Search Results (2,602)

Environmental contamination with potentially toxic elements is a growing concern for ecosystem quality and food safety. This study evaluated the relationships between environmental conditions, anthropogenic activities, and the elemental composition of Prunus spinosa fruits collected from western and central Romania along a pollution gradient. Eighty samples from ten sites representing non-polluted, agricultural, traffic-exposed, and mining-affected areas were analyzed by ICP-MS after microwave digestion. Fruits from impacted areas showed compositional differences, including lower concentrations of some essential macroelements and higher levels of several trace elements potentially associated with anthropogenic pressure. Increased sodium, aluminum, and silicon contents were consistent with environmental stress and enhanced environmental exposure and possible soil-derived particulate influence, while boron and molybdenum declined with pollution intensity. Elemental patterns were mainly associated with local environmental conditions and appeared consistent with site-specific environmental influences. Food safety assessment indicated generally low to moderate risk depending on sampling origin. Overall, Prunus spinosa fruits showed potential as a bioindicator of environmental quality and a useful tool for monitoring anthropogenic contamination. Full article

Slow-onset hazards are intensifying coastal land transformation, yet their socio-environmental implications remain insufficiently understood. The coastal area of Semarang-Demak, Indonesia, represents a critical case due to long-term land subsidence, recurrent tidal flooding, and extensive coastal development interventions. In response to this gap, this study integrates open-access Earth observation with place-attachment perspectives to investigate how urban coastal transformation is materially produced and socially experienced. Multi-temporal Landsat imagery from 1994 to 2024 was processed in Google Earth Engine using the Modified Normalized Difference Water Index (MNDWI), complemented by the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI). The results show spatially uneven coastal land transformation, with 13.02 km² of the study area indicating increased MNDWI values (to-water transformation), while 11.75 km² experienced to-land transformation associated with declining MNDWI values. Further analysis using NDVI and NDBI suggests that part of the to-land transformation reflects anthropogenic built-area expansion, as indicated by areas where NDBI differences exceed NDVI differences. Empirical field observations and interview data contextualize these spatial findings by revealing contrasting yet persistent place attachment across reclamation-influenced areas and communities exposed to erosion and flooding. Building on these findings, the study proposes the notion of the (un)disrupted place to explain how disruption, efforts for resilience and continuity coexist unevenly across coastal space. This study advances a socio-environmental understanding of coastal land transformation and highlights the need for more equitable and multidisciplinary approaches to coastal governance and resilience planning. Full article

During wet deposition, particulate matter and gaseous species in the atmosphere are ultimately transported to the Earth’s surface via precipitation and subsequently incorporated into terrestrial ecosystems. Therefore, investigating the fluxes, chemical compositions, and source apportionment of regional wet deposition is of great scientific importance. An analysis of the concentrations, deposition fluxes, spatiotemporal variations, and source apportionment of water-soluble ions in wet deposition can further enhance our understanding of the water-soluble ion characteristics, atmospheric pollution profiles, and potential ecosystem impacts of wet deposition in the Yangtze River Delta and Pearl River Delta regions. Coastal cities in China are most developed regions, and also areas suffering from severe air pollution. This study investigates the chemical characteristics, sources and wet deposition fluxes of water-soluble inorganic ions in precipitation in two typical coastal urban agglomerations of China: Ningbo in the Yangtze River Delta and Guangzhou in the Pearl River Delta. Precipitation samples were collected and analyzed to determine the concentrations of major ions. The results revealed distinct ionic compositions between the two regions. In Ningbo, NO₃⁻ and SO₄²⁻ were the predominant ions accounting for 16.98% to 23.22% of the total, reflecting the influence of anthropogenic emissions from fossil fuel combustion and mobile sources with the NO₃⁻/SO₄²⁻ ratio of 0.90 and 0.70. In Guangzhou, precipitation was characterized by high contributions of SO₄²⁻, NO₃⁻, NH₄⁺, and Ca²⁺, accounting for 17.22% to 23.29% of the total, indicating a mixed influence of industrial emissions, agricultural activities, and construction dust with the NO₃⁻/SO₄²⁻ ratio of 0.92 and 0.87. A clear inverse relationship between rainfall amount and ion concentration was observed at all sites (p < 0.05), demonstrating a significant dilution effect. Seasonality played a crucial role in deposition fluxes. In Ningbo, fluxes peaked during summer from 4667 to 5156 mg·m⁻², while in Guangzhou, distinct dry and rainy season patterns influenced the scavenging efficiency of different ion species. Urban sites exhibited enhanced scavenging of crustal and anthropogenic ions (e.g., Ca²⁺, NH₄⁺) during the rainy season, whereas the coastal site showed elevated fluxes of marine-derived ions (Na⁺, Cl⁻, Mg²⁺, SO₄²⁻) during the same period. The observed trends in ion fluxes suggest a gradual improvement in regional air quality over the study period. These findings elucidate the complex interactions between anthropogenic activities, natural sources, and meteorological factors in shaping the wet deposition chemistry in coastal urban environments, providing essential data for developing regional deposition models and assessing the ecological impacts of atmospheric pollution. Full article

