Search Results (123)

Soil metal contamination poses potential risks to ecosystem health, yet its vertical distribution and impacts on microbial communities in protected wildlife habitats remain poorly understood. This study investigated the vertical variation (0–80 cm) in seven metals or metalloids (Zn, Cr, Cu, Co, Ni, As, and Pb) and their correlations with soil bacterial communities in the Chinese Changxing Alligator Nature Reserve, Zhejiang Province, China. Soil samples were collected from two functional zones—the Reserved Breeding Zone (FY) and Reintroduction Zone (FG)—at four depth intervals. The results revealed distinct vertical stratification for both soil elements (metals and metalloids) and bacterial communities. Soil element concentrations exhibited depth-dependent variations, with surface layers showing higher accumulation of Zn, Ni, Cu, Cr and Pb, while As was enriched in deeper horizons. Bacterial alpha diversity declined with depth, and community composition shifted markedly: Pseudomonadota and Actinomycetota dominated surface soils, whereas Acidobacteriota and Chloroflexota increased in deeper layers. Network analysis revealed that microbial co-occurrence network complexity decreased with soil depth, indicating greater stability and environmental adaptability of surface soil microbial communities. Pearson correlation and Mantel analyses revealed significant depth-related variation in soil element concentrations (Zn, Co, Ni, Cu, Pb, Cr, and As), and these patterns were closely associated with shifts in soil bacterial community structure. This study provides systematic evidence of vertical differentiation in soil element–microbe interactions within reserve soil profiles, offering a scientific basis for habitat quality assessment, ecological risk warning, and Chinese alligator habitat conservation and management. Full article

HY–4A is China’s first ocean salinity remote-sensing satellite, launched into orbit in November 2024 and currently in operational service. The LASMR (L-Band Aperture Synthesis Microwave Radiometer) is the L-band synthetic aperture radiometer onboard the HY–4A satellite. This study validates the LASMR Level-2 SSS (sea surface salinity) product using in situ salinity observations from Argo floats, covering the period from November 2024 to December 2025. Global analysis indicates that the LASMR SSS retrieval uncertainties show a distinct zonal distribution, which primarily reflects the impact of sea surface temperature (SST) and sea surface wind speed on SSS retrieval accuracy. A lower SST reduces the sensitivity of brightness temperature (TB) to SSS variations, and a high wind speed degrades the sea surface roughness correction. Both factors lead to increasing uncertainties in SSS retrieval. Furthermore, atmospheric parameters including water vapor content and precipitation also affect the SSS retrieval uncertainty. The influence of water vapor may originate from its coupling with SST/wind speed and inherent uncertainties in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The effect of precipitation is more complex: it increases ocean TB through rain-induced surface freshening and additional rain-induced roughening, which aliases into the satellite signal. Moreover, precipitation-enhanced vertical salinity gradients amplify the vertical representativeness error arising from the depth difference between satellite sensing and Argo measurements. Meanwhile, impacted by land brightness temperature contamination and radio-frequency interference (RFI), the SSS retrieval accuracy of HY–4A decreases significantly in coastal waters compared with the open ocean. Since the traditional buoy–satellite dual-matching method tends to overestimate uncertainties in satellite data, an Argo/HY–4A/SMAP (Soil Moisture Active Passive) triple-collocation dataset is used to estimate the LASMR SSS retrieval uncertainties. The triple-collocation method yields robust uncertainty estimates for both satellites (HY–4A and SMAP) over the global ocean and high-salinity-variability regions. In conclusion, the global uncertainty of the HY–4A LASMR SSS product is 0.35 psu. These results provide a reference for future product refinement and improvements in HY–4A SSS retrieval algorithms. Full article

