Campylobacter, non-typhoidal Salmonella, Shigella, Cryptosporidium, and Giardia are responsible for ~1 million domestically acquired waterborne illnesses annually in the United States. The contribution of private well water and underlying geology to these infections has been underexplored. The objectives of this research were to (1) determine whether enteric disease cases in Pennsylvania cluster in time and space; and (2) determine whether enteric disease cases are associated with private well water and karst geology. Confirmed cases of Campylobacter, non-typhoidal Salmonella, Cryptosporidium, and Giardia from 2010 to 2019 in Pennsylvania were analyzed. Spatial clusters were identified using a Poisson-based spatial scan statistic (SaTScan), and temporal patterns were examined using the R package Model Temporal Trends. Zero-inflated negative binomial model regression with county-level random intercepts examined associations between disease incidence, private well usage, and karst geology. All four pathogens had significant clusters of illness in time and space. Cryptosporidium, Giardia, and Campylobacter cases were significantly associated with areas served by private wells (P < 0.05; P < 0.001), and cases of Cryptosporidium and Campylobacter were associated with karst geology (P < 0.01). This novel investigation adds to a growing body of evidence that private well water is a risk factor for enteric disease. Public health interventions should target the management of private well water to reduce the burden of disease globally, particularly in communities not serviced by public water supplies.
Radon is a naturally occurring radioactive gas that poses environmental and health concerns, particularly in regions characterized by uranium-rich geological formations and active fault systems that facilitate its migration from the subsurface into soil gas and near-surface environments. In the Eastern Cordillera of the Central Andes, southern Peru, uranium-bearing deposits intersected by geological faults create favorable conditions for elevated radon concentrations in the soil gas and near-surface environment, due to increased permeability that enhances upward transport. However, lack of systematic data on radon concentrations in these areas has limited development of a national radon framework and constrained regional assessments. This study establishes baseline concentrations of soil gas radon (Rn-222) in faulted and uranium-bearing zones of the Eastern Cordillera. Sixteen measurement sites were surveyed across key geological units, integrating lithogeochemical analyses of uranium in rock samples with in-situ radon measurements. Results reveal spatial variability, with soil gas radon concentrations reaching up to 567 kBq/m3, including high values in structurally controlled zones despite relatively low uranium content (23 ppm). These findings demonstrate that, while uranium-rich lithologies act as primary radon sources, fault-controlled permeability and fracture networks exert dominant control on radon migration. By integrating geological, geochemical, and radon data, this study provides a framework for radon mapping in Peru. Results highlight role of structural geology in radon distribution and support soil gas radon as indicator of uranium mineralization and fault-related permeability. These insights contribute to improved radon assessment strategies and provide scientific basis for future development of a national radon potential map.
Methane released from the subseafloor is significantly attenuated during upward migration, yet the preservation of methane-derived organic carbon (OC) in global deep-sea sediments remains poorly understood. Here, we measured carbon isotopes coupled with temperature-ramped analyses on various methane seepage sediments. Our results reveal a correlation between the radiocarbon (14C) content in deep-sea surface sediments and sulfate-methane transition depth. Notably, our findings suggest that a substantial amount of 14C-depleted OC may originate from deep-seated methane and is efficiently preserved in surface seepage sediments. We propose that the efficient OC preservation is related to microbial-mediated aggregate formation at the seawater-sediment interface, where physical occlusion within coarse-grained matrices reduces oxygen availability and enhances OC stability. We estimate that at least 6 Tg C of methane-derived OC are preserved annually in surface sediments of the global continental slopes. This process may play a non-negligible role in OC preservation in sediments, reducing methane emission into the atmosphere.
Rockfalls are a destructive geo-hazard in Romania's steep environments that pose significant material damage and loss of life, even when involving small rock volumes, owing to their high mobility and unpredictability. This study presents the first national-scale assessment of rockfall potential occurrence in Romania, applying a multi-criteria statistical and geospatial analysis based on the Weight of Evidence method. By integrating 1,743 historical rockfall sites and 19 environmental variables as driving factors, we mapped and statistically assessed the potential rockfall distribution of their occurrence across the Carpathian and Subcarpathian regions. Findings reveal that over 18,000 km2 of Romanian territory is suitable for rockfall assessment, while approximately 1,500 km2 face high rockfall occurrence potential. The Southern Carpathians emerged as the most vulnerable area, and all over the Carpathians and Subcarpathians statistical analysis highlighted that topographical and environmental factors are the primary drivers of rockfall distribution. Our model achieved 94% predictive accuracy, confirming the reliability of the resulting potential rockfall occurrence map, as well as its utility as a decision-support tool. These findings provide a robust scientific reference for national and local authorities to mitigate rockfall geohazards, manage rockfall risks and improve infrastructure resilience in Romania.