Groundwater nitrate (NO₃⁻) pollution is a critical environmental challenge with direct implications for human health. In this work, we propose a comprehensive analytical framework that integrates multi-model intercomparison, interpretable machine learning techniques, and quantitative health risk evaluation to tackle the pressing groundwater nitrate governance dilemmas in Handan City, a representative urban area in North China. Based on 157 groundwater samples and 17 hydrochemical parameters, comparative analysis of three state-of-the-art machine learning algorithms showed that the Light Gradient Boosting Machine (LightGBM) algorithm outperformed all counterparts, delivering the optimal predictive performance (R² = 0.753, RMSE = 3.67). SHapley Additive exPlanations (SHAP) analysis identified F⁻, Ca²⁺, Cl⁻, K⁺, total hardness, and Mg²⁺ as dominant factors influencing groundwater NO₃⁻ concentrations, reflecting the combined effects of carbonate dissolution, nitrification, and anthropogenic inputs. Subsequently, we performed a health risk assessment based on the standard methodological framework issued by the United States Environmental Protection Agency (USEPA), and the results indicated that children were the most vulnerable group, with hazard quotient (HQ, a non-carcinogenic risk indicator) values reaching 1.07 in the western mountainous region, exceeding the safety threshold (HQ > 1). These findings clarify the pollution mechanisms and spatial heterogeneity, and provide targeted policy guidance for groundwater protection as well as the safeguarding of public health. Full article

The preservation of hydrobiological diversity is essential to ensuring the stability of the food chain and the sustainable development of high-Andean basins, which face increasing vulnerability to anthropogenic factors such as the construction of dams and reservoirs. In this study, multiple regression models, both linear and nonlinear, were developed to predict the Shannon–Wiener (H′) and Pielou (J′) indices of periphyton and macrobenthos using 21 water quality parameters and concentrations of nine metals in sediments. Samples of macrobenthos and periphyton were collected at seven monitoring stations during the dry and wet seasons between 2014 and 2025. For the analysis, linear regression models were compared with nonlinear machine learning models, specifically Gradient Boosting and Random Forest. Principal component analysis (PCA) revealed that variability of the basin’s ecosystem is dominated by geogenic factors (conductivity, boron, chlorides, and arsenic) and thermal influence. The Gradient Boosting model demonstrated superior predictive capacity (R² = 0.768 for macrobenthos) compared to linear models (R² = 0.354), successfully capturing the nonlinear responses of biota to stressors such as arsenic in sediments and temperature. It is concluded that natural chemical anomalies in the Titire River act as severe ecological filters, and that artificial intelligence shows promising results in the exploration of new applied tools for environmental management in extreme altoandine ecosystems. Full article