Coastal wetlands are important sinks for heavy metals, yet the linkage between vertical redistribution, quantitative source contributions, and ecological–health risk drivers remain insufficiently understood. This study collected the stratified sediment samples from three depth intervals (0–20, 20–40, and 40–60 cm) from 28 representative sites in the coastal wetlands of western Bohai Bay, and evaluated the spatial distribution, vertical variation, pollution status, potential sources, and ecological–human health risks of eight heavy metals (Cr, Ni, Cu, Zn, As, Cd, Hg, and Pb). The mean concentrations were below the Class I limits of the Marine Sediment Quality Standard. Most metals were close to or slightly below regional background values, whereas Cu and As showed mild enrichment and Cr was higher than values reported for Bohai Bay and Hangzhou Bay. Vertical profiles were generally homogeneous, with weak enrichment of specific metals, probably due to sediment resuspension, tidal disturbance, and bioturbation. Pollution assessment based on the geoaccumulation index (Igeo), Nemerow pollution index (P_N), and pollution load index (PLI) consistently indicated low contamination levels, with Hg and Pb as the main contributors to the regional pollution load. Source apportionment indicated that heavy metals were jointly influenced by lithogenic background (38.9%), atmospheric deposition (31.1%), and local anthropogenic activities (30.0%). Ecological risk assessment showed that the integrated risk index (RI) remained within the low-risk category, although Hg consistently fell within the moderate-risk range and Cd approached the moderate-risk threshold. Health risk assessment showed that both non-carcinogenic and carcinogenic risks were within acceptable limits for all receptor groups. Children had higher risks in core residential areas, whereas adults showed higher risks in non-core industrial–agricultural zones because of increased exposure frequency. The source–risk analysis indicates that non-carcinogenic risk is mainly associated with background-derived Cr, whereas carcinogenic risk is primarily linked to anthropogenic As inputs. These findings indicate that source contributions and risk contributions are not necessarily consistent, highlighting the need for source-oriented risk management in industrialized coastal wetlands. Full article

To address the inefficiency of demolition robots at nuclear contamination sites due to frequent retreats to safe zones for attachment replacement, this study develops and experimentally evaluates a six-wheeled mobile platform for attachment-replacement support near the work area. Structurally, the prototype adopts a well-established passive rocker-bogie suspension architecture combined with six-wheel independent drive. The focus of this work is not to claim a new suspension topology, but to evaluate its engineering feasibility and drive-load margins for a heavy-duty nuclear support platform through multibody simulation and onboard-sensor measurements. A constrained multibody model was implemented in ADAMS/Simulink to represent rocker joints, wheel revolute joints, actuator limits, and wheel–ground contact. A full-scale prototype was tested on representative nuclear-facility terrain conditions, including a 20° slope and a 250 mm vertical step. The results show that the prototype completed both tests while the measured motor torques remained within the allowable drive range. The positive and negative torque signs observed on the left and right sides are explained by mirrored motor installation and coordinate definitions rather than by a special torque-distribution mechanism. This study provides a structural selection and experimental performance reference for mobile operation support in radiation environments. Full article

Heavy metal pollution poses a significant threat to industrial and agricultural ecosystems; however, thorough research on the coupled risks and migration mechanisms of heavy metals within soil-groundwater systems in arid-region industrial parks remains limited. This study systematically collected 312 surface soil samples and 239 groundwater samples from typical chemical industrial parks in Xinjiang, northwestern China. The pollution levels of six typical heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) were quantitatively evaluated utilizing the Single Pollution Index (P_i), Nemerow Pollution Index (P_N), and Potential Ecological Risk Index (RI) for soil and the improved Heavy Metal Contamination Index (HCI) for groundwater. Additionally, GIS mapping and the Positive Matrix Factorization (PMF) model were integrated to delineate spatial distributions and primary emission sources. The assessment results indicated overall moderate pollution risks for Cd, Cu, and Ni in the soil, and for Cd, Pb, Cr, and Ni in the groundwater. Notably, Cd emerged as the primary risk contributor across both media. The RI identified Cd as the element posing the highest soil toxicity risk (with a mean RI of 53.57), while the HCI revealed that specific industrial zones face severe contamination levels (HCI > 4500), predominantly driven by Cd and Pb. GIS analysis illustrated a distinct distance–decay diffusion pattern emanating from industrial point sources. Crucially, PMF source apportionment demonstrated divergent contamination pathways: surface soil heavy metals (e.g., Cr, Cu, Pb, Zn) were primarily governed by top-down local industrial emissions (52.5%), whereas groundwater contamination was largely dictated by regional groundwater flow carrying mixed agricultural and natural geogenic inputs (75%). Furthermore, Pearson correlation analysis revealed a prevalent weak or negative correlation between heavy metal concentrations in the two media, suggesting a spatial “decoupling” of their contamination pathways. This phenomenon is likely driven by a dynamic “retention-leaching” mechanism within the arid vadose zone, where alkaline pH and high clay content act as a hydrochemical barrier impeding vertical migration. These findings underscore that soil and groundwater in arid industrial regions should be managed as distinct hydrochemical systems, providing a robust scientific basis for targeted remediation and the sustainable redevelopment of industrial brownfields. Full article