Induction motors are foundational components across industrial applications, valued for their inherent robustness, operational simplicity, and cost-efficiency. Maintaining their reliable function is paramount for a wide range of mechanical and electrical systems. However, they are prone to various mechanical and electrical faults, such as bearing defects, rotor issues, and voltage imbalances, which can significantly impair their performance and reliability. This study presents a novel vibration dataset for induction motor fault diagnosis, uniquely acquired using a smartphone-based inertial sensor rather than conventional industrial accelerometers. Vibration signals were recorded along three orthogonal axes (gx, gy, gz), alongside gravity-compensated acceleration components (guserx, gusery, guserz), enabling detailed analysis of both raw and gravity-free vibration characteristics. Data were collected under diverse conditions, including healthy operation and several fault types, across varying rotational speeds and load states. The dataset features long-duration vibration recordings sampled at 100 Hz, suitable for both time-domain analysis and window-based feature extraction. Its inclusion of multiple operating speeds and load conditions is ideal for studying the impact of operational variability on fault signatures. By leveraging low-cost and readily accessible smartphone sensors, this dataset supports practical and accessible vibration data acquisition for supporting the development, benchmarking, and validation of data-driven fault diagnosis methods. This resource is expected to significantly advance research in condition monitoring of induction motor, particularly for machine learning and signal processing applications using vibration data.
Groundwater quality and ecosystem function are significantly influenced by aquifer-hyporheic zone systems, particularly in cases where such systems interact with influent rivers. This study investigates the impact of the geological structure on natural attenuation of chloroethenes in such connected systems. Our research focuses on understanding the complex interactions between geological features and microbial dynamics, shedding light on perchloroethylene transformation from DNAPL sources. Field investigations were conducted in an alluvial aquifer with fluvial paleochannels dominated by gravels and sands separated by silts and clays in floodplains. A multidisciplinary approach was employed, combining sediment geochemistry, chloroethene isotopic fractionation (δ13C), and microbial community characterization. The results revealed distinct microbial assemblages associated with different geological structures, highlighting hydrogeological heterogeneity's role in shaping microbial diversity and activity. Specific microbial genera involved in chloroethene dechlorination across paleochannels, interchannel areas, and the hyporheic zone on the bank of an influent river were identified, illustrating differential microbial contributions to contaminant degradation. Furthermore, the study elucidated medium factors such as hydraulic conductivity and organic carbon availability that modulate microbial community structure and function. These findings enhance understanding of microbial-mediated contaminant attenuation in heterogeneous subsurface environments, informing groundwater remediation strategies and supporting sustainable groundwater management and environmental protection.
This study presents a rigorous technical evaluation of the sequestration of Lead (Pb (II)), a representative potentially toxic element (PTE), using the biomass of the lichen Ramalina conduplicans Vain. Surface characterization conducted via SEM-EDX, transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared (FT-IR) confirmed that the lichen biomass possesses a heterogeneous, porous, and amorphous structure. The surface is rich in carboxyl, hydroxyl, and amino functional groups, which undergo distinct morphological transformations following Pb (II) adsorption. Batch experiments achieved a maximum removal efficiency of 99.15% at pH 5 and a dosage of 83.33 g L-1. Kinetic modeling via nonlinear regression identified the pseudo-second-order model (R2 = 0.965) as the superior fit, while nonlinear Boyd and Weber-Morris models confirmed film diffusion as the primary rate-limiting step. Equilibrium data were evaluated using five nonlinear equilibrium models, with the Hill model providing the most accurate description (R2 = 0.936). The Hill coefficient (nH = 1.983) reveals positive cooperativity, indicating that the initial Pb (II) binding enhances the affinity of subsequent binding sites. While the Langmuir model (R2 = 0.894) estimated a maximum adsorption capacity (qmax) of 3.889 mg g-1, the superior fits of Hill, Redlich-Peterson, and Temkin models confirm a complex chemisorption mechanism occurring on a heterogeneous surface. Thermodynamic analysis further categorized the process as both spontaneous and endothermic. In conclusion, R. conduplicans biomass functions as a sustainable and cost-effective biosorbent for Pb (II) removal. While further optimization is required for industrial scaling, its cooperative binding mechanism and high removal efficiency highlight its potential as a green component in integrated PTE remediation strategies.
