Search Results (539)

Plastic pollution has emerged as a major environmental concern due to its persistence and widespread accumulation in terrestrial ecosystems. The extensive utilization of plastics across a diverse range of products, from packaging to healthcare, construction, and transportation, poses a significant risk due to their enduring and non-biodegradable nature. Micro/nanoplastics (MNPs) derived either from the fragmentation of larger plastics or direct release are increasingly detected in agricultural soils, where they interact with plant systems. In addition, chronic exposure of MNPs alters soil structure, microbial diversity, and nutrient cycling, further impacting agroecosystem functioning. Plants have been shown to absorb MNPs mostly from contaminated soil and irrigated water through their root systems, allowing their subsequent translocation to aerial tissues. MNPs can enter plants through the aquaporins, apoplast pathways, crack entry modes, and leaf stomata, disrupting nutrient uptake, photosynthesis, and growth processes, ultimately affecting crop productivity and quality, while their accumulation in edible tissues raises concerns regarding food safety and trophic transfer. To address these challenges, it is crucial to have standard detection methods for identifying MNPs and to bridge the gap for further mitigation. This review further discussed effective mitigation strategies, including nanomaterial and phytohormone-based interventions under increasing plastic contamination. Full article

Rapid coastal urbanization poses severe threats to biodiversity through habitat fragmentation, making continuous monitoring of urban ecosystems essential. While birds serve as sensitive bio-indicators, the long-term spatiotemporal dynamics of their habitats and temporal shifts in environmental drivers remain poorly understood in high-density megacities. This study addresses this gap by developing a trend-explainable machine learning framework to evaluate avian habitat suitability across the western coast of Shenzhen from 2010 to 2020. We applied a standardized filtering protocol to citizen science data and integrated occupancy modeling with a Random Forest algorithm to simulate habitat distributions at 30 m resolution. Spatiotemporal habitat alterations were quantified using Mann–Kendall trend analysis, while SHAP was utilized to diagnose the changing importance and non-linear thresholds of ecological drivers over the decade. Our findings reveal pronounced spatial heterogeneity among six avian guilds. Habitat quality for terrestrial birds, raptors, and songbirds degraded severely in northern industrial regions, whereas targeted ecological restoration facilitated recovery in southern and western urban cores. The analysis further demonstrates dynamic temporal shifts in environmental responses. The restrictive impact of anthropogenic stressors including population density and nighttime light weakened for terrestrial and canopy-dwelling guilds but intensified for waterfowl. Concurrently, natural elements such as vegetation coverage and proximity to water bodies became increasingly important. Based on these spatiotemporal patterns, we delineated five ecological zones to guide targeted conservation interventions. This research provides an analytical framework linking predictive modeling with mechanistic insights, supporting evidence-based biodiversity conservation and sustainable urban planning in rapidly developing coastal landscapes. Full article

Oil pollution remains a persistent global environmental challenge due to the recalcitrance and toxicity of lipid-rich contaminants in terrestrial and aquatic ecosystems. Bacterial lipases (EC 3.1.1.3) play a pivotal role in the initial stages of bioremediation by catalysing the hydrolysis of complex lipids into more bioavailable intermediates, thereby facilitating downstream microbial degradation and mineralisation. This review critically examines the mechanistic basis of lipase-mediated hydrocarbon degradation, with emphasis on enzyme structure–function relationships, catalytic pathways, and regulation under environmentally relevant conditions. In addition to conventional applications in soil and wastewater bioremediation, emerging strategies involving immobilised enzymes, microbial consortia, and waste-derived substrates are evaluated for their effectiveness and scalability. Attention is given to advances in molecular and omics approaches, including metagenomics, transcriptomics, and proteomics, which have expanded the discovery of novel lipases but remain limited in their ability to predict in situ functionality. The review highlights the growing role of protein engineering and artificial intelligence in tailoring lipase properties; however, it also critically assesses current limitations, including insufficient experimental validation and challenges in translating computational predictions to complex environmental systems. Furthermore, integrating multi-omics data into quantitative and predictive frameworks is identified as a key future direction for improving bioremediation efficiency. Despite significant progress, major gaps persist in linking enzyme activity to real-world degradation performance and in developing standardized, scalable approaches. This review therefore provides a comprehensive and critical synthesis of current knowledge while identifying strategic research priorities required to advance bacterial lipases as robust tools for sustainable bioremediation of lipid-based pollutants. Full article