Water resources face a significant environmental challenge: pollution from microplastics (MP) and heavy metals (HM). These elements pose a dual threat to ecosystems and public health. Microplastics, defined as particles smaller than 5 mm, are of anthropogenic origin, resulting from the degradation of plastics by environmental factors such as solar radiation and friction with the surrounding environment, as well as from their addition to cosmetic and textile products. These materials have been widely detected in drinking water and everyday foods. Heavy metals, high-density elements $(>5{\mathrm{g}/\mathrm{cm}}^3)$, while naturally present in the Earth’s crust, are also generated in large quantities through human activity. Their toxicological risk lies in their ability to accumulate and efficiently move through the trophic chain. Due to the risks to public health and the impacts these pose to ecosystems, it is necessary to continue seeking solutions that enable their monitoring and detection. As a contribution, this work presents a methodology for detecting microplastics and heavy metals in seawater using different machine learning models and an electronic tongue coupled to a sensor network. Two different types of heavy metals, primarily zinc (Zn) and cadmium (Cd), as well as microplastic particles composed of expanded polystyrene (EPS), were detected under controlled conditions simulating different types of water. Atomic absorption spectroscopy (AAS) confirmed the concentrations of the heavy metals studied, supporting machine-learning classification of contaminated waters. Microplastics exhibited strong metal adsorption, influenced by the physicochemical properties of the water. Overall, AUC values above $90\%$ were obtained for seven different models, demonstrating the reliability of the electronic tongue in conjunction with classical machine learning techniques for detecting these elements. Full article

Selenium plays a crucial role in estuarine biogeochemistry, balancing essential nutrient functions with potential environmental toxicity. This study examines the seasonal distribution of dissolved Se species, including volatiles, in the Adour estuary in relation to anthropogenic influences. To characterize major Se inputs from upstream watersheds to downstream tributaries, water samples were collected at low tide during three different seasons in upstream freshwaters, industrial/urban effluents and downstream estuarine waters. A tidal-cycle sampling campaign was conducted under low discharge conditions to assess Se dynamics during downstream estuarine mixing. Total dissolved Se (TDSe) concentrations ranged from 71 (pristine river) to 656 ng L⁻¹ (industrial/urban-impacted tributaries). TDSe correlated strongly with nitrate (r = 0.84) in upstream waters, indicating significant agricultural and livestock contributions at the watershed scale. Selenate was the dominant species, followed by Se(-II+0) fraction and selenite. Volatile Se compound concentrations varied from 51 to 2757 pg L⁻¹. Seasonal changes suggest that Se speciation is mainly controlled by watershed inputs derived from land use (agricultural and livestock practices) rather than downstream estuarine inputs. This speciation study further indicates that Se reactivity/bio-availability in estuarine systems can be largely influenced by anthropogenic activities, although further characterization of the aqueous reduced Se fraction is still needed. Full article

Irrigation-silted soil in Ningxia represents a unique, anthropogenically modified agroecosystem, beneficial for regional food security. Yet, how different agricultural management techniques influence soil microbiome diversity remains poorly explored. Full-length amplicon sequencing (16S rRNA and ITS) was applied to assess the effects of vegetable and maize cultivation, relative to an uncultivated wasteland control, on soil bacterial and fungal community. Cropping patterns significantly influenced microbial alpha diversity, with contrasting effects on bacterial and fungal communities. Specifically, bacterial diversity peaked in vegetable fields, while fungal diversity was highest in maize fields. Both the bacterial and fungal community structures differed markedly among the three land-use types (p < 0.01). Although Pseudomonadota (among bacteria) and Ascomycota (among fungi) were the dominant phyla across all soils, each land-use type harbored distinct biomarkers. For example, vegetable fields facilitated the enrichment of the genus Fusarium, whereas maize fields were characterized by both Pseudomonadota and diverse saprotrophic fungi. Based on functional prediction, sulfur oxidation and cellulose decomposition were enhanced in soil with vegetable cultivation, while maize cultivation promoted relatively broader metabolic activity and enriched arbuscular mycorrhizal fungi compared with the control. Agricultural practices act as selective filters shaping soil microbial assembly and function, which provide a theoretical foundation for sustainable management strategies aimed at preserving soil health. Full article