This study proposes a novel method for lithological identification to address the challenge of accurate classification in complex sedimentary successions. Leveraging principal component analysis, the methodology was developed using Ordovician data from the Western Ordos Basin, where the lithological assemblage predominantly comprises of marine carbonate rocks, claystones, and their associated transitional rocks. Five well-log curves highly sensitive to lithology were selected as original variables, from which two principal components (PCs) were extracted to capture key compositional discrepancies. The first PC effectively differentiates clay and carbonate minerals, thereby enabling identification of transitional rocks between carbonates and claystones. The second PC reflects variations in calcite and dolomite contents, allowing discrimination of transitional lithologies between limestone and dolostone. Following the geological interpretation of these two principal components, a lithological cross-plot was constructed, which reveals distinct clustering among various rock types and supports a well-defined classification framework for transitional lithologies. The reliability and accuracy of the proposed method were validated against X-ray fluorescence element logging data from an active borehole. By prioritizing geological interpretability through feature transformation rather than treating the classification as a "black box", this study establishes a transparent, observable, and highly practical framework for lithological identification.
The standard addition method (SAM) determines sample isotope compositions from mixtures of samples and standards with known isotope ratios, which has been widely applicated for low-mass or low-concentration samples. However, conventional off-line SAM is labor-intensive and can suffer from substantial uncertainty (≥2.5%) in the sample proportion (f value) within the mixture, which compromises isotopic accuracy. Here we present a novel online SAM specifically designed to address these challenges. The reference gas routinely used in conventional analyses is innovatively repurposed as a standard and introduced online directly into the sample stream via the ConFlo IV interface. The isotope ratios of samples are subsequently calculated using an isotope mass balance model. The method is evaluated and validated by measuring the sulfur (S) isotope compositions of standard materials and natural samples using elemental analyzer isotope ratio mass spectrometry (EA-IRMS). The uncertainty in the f value is less than 0.148%, ensuring the accuracy of calculated results. The approach eliminates the need for manual standard addition, significantly enhancing measurement efficiency. The method achieves accuracy and reproducibility comparable to conventional techniques while reducing the sample mass by 75%. Based on the developed approach, coarse to ultrafine atmospheric particulate matter was successfully measured in a haze event, revealing size-dependent S isotope variations. Importantly, this methodology is highly practical and easy to be widely adopted for current standard equipped EA-IRMS laboratories, as it requires no additional labor and financial investments for hardware upgrading proposed in previous publications.
Persistent biodiversity data shortfalls undermine our capacity to detect species, map their distributions and characterize their spatial genetic structure, limiting robust biogeographic analyses and the development of effective conservation strategies. This particularly affects hyperdiverse invertebrate groups where hidden diversity remains largely undocumented. This study develops and demonstrates the potential of an integrated high-throughput sequencing (HTS) framework to improve the representation of hidden diversity in regional species inventories and to help close critical gaps in our understanding of species distributions and genetic diversity from a conservation biogeography perspective. Focusing on the Canary Islands (Spain), the workflow combines megabarcoding of more than 4000 mesofauna specimens to generate a curated species-level molecular reference library with community DNA metabarcoding of 168 soil samples. This approach enables consistent taxonomic assignment across insular landscapes and increases the spatial and genetic resolution of occurrence data. We identified 145 species of mites and springtails, including 49 species newly recorded for the archipelago and numerous genetically distinct lineages likely representing undescribed taxa, highlighting all the biodiversity that remains to be described. Integration of the barcode library with metabarcoding data produced 1440 species occurrences, revealing extensive distributional gaps, multiple range expansions and strong within-island phylogeographic structuring, indicating prevalent diversification at fine spatial scales. These results highlight a deep, taxonomically broad underestimation of soil biodiversity and demonstrate that this integrative approach provides a transferable model for advancing the biogeography, evolutionary understanding and conservation of dark and cryptic taxa across broad taxonomic and conservation-relevant contexts.