Efficient bridge scanning and documentation are crucial for creating reliable digital 3D models. However, scanning workflows often rely on implicit practitioner experience rather than standardized protocols. This paper presents practical insights derived from a Multiple Case Study (MCS) of ten heterogeneous, real-world bridges in Germany. The study evaluates Terrestrial Laser Scanning (TLS), Mobile Laser Scanning (MLS) and Unmanned Aerial Systems (UAS) photogrammetry. The findings isolate distinct performance trade-offs. TLS offers high accuracy but suffers from shadowing occlusions. Conversely, UAS provides operational flexibility but introduces geometric vulnerabilities, including photogrammetric reconstruction noise on fine structures and SLAM trajectory drift on vibrating spans. To unify these insights, a generalized, BPMN-compliant process model mapping the complete data acquisition lifecycle under legal and spatial constraints is defined. This research provides an actionable, practical guide to optimize data quality and efficiency in structural engineering workflows. Full article

Environmental risk assessment of landfill solid waste should include higher plants as indicators of toxicity to support sustainable waste management. This study evaluated solid waste from mining and power-generating industries using SANS 10234, a multidisciplinary approach that combined physicochemical analysis of waste samples and the Phytotoxkit bioassay to assess plant-based toxicity. Leachate extractions from samples identified as wastes of concern were evaluated using standard toxicity tests. Based on the Phytotoxkit results, Coal solid waste A, Clinker ash, and Chrome solid waste were identified as wastes of concern, whilst the whole effluent toxicity test results of the leachate indicated that these three samples pose a low risk to aquatic ecosystems. The phytotoxicity was attributed to the waste’s physicochemical parameters. Coal solid waste A expressed a low pH of 2.60 and a high electrical conductivity of 14,557 µS/cm, while Clinker ash presented a pH of 6.72 and an electrical conductivity value of 3685 µS/cm. These values were outside the optimal range for many plants to thrive. The presence of toxic elements in some samples may have contributed to the observed phytotoxicity. These results highlight that solid waste can present varying risks to both terrestrial and aquatic systems, reinforcing the importance of including higher plants in landfill risk assessments for sustainable waste management. Full article

Colombia hosts 28 species of freshwater and terrestrial turtles, yet anthropogenic pressures such as illegal trafficking and urban expansion have intensified risks. In Cali, non-native turtles are frequently introduced into wetlands through pet abandonment and confiscations, creating novel assemblages in urban ecosystems. To examine this issue, ecological surveys were conducted in three urban wetlands during December 2024, complemented by enforcement records from the Wildlife Rescue Center (WRC) spanning 2015–2023 and reports from environmental authorities. Turtles were captured manually using natural baits placed in floating containers or along shoreline areas to attract individuals, then identified morphologically, measured for standard morphometric parameters, and released at the site of capture. WRC records were reviewed to assess species composition and causes of admission. Field sampling yielded 109 individuals representing four species (Trachemys callirostris, Podocnemis unifilis, Kinosternon leucostomum, Rhinoclemmys melanosterna). WRC records documented 2751 individuals across 11 species, with five taxa accounting for over 96% of admissions. Both datasets revealed a predominance of Trachemys callirostris. Morphometric data indicated multiple size classes, suggesting demographic heterogeneity within the turtle populations inhabiting the sampled wetlands. The overlap between confiscation records and wetland observations suggests potential links between illegal trade and species presence in urban wetlands, while the predominance of voluntary surrenders reflect the influence of enforcement activity and pet abandonment. Collectively, these findings demonstrate how urban wetlands facilitate the persistence of non-native turtles, reshaping species composition and underscoring the urgency of integrated strategies that combine enforcement, habitat management, veterinary protocols, and citizen education to safeguard native biodiversity. Full article