Understanding how the development of large-scale coal mining bases affects river hydrochemistry is a key scientific issue in the field of water environment research. In this study, the Qingyang–Binzhou section of the Jinghe River Basin was selected as the study area, and a total of 29 water samples were collected in April 2025 from the upper to lower reaches of the coal mining base. Hydrochemical analysis, ion ratio methods, and the positive matrix factorization (PMF) model were comprehensively applied to systematically characterize the hydrochemical features and identify the pollution sources in the river under the influence of large-scale coal mining activities. The results showed that the mean concentrations of Na⁺, SO₄²⁻, Cl⁻, and total dissolved solids (TDS) in the mainstream were as high as 414 mg/L, 728 mg/L, 226 mg/L, and 1636 mg/L, respectively, reflecting a significant impact of coal mining activities on river hydrochemistry. Four spatial variation patterns were observed along the river: the first pattern was characterized by “stable in the upper reaches, sharp increase in the middle reaches, and fluctuating increase in the lower reaches,” represented by Na⁺ and SO₄²⁻; the second pattern showed “stable in the upper reaches, slight decrease in the middle reaches, and fluctuating decrease in the lower reaches,” represented by pH; the third pattern exhibited “fluctuating in the upper reaches, sharp decrease in the middle reaches, and extremely low levels in the lower reaches,” represented by NO₃⁻; and the fourth pattern was dominated by irregular variations controlled by nitrogen transformation processes, represented by NH₄⁺ and NO₂⁻. Gibbs plots and ion ratio diagrams indicated that the hydrochemistry of sites unaffected by coal mine drainage was primarily controlled by rock weathering, whereas contaminated samples shifted toward the evaporation-concentration zone and extended beyond its typical range, reflecting an “anthropogenic salinization effect” induced by the input of mine water superimposed on the arid to semi-arid climatic background. The PMF model identified three main pollution sources: coal mining and mine water discharge (48.3%), domestic sewage (30.2%), and carbonate weathering (21.5%). This study reveals the significant modification mechanism of river hydrochemistry by large-scale coal mining base development, providing a scientific basis for targeted water pollution control in the Jinghe River Basin and for water environment management in similar mining areas. Full article

Carbon use efficiency (CUE) is a critical indicator of ecosystem carbon sink capacity. However, the nonlinear response of CUE to complex environmental drivers remains poorly understood in subtropical humid regions. This study analyzed the spatiotemporal dynamics of vegetation CUE in the Poyang Lake Basin (PYLB) from 2001 to 2020 and quantified the influence of natural and anthropogenic factors using XGBoost-SHAP and GeoDetector models. The results showed that: (1) The average annual CUE in the PYLB was 0.455, exhibiting a declining trend, with a linear rate of −0.001524 yr⁻¹. (2) SHAP analysis revealed that the association between LAI and CUE exhibited a non-monotonic transition at a threshold of approximately 1.80. Specifically, while lower LAI levels were positively correlated with CUE, this relationship shifted to a negative trend as LAI exceeded the threshold, demonstrating a phase-specific coupling pattern across the canopy density gradient. For hydrothermal drivers, CUE exhibited localized downward fluctuations when precipitation was between 1700 and 2700 mm and temperature ranged from 15.0 to 18.0 °C. (3) GeoDetector analysis indicated that LAI was the dominant individual factor controlling the spatial heterogeneity of CUE (q = 0.471), and its interaction with TEM exerted the strongest synergistic effect (q = 0.493). These results emphasize the necessity of considering nonlinear thresholds and factor interactions when evaluating ecosystem carbon budgets in changing climates. Full article