Fluoride (F¯) is a global geogenic contaminant in groundwater, occurring at elevated concentrations across almost every continent. While optimal fluoride intake benefits dental health, levels exceeding the WHO safe limit (1.5 mg L-1) can cause dental fluorosis and even severe skeletal fluorosis, with drinking water being the primary exposure pathway. Understanding the global occurrence and geochemistry of fluoride in groundwater is essential for minimizing associated health risks. Therefore, this study reviews the incidence, distribution, mobilization mechanisms of fluoride in groundwater, and identifies the key knowledge gaps related to fluoride contamination worldwide. The study presents a large-scale synthesis of contaminated aquifers, cost-effective defluoridation methods, socio-economic challenges, and strategies for safe drinking water supply. This was done by adopting the PRISMA 2020 systematic review framework with review period between 1953 and 2025. Findings confirm that fluoride contamination is prevalent in Asia, Africa, the Middle East, Europe, and the Americas, driven mainly by fluorine-bearing minerals in aquifers. Key factors intensifying the contamination includes hydrogeochemical conditions such as high pH, Na-HCO3 water types, and low calcium (Ca2+) concentrations. Identified hotspot are the East African Rift Valley, Indo-Gangetic plains, northern China, and volcanic or geothermal regions in Mexico and Türkiye, with localized anomalies observed in Estonia, Poland, and Australia. Anthropogenic inputs contribute in some localized areas, although their impact is minimal. The fluoride levels are particularly high in arid and semi-arid regions, where evaporation and prolonged water-rock interaction accelerate fluoride mobilization. Despite decades of research, monitoring gaps persist, and mitigation remains challenging, especially for rural communities who are entirely dependent on untreated groundwater. This study recommends prioritizing efforts on scalable, cost-effective solutions to provide fluoride-safe water, particularly in areas where populations are largely vulnerable.
Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and secondary datasets and 11 repositories and argues how better integration and accessibility of hydrological data can improve research. The paper distinguishes between datasets where streamflow was the primary data collection objective and those where it was secondary. This distinction highlights opportunities to consider data from efforts peripheral to hydrology but is still useful for understanding hydrologic conditions. The analysis reveals that out of about 118 000 active and inactive stream observation sites, about 6.6% and 25% are located on first- and second-order streams, respectively. This indicates a substantial data gap for headwater systems, which account for over 77% of stream length in CONUS. Federal agencies manage 72% of hydrologic monitoring sites across all stream orders, but only 34% of these are in headwater systems. Academic institutions operate about 2% of sites, with almost half (48%) in headwater systems, focusing on ecosystem research. State agencies also operate about 2% of sites, primarily on larger systems, with 19% on headwaters. Additionally, 23% of sites are managed by multiple agencies. Spatial patterns further reveal pronounced disparities among physiographic regions. Eastern and coastal provinces show relatively dense monitoring, while central and western regions show sparse coverage. These gaps reflect historical priorities, logistical constraints, funding limitations, and the high cost of continuous instrumentation. To address biases in monitoring networks, data collection could be enhanced with low-cost monitoring, community science, and remote sensing technologies. This study also notes the benefits of long-term monitoring and prioritizing retention of streamgages with longer records.
Gadolinium (Gd) has emerged as a trace contaminant in aquatic environments due to the widespread use of gadolinium-based contrast agents (GBCAs) in magnetic resonance imaging (MRI) diagnostics. This study evaluates how preservation conditions, including temperature, acidification, and filtration, affect the stability of Gd chelates in three water matrices (deionized water, tap water, and river water) using inductively coupled plasma mass spectrometry (ICP-MS) for total Gd quantification and ion chromatography coupled with ICP-MS (IC-ICP-MS) for individual GBCA quantification. Across all experiments, the linear GBCA was the most susceptible to degradation, with acidification and ion-rich waters accelerating their dissociation, while macrocyclic agents remained more stable. Freezing provided no preservation benefit and sometimes introduced artifacts possibly related to freeze-concentration effects. Filtration improved recoveries in river water by reducing interactions with particulates and microbial activity, and refrigeration slowed degradation but did not fully prevent it in complex matrices. These patterns show that certain preservation choices can alter apparent speciation and lead to underestimation of linear chelates and misinterpretation of GBCA sources. The results provide standardized preservation protocols for sample handling, including avoiding acidification, minimizing storage time, and refrigerating samples when immediate analysis is not possible.