This work presents a comprehensive review of axion physics through the generative lens of a novel theoretical framework: Real-Now-Front (RNF) cosmology. Moving beyond the standard treatment of the axion as a fundamental particle in a pre-existing spacetime, we systematically reinterpret it as a specific collective excitation, a “twist” mode, arising from the alignment dynamics of the more fundamental Chronon field, from which spacetime itself emerges. Within this paradigm, the axion’s mass, its couplings to photons and matter, and the symmetry-breaking scale $f_a$ are not independent parameters but are derived from the microscopic stiffness and correlation length of the Chronon field, governed by the Temporal Coherence Principle. We re-examine the entire axion landscape, including benchmark models (KSVZ, DFSZ, ALPs) and the full spectrum of experimental constraints from terrestrial haloscopes, helioscopes, and astrophysical environments, translating them into probes of Chronon alignment dynamics. Furthermore, this generative framework yields unique, testable predictions, such as emergent bimetric effects and primordial black hole seeds from closed domain walls, providing independent avenues for falsification. By synthesizing established knowledge with this foundational new perspective, the review aims to establish a unified basis for the next generation of axion searches, positioning them as direct tests of the microscopic architecture of emergent spacetime, leveraginga multi-decade, multi-messenger observational campaign. Full article

6G promises ultra-low latency, high data throughput, and seamless global connectivity. However, providing uninterrupted connectivity in remote and underserved regions remains a critical challenge for Terrestrial Networks (TNs), where the cost of deploying infrastructure is difficult to justify against sparse user density. Standardized under 3GPP Release 17, Non-Terrestrial Networks (NTNs) have emerged as a viable solution to close this digital divide. Among NTN platforms, High-Altitude Platform Stations (HAPS) occupy a strategic middle ground, as they deliver lower propagation delays than Low-Earth Orbit (LEO) satellites while achieving far broader coverage than TN-based Base Stations (BS). Despite these advantages, battery-powered Internet of Things (IoT) devices communicating via HAPS face a fundamental energy efficiency (EE) challenge: transmit power must be carefully managed to maximize data throughput while preserving battery life and minimizing packet queuing delays. To address this, we propose a Q-learning-based Reinforcement Learning (RL) framework. The RL agent observes the instantaneous battery level and queue state of the IoT device, and dynamically selects optimal power levels from a discrete action space across successive time slots. Unlike traditional heuristic algorithms, such as Round Robin (RR), Max Single-to-Noise Ratio (Max-SNR), and fixed-power allocation, which rely on static rules or greedy channel-based decisions, the proposed Q-learning agent learns adaptive, long-term optimal policies through direct interaction with the environment, without requiring explicit mathematical modeling of the channel or traffic dynamics. Extensive simulations demonstrate that the proposed framework achieves up to 40% higher average EE compared to all benchmark schemes, maintains consistently lower power consumption, and exhibits superior statistical reliability as evidenced by a right-shifted Cumulative Distribution Function (CDF) of EE. These results demonstrate Q-learning as a promising candidate for scalable, energy-aware power control of next-generation HAPS-assisted IoT deployments in 6G NTN ecosystems. Full article

Soil fungi are key drivers of terrestrial ecosystem functioning, contributing to organic matter decomposition, nutrient cycling, and plant–microorganism interactions. Despite their importance, the global distribution and structural biases of public sequence records for soil fungi remain incompletely characterized. In this study, we analyzed soil-associated fungal DNA sequences retrieved from the NCBI GenBank database using a custom R-based bioinformatics pipeline. Following filtering and metadata standardization, 544,554 filtered sequence records were obtained. The taxonomic composition of the dataset consisted primarily of Ascomycota (69.62%), followed by Basidiomycota, Glomeromycota, and Mucoromycota, with Trichoderma, Penicillium, and Aspergillus representing the most frequent genera. The geographic distribution revealed strong sampling bias, with China and the United States accounting for over one-third of all records. Ecological metadata indicated that rhizospheric and forest soils were the most common sources of the deposited sequences. At the same time, gene marker analyses confirmed the widespread use of the ITS region as the primary fungal barcode. Sequence diversity analyses revealed continental variation, with Europe and Asia showing higher medians, while the ordination highlighted clustering of sequence profiles, particularly among records from extreme environments. This study demonstrates the potential of public sequence databases for large-scale biodiversity assessments while highlighting the influence of sampling bias and the limitations of metadata. Full article