Heavy metal (HM) contamination in urban soils is a pressing global issue, particularly in rapidly industrializing regions like Kazakhstan, where anthropogenic activities such as transportation, energy production, and manufacturing exacerbate accumulation in ecosystems. In Almaty, the largest city in Kazakhstan, urban expansion and legacy pollution pose risks to soil functions, biodiversity, and public health through bioaccumulation and migration pathways. This study evaluates the spatial distribution and ecological impacts of total heavy metal concentrations (HMs) (Pb, Cd, As, Zn, Cu, Ni, Co, Mo, Mn) in Almaty’s soils to inform remediation strategies. Soil samples (n = 73) were collected using a systematic grid sampling method across urban, industrial, and peri-urban zones in Almaty. HM concentrations were determined via X-ray fluorescence spectrometry (XRF) following GOST 33850-2016 standards. Pollution indices (contamination factor K_c and integrated pollution index Z_c) were calculated relative to Kazakhstani permissible limits (PDK RK) and Russian approximate permissible concentrations (ODK RF). Statistical analyses included Spearman’s correlation, boxplots, and coefficient of variation. Morphological, physicochemical (pH, humus content), and biological assessments evaluated degradation. Spatial interpolation via GIS mapped the hotspots. HM distributions showed significant variability, with As, Zn, and Ni exceeding norms in >90% of samples (median K_c ≈ 5 for As). Z_c classified >70% of sites as hazardous or extremely hazardous (Z_c > 32), with hotspots in central-eastern districts (Z_c 90–145). Strong correlations (ρ ≥ 0.6) identified a technogenic group (Pb–Zn–Cu–Ni) from traffic and industry, contrasting predominantly geogenic elements with possible anthropogenic contribution (As–Co–Mo–Mn). Pollution induced soil compaction, reduced humus/pH, and disrupting biogeochemical cycles. Local exceedances were noted near TECs, factories, and transport hubs. Almaty’s soils exhibit pervasive technogenic HM pollution, driven by urban sources, leading to ecosystem degradation and health risks. Future research should incorporate vertical profiling and isotopic sourcing for refined risk models. Prioritized monitoring and phytoremediation in hotspots are recommended to enhance resilience, aligning with UN SDGs for sustainable cities and ecosystems. Future research should incorporate vertical profiling and isotopic sourcing for refined risk models. Full article

To elucidate the pollution status and spatial distribution patterns of microplastics in representative deep-sea regions of China, the Qiongdongnan sea area has emerged as a key focus area for microplastic research. A comprehensive assessment of microplastic contamination across the water column (0–1500 m) was conducted using CTD-integrated water sampling coupled with 0.2 μm membrane filtration. Results revealed that polypropylene (PP), polyethylene (PE), and polyamide (PA) were the dominant polymer types. Granular microplastics constituted the overwhelming majority (95.3%) of identified particles, while size analysis showed that those in the 20–50 μm range accounted for the largest fraction (80.5%). The average microplastic abundance across all sampled depths was 3.47 particles/L. Comparative analysis with other prominent marine environments globally and domestically indicates minimal vertical differences in the characteristics of microplastics. Comparative analysis with other prominent marine environments globally and domestically indicates that microplastic pollution in the South China Sea is relatively moderate. This study delivers foundational empirical data critical for environmental risk assessment and source apportionment of microplastics in the South China Sea. This study provides key basic data for assessing the environmental risk of microplastics in the South China Sea and tracing their sources. Full article