Large Late Permian reef-shoal mounds and supergiant gas fields have been identified along the margin of the Kaijiang-Liangping trough on the Upper Yangtze Platform. However, the underlying mechanisms of their concentration along the trough margin remain unclear. Herein, the Damaoping Block at the eastern trough end is used as a case study to examine how trough currents influence the development of reef-shoal mounds and reef-cap reservoir distribution. Results show that enhanced seismic facies analysis can identify individual reef-shoal mounds in low-amplitude reef-shoal zones and map small-scale reef-cap dolomite reservoirs. Sponge reefs occur in neritic water below the normal wave base because of upwelling. Rear reef-shoal mounds align directionally and become less developed toward the platform interior, with their orientation following the trough axis-indicating upwelling direction. Nutrient- and oxygen-rich cold bottom currents and upwelling helped sustain the preferential development and directional distribution of reef-shoal complexes, and indirectly controlled dolomite reservoir distribution on reef tops. This study establishes a methodological framework for reconstructing carbonate sedimentary systems and characterizing small-scale reef-shoal facies reservoirs, and provides evidence for deep-water bottom currents and upwelling on the Permian Yangtze Platform, which may contribute to future discussion of Late Permian thermohaline circulation.
This data article describes a structured dataset of seismic and geodetic deformation parameters for the Kopeh Dagh Belt in northeastern Iran. The dataset integrates Global Navigation Satellite System (GNSS) velocity measurements from 16 stations with earthquake focal mechanism information covering the period 1969-2024. GNSS velocity components and associated uncertainties are provided in a Eurasia-fixed reference frame. Earthquake data include location, magnitude, focal depth, and nodal plane parameters (strike, dip, and rake), together with derived stress tensor quantities. The spatial framework is defined by a discretization of the region into 20 triangular subnetworks using Delaunay triangulation. For each subnetwork, geodetic strain components are calculated from GNSS velocity gradients, while seismic strain parameters are derived from moment tensor information. Additional variables include rotation rates obtained from the antisymmetric component of the velocity gradient tensor, as well as principal stress axes, stress ratios, and stress regime classifications obtained through inversion of focal mechanism data. All datasets are organized in a machine-readable format and include raw measurements, intermediate parameters, and derived quantities. The dataset is intended for reuse in tectonic analyses, numerical modeling of deformation fields, evaluation of strain partitioning, and comparison of seismic and geodetic deformation patterns in intraplate regions.
The global current systems of a planet represent electrodynamic interactions between its different parts, and between its magnetosphere and the ambient solar wind. Although some local currents of Mercury's magnetosphere have already been revealed by previous observational studies, the global picture of current systems in Mercury's magnetosphere remains unknown. Here we reconstruct the global current systems in the Mercury's magnetosphere, using five years magnetic field and plasma measurements made by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft. It reveals a complex picture: a magnetopause current, cross-tail current, inner and outer equatorial ring currents and an unexpected polar ring current. The equatorial ring currents and the polar ring current agree with the prediction of the plasma drifting model in a region with a pressure gradient. These ring currents could reshape Mercury's magnetosphere and reveal new dynamics and energy transfer processes in Mercury.