As an important port in the Beibu Gulf of the South China Sea, Tieshangang Bay is potentially at risk of PTE pollution, yet systematic research integrating multi-hydrological period data remains limited. By applying pollution indices (C_f, WQI, I_geo, RI) combined with PCA, and PMF, we investigated PTE distribution characteristics, risk assessment, and source apportionment across different hydrological seasons. The results indicate that average PTE concentrations in surface seawater meet Class II standards of the Sea Water Quality Standard, with Zn and As showing relatively high concentrations compared to other PTEs. High-concentration areas were mainly located in the inner and middle bay. In sediments, concentrations of Zn and Cr were relatively high, with values generally higher inside the bay than outside. Both C_f and WQI values for seawater PTEs were below 1, indicating an overall low pollution risk. However, Cd and Hg in sediments presented a moderate potential ecological risk. Source apportionment revealed that seawater PTEs primarily originated from an industrial–aquaculture composite source (44.60%), while sediment PTEs were mainly attributed to composite terrestrial inputs (53.16%). These findings provide a scientific basis for PTE pollution management and sustainable development in Tieshangang Bay. Full article

Heavy metal(loid) pollution in watersheds surrounding mining areas originates from multiple and complex sources, posing persistent threats to terrestrial–aquatic ecosystems and human dietary safety. This study systematically investigated the pollution characteristics, spatial distribution, ecological risks and human health hazards of seven typical heavy metal(loid)s (As, Pb, Cr, Cd, Cu, Zn, and Ni) in the integrated water–soil–vegetable continuum of a mining-affected watershed in Southwest China. Field sampling was carried out in three functional zones with different mining disturbance intensities, and inductively coupled plasma mass spectrometry (ICP-MS) was used to detect heavy metal(loid) concentrations in all samples. Multiple pollution evaluation indices and the USEPA human health risk assessment model were adopted for comprehensive quantitative analysis. The results showed that 44.0% of surface water samples exceeded national permissible limits, with high-pollution areas concentrated in intensive mining zones, presenting moderate overall aquatic heavy metal(loid) pollution. Although the average concentrations of seven heavy metal(loid)s in riparian soils complied with Chinese agricultural soil screening standards, localized significant enrichment was observed for As (1.98 times), Cd (4.62 times), Cu (1.81 times), and Zn (2.72 times) compared with regional background values, causing mild comprehensive soil pollution. Farmland soils exhibited prominent Cu and Zn accumulation, and leafy vegetables in the study area suffered severe Pb and Cd pollution, with potential dietary exposure risks. Health risk assessment indicated that children face higher non-carcinogenic and carcinogenic risks than adults via soil hand-to-mouth exposure; dietary intake of vegetables leads to moderate carcinogenic risks for children caused by As and Ni exposure. Overall, this study clarifies the migration and enrichment rules of heavy metal(loid)s in the water–soil–vegetable system of mining watersheds, confirms the prominent ecological and human health risks of Cd, As and Pb in the study area, and provides targeted basic data for regional heavy metal(loid) pollution prevention and food safety management. Full article

Microplastics (MPs; <5 mm) represent a growing environmental concern that increasingly challenges environmental monitoring, governance, and evidence-based decision-making. This review critically examines how current scientific understanding of microplastic sources, classification, occurrence, and environmental behavior can support environmental governance. MPs are classified as primary and secondary particles; however, persistent inconsistencies in size definitions, shape descriptors, and polymer identification limit the comparability of monitoring data and constrain the development of coherent regulatory frameworks. Evidence on the occurrence of MPs in surface waters and sediments highlights widespread contamination and pronounced spatial variability, raising challenges for risk assessment and policy harmonization across regions. Key transport pathways, including atmospheric deposition, terrestrial runoff, and riverine fluxes, are analyzed to illustrate how local emissions translate into large-scale environmental impacts. Rivers emerge as key components linking sources to receptors, offering relevant points for policy intervention and management measures. The review evaluates current policy responses to microplastic pollution, identifying significant gaps in standardized monitoring, data integration, and risk assessment approaches. It emphasizes the need for stronger alignment between scientific outputs and policy requirements, including the co-production of knowledge involving scientists, regulators, and stakeholders. By outlining pathways through which scientific evidence can inform regulatory design and environmental management, this study provides actionable insights for improving policy effectiveness. Advancing harmonized methodologies and integrating science into decision-making processes are essential steps toward mitigating microplastic pollution and supporting sustainable environmental governance. Full article

