforts, sludge historically disposed of in landfills continues to pose risks, including heavy metal leaching and contamination of groundwater and soil.

Association between urinary phthalate metabolites and sarcopenia in US adults from NHANES 2011-2018.

Background: Phthalates, widely used as chemical additives, are often found as mixtures in the environment. However, the combined impact of phthalate exposure on sarcopenia remains unclear.

Objective: This study aimed to investigate the relationships between phthalates and sarcopenia in adults.

Speciation and historical invasions of the Asian black-spined toad (Duttaphrynus melanostictus).

Animal translocations provide striking examples of the human footprint on biodiversity. Combining continental-wide genomic and DNA-barcoding analyses, we reconstructed the historical biogeography of the Asian black-spined toad (Duttaphrynus melanostictus), a toxic commensal amphibian that currently threatens two biodiversity hotspots through biological invasions (Wallacea and Madagascar). The results emphasize a complex diversification shaped by speciation and mitochondrial introgression that comprises two distinct species.

Anthropogenic Drivers of Small-Island Effects in Urban Remnant Woody Plants.

The positive relationship between species richness and area is a fundamental principle in ecology. However, this pattern deviates on small islands, where species richness either changes independently of area or increases at a slower rate-a phenomenon known as the Small-Island Effect (SIE). While the SIE has been well documented in natural ecosystem, its presence in highly fragmented and disturbed urban ecosystem remains unexplored, posing challenges for urban vegetation conservation.

Planted Citrus Regulates the Community and Networks of -Harboring Bacteria to Drive Phosphorus Availability Between Karst and Non-Karst Soils.

The phosphorus (P) availability in soils is influenced by microbes, particularly those containing the gene responsible for phosphate solubilization. The present study investigated the community structure, diversity, and co-occurrence networks of -harboring bacteria in karst and non-karst citrus orchard soils across a planting duration gradient, natural forests, and abandoned land, as well as the soil total P (TP) and available P (AP) contents and enzyme activities. The soil AP contents were lower in the karst regions than in the non-karst regions, while the soil organic carbon (C; SOC), exchangeable calcium, and microbial biomass nitrogen (N) contents; alkaline phosphatase (ALP) and β-Glucuronidase activities; and pH had the opposite trends.

Larval Feeding Habits of Five Firefly Species Across Aquatic, Semi-Aquatic, and Terrestrial Lineages.

While adult fireflies are terrestrial, their larvae inhabit various habitat types, and a lack of comprehensive research on the feeding habits of these larvae across different habitats has greatly impeded the development of artificial diets. Here, we tested 14 types of foods, primarily covering gastropods, vertebrates, and fruit, to survey feed for aquatic ( and ), semi-aquatic ( and sp.), and terrestrial () fireflies.

Status of a New Model of ERCP Training in China: A Nationwide Survey of Standardized Training for ERCP Procedure (STEP) Programs.

Aims: ERCP training should adapt to the rapid development of ERCP technology and indications. China has a large population and vast land area, but ERCP training resources are insufficient. To make effective use of scarce ERCP training resources, the Standardized Training for ERCP Procedure (STEP) program was launched as a pilot trial.

BO-CNN-BiLSTM deep learning model integrating multisource remote sensing data for improving winter wheat yield estimation.

Introduction: In the context of climate variability, rapid and accurate estimation of winter wheat yield is essential for agricultural policymaking and food security. With advancements in remote sensing technology and deep learning, methods utilizing remotely sensed data are increasingly being employed for large-scale crop growth monitoring and yield estimation.

Methods: Solar-induced chlorophyll fluorescence (SIF) is a new remote sensing metric that is closely linked to crop photosynthesis and has been applied to crop growth and drought monitoring.

Monitoring and discussion on river carbon and nitrogen fluxes in the Pearl River Estuary region.

Rivers link land and sea, playing an important role in the global carbon and nitrogen cycles. By conducting surveys and research on river flow in a specific region, we can gain a better understanding of the nitrogen and carbon sinks in the area and their contributions to the environment. In this study, we conducted bi-annual sampling and monitoring of river flow in the Pearl River Delta downstream of Zhuhai, China, and collected hydrological information.

Enhanced risk assessment framework integrating distribution dynamics, genetically inferred populations, and morphological traits of lizards.

Assessing the threat status of species in response to global change is critical for biodiversity monitoring and conservation efforts. However, current frameworks, even the IUCN Red List, often neglect critical factors such as genetic diversity and the impacts of climate and land-use changes, hindering effective conservation planning. To address these limitations, we developed an enhanced extinction risk assessment framework using lizards as a model.