Significant gold deposits occur within the ophiolitic rocks of the Central Eastern Desert of Egypt; yet, the structural controls governing ore distribution remain insufficiently constrained. This study applies an integrated remote sensing-aeromagnetic-structural workflow to the Um Salim area along the ENE-trending Barramiya-Um Salatit ophiolitic belt to delineate surface and subsurface architectures and assess their influence on gold localization. High-resolution lithological mapping was achieved through machine-learning classification of hyperspectral EnMap data using the Random Forest (RF) and Support Vector Machine (SVM) algorithms. SVM applied to enhanced Minimum Noise Fraction (MNF) components yielded superior performance, achieving an overall accuracy of 95.8%, a kappa coefficient of 94.6%, and an F1-score of 96.6%. Reduced-to-pole magnetic data reveal a prominent positive anomaly (~ 1400 nT) directly over the Um Salim gold mine, attributed to magnetite-bearing metavolcanics and ophiolitic serpentinite rocks. Upward continuation to 0.5-1 km confirms that this anomaly reflects a deeply rooted magnetic source. To refine structural interpretation, advanced edge-detection filters (TAHG and ILTHG) were applied, enhancing ENE-WSW, NE-SW, NW-SE, and N-S trends consistent with multi-phase deformation (D1-D3), and SAR-derived lineaments. Center for Exploration Targeting (CET)-based lineament density and orientation entropy maps delineate zones of intense structural complexity that closely correspond with mineralized shear zones and dyke-like porphyry intrusions. Depth-to-source analyses using Euler Deconvolution (EUD) and Tilt-Depth (TD) methods reveal that most magnetic bodies occur within 0-1000 m, whereas deeper (~ 1500 m) sources likely represent intrusive conduits that focused hydrothermal fluids. The novelty of this study lies in its integrated, multi-technique application of aeromagnetic analysis combined with hyperspectral machine learning to characterize a small, gold prospect and to map alteration-linked structural features at high resolution in the Barramiya-Um Salatit belt. The integrated results highlight new structurally complex zones in the eastern and southeastern Um Salim region as high-priority exploration targets, particularly along the NE-SW shear system that controls gold mineralization. This workflow provides a high-resolution, transferable strategy for targeting gold in structurally complex Precambrian terranes worldwide.
Cannibalism and intraguild predation (IGP) are common interactions among predators that can influence the effectiveness of biological control agents. The minute pirate bug Buchananiella whitei is a recently commerciali sed biocontrol agent in New Zealand, but its intraspecific predation and interactions with potentially co-occurring predatory mites remain poorly understood. This study examined cannibalism within B. whitei, as well as IGP between first-instar B. whitei nymphs and adult females of seven predatory mite species (Phytoseiidae and Laelapidae), using observations in enclosed setups with emphasis on the role of extraguild prey availability (dried fruit mite Carpoglyphus lactis). Both cannibalism and IGP were observed, and their occurrence was strongly influenced by extraguild prey availability. No predation on B. whitei eggs was observed in either cannibalism or IGP. Cannibalism occurred only in adult-nymph interactions, and its prevalence was greatly reduced by the presence of extraguild prey. IGP was more frequent in the absence of extraguild prey. First-instar B. whitei nymphs preyed on most predatory mite species, but reciprocal predation was only observed with Neoseiulus cucumeris and Stratiolaelaps scimitus. Differences in body size among predator species partly contributed to the observed outcomes. These findings indicate that although cannibalism and IGP can occur in systems involving B. whitei, their ecological significance is probably limited when alternative prey are available. Predatory mites are therefore unlikely to substantially suppress B. whitei populations. A better understanding of these trophic interactions will improve the use of B. whitei and other natural enemies in biological control programs. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
This study provides a detailed, bi-seasonal analysis of microplastic (MP) distribution in Kuakata's coastal region, which is influenced by both terrestrial and marine pollution sources. The research documented spatio-temporal variation of MP pollution, with the use of stereomicroscopy for morphological characterization and ATR-FTIR for polymer identification. The analysis revealed that MP concentration peaked during the monsoon season, with river flow identified as the primary distributing factor. Higher degree of contamination was observed along the eastern coastline, attributed to land-based sources and degradation of larger plastics like polyethylene (PE) and polypropylene (PP). White, grey, and transparent MPs (70.06%) were dominant, while fragments were the most prevalent morphological shape (59.67%). Based on these findings, it is speculated that long-distance river transport is the major contributor to MP accumulation, overshadowing local sources and tourist activities. The combination of morphological study with grain size analysis depicts the factors influencing MP degradation, transport, and accumulation. Additionally, SEM analysis revealed surface irregularities like cracks and pits, indicating environmental breakdown. Detailed risk assessments, including pollution load index (PLI), potential risk index (PRI), potential ecological risk index (PERI), and polymer hazard index (PHI), highlighted varying ecological risks. Although hazardous polymers like polyvinyl chloride (PVC) were found in small level, their high hazard score contributed to elevated risks. Principal component analysis (PCA) revealed distinct distribution patterns and common origins for different plastic types. Pellet, film, and fiber particles showed potential commonalities in origin and transport pathways. The findings provide dynamic insights into the MP pollution scenario, offering a foundation for future advanced research.