Mass–balance discrepancies exist between estimated land-based inputs and observed marine plastic inventories. While current global mass–balance models predominantly treat the open ocean as a passive terminal sink, they overlook the rapid expansion of offshore and deep-sea industrial frontiers. This review identifies offshore and deep-sea activities as active, in situ emission nodes of microplastics (MPs). Through a bibliometric analysis and numerical descriptions of studies, we document that direct offshore emissions are underrepresented in the current literature. By synthesizing these limited quantitative data, preliminary metrics indicate localized MP enrichment signals and elevated biological exposure near specific offshore infrastructures. Furthermore, plastics released directly into the marine environment bypass terrestrial weathering, undergoing distinct multiscale aging pathways governed by the complex interplay of wave-induced physical fragmentation bounded by critical size thresholds, UV-driven chemical photo-oxidation, and biological interactions. We conclude that refining global plastic budgets supports moving toward an integrated ocean-industrial framework. However, the synthesis remains constrained by data scarcity and high methodological heterogeneity across different environmental matrices. Future strategies must prioritize standardized in situ flux quantification and the incorporation of MP emission risks into offshore Environmental Impact Assessments. Full article

Underwater object detection using forward-looking sonar presents fundamental challenges absent from terrestrial imagery: low-contrast single-channel inputs, multi-scale acoustic shadows, and object classes spanning a wide range of acoustic scattering characteristics. Three coordinated modifications to the YOLOv8 framework are proposed to address structural limitations of standard bottleneck chains for this domain. A fractional-order feature propagation mechanism based on Grunwald–Letnikov discretization enables each bottleneck to access a decaying-weighted history of all prior intra-chain feature states via a single learnable scalar per block. A boundary-aware gating module with joint spatial-channel attention selectively suppresses fractional correction at geometric boundary locations. A parameter-free energy-based attention module applied in the detection neck exploits the local statistical distinctiveness of genuine acoustic features during multi-scale fusion. Evaluated on the Underwater Acoustic Target Detection dataset, the proposed system achieves mAP50 of 0.8635 and mAP50-95 of 0.3964, improvements of 0.0188 and 0.0136 respectively over the YOLOv8n baseline at less than 2.0% parameter overhead, surpassing larger generic YOLOv8 variants on mAP50. Full article

Microplastic (MP) contamination has become a defining feature of twenty-first century environmental change, yet the toxicological and ecological consequences for amphibians and reptiles—two vertebrate classes already facing severe extinction pressures—remain fragmented across taxa, regions, and methodological traditions. Here, we synthesize field and experimental evidence from five continents to provide a taxonomically balanced, mechanistically grounded, and geographically explicit assessment of MP exposure, bioaccumulation, and toxicity in herpetofauna, drawing on a structured literature search in Web of Science, Scopus, and PubMed (January 2015—March 2026). Field detection rates of MPs in amphibian larvae range from 26% in conservatively screened Central European populations to 73–80% in anuran tadpoles from high-anthropogenic-pressure Anatolian catchments, with fibrous polyethylene terephthalate (PET), polyethylene (PE), and polypropylene (PP) particles dominating the detected burden. Mechanistic evidence converges on oxidative stress cascades, hypothalamic–pituitary–thyroid axis disruption, gut and cutaneous microbiome dysbiosis, and compromised antiviral and antifungal immunity, with the latter potentially amplifying vulnerability to Batrachochytrium dendrobatidis and to ranavirus. Among reptiles, sea turtles display near-universal MP ingestion with documented maternal transfer to eggs; freshwater turtles, terrestrial squamates, and crocodilians remain critically understudied. Three structural asymmetries constrain current ecotoxicological risk characterization: taxonomic bias toward anurans and sea turtles, geographic bias toward the Global North, and experimental bias toward acute, supra-environmental laboratory exposures using pristine, single-polymer particles that fail to capture the chemical complexity of weathered field mixtures. We argue that MP burden may warrant consideration as a candidate stressor criterion within IUCN Red List assessments and within environmental risk assessment frameworks for freshwater and terrestrial biodiversity once a robust quantitative relationship between MP burden and demographic decline or population-level fitness has been established, and propose six hypothesis-driven research priorities: methodological standardization, reptile toxicokinetics, transgenerational epigenetics, MP–pathogen microbiome interactions and their translation into population viability models, temperature × MP interaction under climate warming, and population-genetic consequences of contemporary MP-driven selection, as the most tractable avenues for ecotoxicological progress and for the development of herpetofauna-specific risk characterization frameworks. Full article