Remote-sensing land surface deformation (LSD) is a powerful and effective approach for investigating regional alpine permafrost variations. However, alpine permafrost is often distributed in areas characterized by earthquakes, and the LSD of alpine permafrost is potentially contaminated or diminished by earthquake-related LSD. Therefore, this study aimed to derive the effective LSD in the alpine permafrost of the Source Area Yellow River (SAYR) by removing LSD originating from the M_w 7.4 Maduo earthquake in 2021-05-22 and analyzing the spatiotemporal variations in LSD during 2017–2024. Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) was used to obtain the initial LSD time series from Sentinel-1 images acquired during 2017–2024. The LSD of the M_w 7.4 Maduo earthquake, its aftershocks and the post-seismic relaxation in SAYR was simulated separately by considering its temporal process and removed from the LSD time series in SAYR. The final LSD was validated against in situ Global Navigation Satellite System (GNSS) measurements, and the spatiotemporal variations in LSD in SAYAR were subsequently analyzed. The study found the following: (1) the removal of the earthquake-related LSD was successful both spatially and temporally and the final LSD has mean absolute error (MAE) of 3.22 mm and root mean squared error (RMSE) of 3.92 mm; (2) during 2017–2024, the vertical LSD in SAYR was mostly −8–8 mm/y; (3) soil moisture determined the spatial distribution of the LSD direction in SAYR as a result of local drainage conditions, air temperature, precipitation and snow melt. This study demonstrated the necessity of removing the earthquake-related LSD when investigating the alpine permafrost LSD in tectonically active areas. The strategy adopted in this study serves as a technical reference for future investigations of this kind. The findings in this study provide insight for a thorough understanding of permafrost evolution on the Tibetan Plateau in the context of climate change. Full article

The aim of this study was to critically assess the usefulness of pollution indicators in monitoring riverside soils (fluvisols) for heavy metal content. A novel methodological approach was used, comparing areas located inside and outside flood embankments, which allowed for a precise determination of the impact of fluvial and anthropogenic processes on heavy metal accumulation. The experimental logic validated the usefulness of four indicators: the Individual Pollutant Index (PI), the Background Enrichment Factor (PIN), the Potential Ecological Risk (RI), and the Pollution Load Index (PLI). Comparative analysis revealed that soils within the embankment zone have higher metal concentrations, resulting from the continuous deposition of alluvial material, which often contains industrial and municipal pollutants. The vertical distribution of pollutants in fluvisols was shown to be closely related to sediment dynamics and soil properties (clay fraction, organic matter, redox conditions). Validation of the indicators revealed their varying sensitivity. The study revealed the limitations of the PLI, which, due to its summary nature, did not account for significant variability in contamination within the soil profile. Consequently, the PI, PIN, and RI indices were shown to be the most effective tools in assessing the actual degree of soil contamination by fluvisols in the middle Oder Valley. The study results emphasise the need for the selective selection of indicators in environmental monitoring. This comparative approach provides a reliable method for assessing the effectiveness of floodplain management strategies under exposure to chemical pressure. Full article

As a pivotal unit in water treatment, filters undergo significant media aging during long-term operation, altering their physicochemical properties and heavy metal accumulation behavior. This study investigated long-term operated filter sands from a rapid sand filter (RSF) and a traveling bridge sand filter (TBSF) at a drinking water treatment plant in Guangzhou. Characterization revealed that prolonged operation induced the formation of poorly crystallized Fe–Mn oxide coatings on sand surfaces. The RSF exhibited markedly higher heavy metal enrichment than the TBSF—with substantially more fine particles (+9.5%) and coarse particles (+4.7%)—attributable to its higher proportion of fine particles and greater treated water volume per unit media mass. Distinct vertical distribution patterns were observed; metal concentrations decreased with depth in the RSF, while the TBSF showed minimal variation. Sequential extraction according to the European Community Bureau of Reference indicated that heavy metals (excluding Fe and Ti) were predominantly present in the reducible and acid-soluble fractions, with the RSF showing a higher proportion of the reducible fraction. Although particle size significantly influenced accumulation levels, it did not affect metal speciation within the coatings. Citric acid soaking partially removed Mn, Ni, and Cd; however, the associated Mn loss may compromise the coating’s adsorptive capacity. This approach proved insufficient to fully mitigate contamination risk—particularly given that acid-soluble fractions were not reduced, and even increased for Cd in the RSF—thereby substantiating the scientific basis for replacing long-term operated filter sands. Full article

Microplastic (MP) contamination in terrestrial ecosystems has emerged as a critical environmental concern, particularly in agricultural soils influenced by anthropogenic activities. This study investigated the depth-wise distribution, polymer composition, and associated ecological and human health risks of MPs in homestead agricultural soils across four regions of Bangladesh representing different levels of industrialization: Narayanganj (old industrial), Savar (moderate industrial), Gazipur (emerging industrial), and Mymensingh (non-industrial). Soil samples were collected from two depth intervals (0–20 cm and 21–50 cm), and MPs were extracted using density separation, identified through microscopic analysis, and characterized via ATR-FTIR spectroscopy. A diverse range of MP morphologies and polymers was detected, with irregular particles and fragments dominating the composition. Polypropylene (PP), high-density polyethylene (HDPE), and polyethylene terephthalate (PET) were the most abundant polymers, reflecting widespread domestic, industrial, and agricultural plastic usage. MP abundance was consistently higher in surface soils, indicating dominant surface inputs, although vertical migration into subsoil layers was evident. Spatial analysis revealed higher MP contamination in industrial regions, particularly Narayanganj and Savar, compared to the non-industrial reference site. Ecological risk assessment indicated low risk levels across all regions; however, significant spatial variability was observed. Human exposure assessment demonstrated that inhalation was the primary pathway, followed by dermal contact and ingestion, with children exhibiting higher exposure levels than adults. Lifetime average daily dose (LADD) and carcinogenic risk estimates remained below acceptable thresholds, suggesting minimal immediate health risks. Nevertheless, the persistence, mobility, and cumulative nature of MPs highlight potential long-term concerns. Therefore, this study provides comprehensive insights into the sources, distribution, and risks of MPs in homestead agricultural soils and underscores the need for improved waste management practices, sustainable agricultural strategies, and long-term monitoring to mitigate environmental and human health impacts. Full article

Microplastics (MPs) are emerging pollutants of global concern, posing significant ecological and human health risks. They are frequently detected in stormwater systems, with urban runoff serving as a major transport pathway into the environment. Green stormwater infrastructure, particularly bioretention systems (BRSs), offers a promising approach to mitigate these risks by filtering and retaining various contaminants. However, the occurrence of MPs in BRSs and their capacity to retain these pollutants remain largely unexplored in the literature, despite being critical for stormwater management and water quality protection. Therefore, this study attempted to examine the occurrence, vertical distribution, and trapping of MPs within a field-installed BRS, potentially emphasizing their role in reducing microplastic (MP) transport. Therefore, field samples were collected at depths of 2, 12, and 24 inches below the surface and processed in the laboratory for MP detection and quantification. The results revealed an average concentration of 1095 particles per kg of dried sediment, with fragments (microplastics shape) accounting for 78.54% of the total MPs. Although no clear vertical distribution pattern was observed, the initial findings showed that MPs were mostly retained at 24 inches, potentially indicating their transport through the media and the retention capacity of a BRS (surface and middle layer) in capturing microplastics from stormwater environments. However, there is no direct evidence to explain the mechanisms driving the observed concentrations at greater depths. The preliminary findings of this study highlight that the concentrations of different sizes of MPs can vary with soil depth in bioretention media. Integrating a BRS into urban stormwater infrastructure likely provides the dual benefits of improved stormwater management and reduced plastic pollution. This study underscores the importance of optimizing bioretention design and media composition to enhance MP trapping from stormwater. Full article

The expansion of organic farming in Europe increases the co-occurrence of medicinal and aromatic plant crops and pyrrolizidine alkaloid (PA)-producing weeds, raising serious contamination concerns. This study evaluated the risk of PA contamination in organically grown chamomile (Matricaria recutita L.) under field conditions in the North Vidzeme region of Latvia, with particular emphasis on vertical PA distribution in dominant weeds and on whether PA occurrence could be detected in chamomile plants growing adjacent to PA-producing weeds under field conditions. Three commercial fields were surveyed using systematic quadrat sampling to quantify weed density, biomass, and height. PA-producing weeds were segmented into 5 cm fractions, and pyrrolizidine alkaloids were quantified by LC-HRMS. Myosotis arvensis was the dominant species (up to 48,000 plants ha⁻¹), contributing the highest field-level PA load (up to 669.3 mg ha⁻¹), whereas Anchusa arvensis occurred at lower densities (≤2400 plants ha⁻¹) with a total PA load of 104.8 mg ha⁻¹. In both species, PA concentrations increased toward upper plant segments, while contamination hazard at harvest was determined by the amount of PA-bearing biomass in the harvest-relevant zone. No PAs were detected in chamomile samples collected within 10 cm of PA-producing weeds (<LOQ). Under the investigated conditions, contamination hazard was primarily associated with mechanical admixture during harvest rather than soil-mediated transfer. Full article

The combined effects of organic pollutants and vertical soil gradients on microbial community assembly in long-term contaminated sites remain insufficiently understood. In this study, high-throughput sequencing was employed to characterize prokaryotic communities across depth-resolved soil profiles at a contaminated site in Tianjin, China. Microbial diversity, taxonomic composition, and predicted functional traits varied significantly with soil depth and pollutant distribution. Surface soils exhibited higher richness and diversity, with Shannon, Sobs, and PD indices decreasing with depth (p = 0.020, p = 0.002, and p < 0.001, respectively). Redundancy analysis showed that the first two axes explained 89.91% of the total variance, indicating strong associations between microbial community structure and environmental variables. Community differentiation was related to pollutant type, with aromatic hydrocarbons more strongly linked to surface assemblages and chlorinated compounds associated with deeper horizons. Although the overall abundance of predicted metabolic genes decreased with depth, the distribution of major functional categories, including pathways related to organic matter degradation, remained comparatively stable. Co-occurrence network analysis revealed a progressive decline in network connectivity and complexity along the vertical gradient, with the number of edges decreasing from 853 (L1) to 447 (L3) and average degree decreasing from 16.404 to 9.122. These findings highlight depth-related environmental filtering as a key mechanism structuring microbial communities under long-term organic contamination and provide a scientific basis for optimizing depth-specific in situ bioremediation strategies, such as targeting aromatic hydrocarbon degradation in surface soils and chlorinated compound remediation in deeper layers. Full article

Using perfluorooctanoic acid (PFOA) as a representative highly mobile solute to isolate hydrological controls, we investigated how slope influences the partitioning of vertical and lateral transport pathways. While vertical percolation has been widely examined using conventional column leaching tests, lateral transport driven by topographic gradients remain insufficiently quantified under controlled conditions. Here, laboratory-scale inclined leaching experiments were conducted to resolve the distribution of solute transport among vertical leachate, lateral runoff, and solid-phase retention under systematically varied slope angles (0°, 4°, 9°, and 20°), flow regimes, and leaching volumes. Results show that solute migration shifted from vertical-dominated transport under flat conditions (91% at 0°) to lateral-dominated export at moderate slopes, with lateral pathways accounting for up to 75% of the recovered mass at 9°. This pathway shift was well described by an exponential partitioning model, f₁(α) = f_max (1 − e^−kα), where f_max = 0.80 and k = 0.34°⁻¹ (R² = 0.97), indicating a critical crossover threshold at approximately 4° slope. Flow regime interacted with slope angle to modulate lateral transport efficiency: slower flow enhanced lateral export at moderate slopes, whereas faster flow promoted peak lateral transport under steeper conditions. In contrast, solid-phase retention remained consistently low (5–9%) across all treatments, indicating that the observed redistribution patterns were primarily governed by hydrological pathway partitioning rather than sorption processes. These results demonstrate that even modest topographic gradients can fundamentally alter solute transport pathways in sloped soils. The slope-dependent pathway partitioning framework developed here provides a process-based basis for incorporating lateral transport into hillslope hydrological models and for improving assessments of contaminant redistribution in both managed and natural landscapes. Full article