Background: Exposure to anthropogenic and/or natural (e.g., herbicides or mycotoxins) endocrine-disrupting chemicals (EDCs) has been linked to several reproductive disorders. Glyphosate (GLY), a common agricultural agent, is a potential element of the exposome that bioaccumulates and has potential endocrine and oxidative stress-related effects. However, data on its presence in the human ovarian microenvironment remain limited. Our study examined GLY levels in follicular fluid (ff) and serum and their relationships with oxidative stress markers, reproductive hormones, and stress hormones in women undergoing in vitro fertilization (IVF). Methods: 50 women undergoing controlled ovarian stimulation participated. Serum and ff samples were routinely collected during oocyte retrieval. GLY, related hormones (e.g., cortisol, estradiol-E2, anti-Müllerian hormone-AMH, and melatonin-MT), an oxidative stress marker malondialdehyde (MDA), antioxidant enzyme activities, total antioxidant capacity, and co-occurring natural pollutant mycotoxin levels were measured. Relationships between GLY levels and these mediators were assessed using correlation and regression analyses. Results: GLY was detected in both serum and ff at similar concentrations (0.038 ± 0.006 ng/mL vs. 0.045 ± 0.006 ng/mL; p = 0.414). Follicular GLY levels showed a positive association with MDA (Spearman’s r = 0.4487, p < 0.001), explaining 28.6% of the variability in follicular MDA. Serum GLY was positively associated with serum (β = 40.26, p = 0.0058) and follicular E2 (r = 0.29, p = 0.042). Serum GLY levels were negatively correlated with cortisol (β = −0.0188, p = 0.020). A slight correlation between follicular GLY and MT was observed (p = 0.03). No associations were found between GLY levels and age, body mass index, AMH, the recombinant gonadotropin dose used, antioxidant enzyme activities, follicle count, oocyte yield, or embryo viability. Conclusions: This study might be the first to demonstrate the presence of GLY of exposome in human ff, indicating that environmental exposure to GLY may reach the oocyte microenvironment. The correlation with lipid peroxidation suggests GLY could contribute to follicular oxidative stress. The associations with E2 and cortisol point to potential endocrine-disrupting effects. While no direct impact on IVF outcomes was observed, findings suggest low-level exposure to GLY could influence ovarian physiology through specific biochemical mechanisms. Full article

This study evaluated the seasonal variability, origin, and ecological risk of heavy metals in the Pom–Atasta lagoon system, a tropical estuary in southeastern Mexico subject to increasing anthropogenic pressure. The main objective was to determine how seasonal changes influence the distribution, bioavailability, and risk of metals in sediments and benthic organisms. Thirty sampling stations were monitored during dry, rainy, and north wind seasons. Sediment concentrations of As, Cd, Cr, Ni, Pb, and V were measured, and bioaccumulation was assessed in the bivalve Rangia cuneata. Ecotoxicological risk was evaluated using the Adverse Effects Index (AEI), Toxic Risk Index (TRI), and potential ecological risk index (ERI). The results showed higher metal concentrations during the rainy and north wind seasons, likely due to increased runoff and sediment resuspension. Cr and Ni exhibited the highest enrichment, with values from 115.0 to 130.4 µg g⁻¹ and from 60.5 to 75.9 µg g⁻¹, respectively. Ni showed the highest bioaccumulation factor (BSAF > 1.51) in R. cuneata, indicating high mobility and environmental availability. Weak correlations among some metals (As, Cr, and Pb) suggest mixed natural and anthropogenic sources. TRI values indicated low to moderate toxic risk, and ERI classified most sites as low risk (ERI < 60) at several stations. Organic carbon levels remained within tolerable limits (<10%) for benthic fauna. These findings highlight the role of seasonal dynamics in metal distribution and confirm R. cuneata as a suitable bioindicator for monitoring ecological health in tropical estuarine systems. Full article

Ecological risk assessment of ecosystems facing anthropogenic pressures informs coastal management. This study evaluated the ecological risk of ecosystems in two coastal municipalities in the Gulf of California, Mexico. The coastal area under study spans 175 km of coastline and includes various ecosystems, as well as the cities of Guaymas and Empalme (~160,000 inhabitants). Ecological risk was assessed by surveying the opinions of experts on local and global activities and influences (climate change), the ecological consequences of hazards, and the resilience (fragmentation) and natural recovery of ecosystems. In addition, potential synergies between human activities and the effects of climate change were identified. The results showed that the main threats are discharges of raw or poorly treated wastewater into the sea, the generation and dumping of garbage, and illegal fishing. Wastewater discharges represent the local threat that interacts most intensively with the effects of climate change. Mangroves, coastal water bodies, and rocky shores face the greatest ecological risk due to continuous exposure to anthropogenic threats, poorly planned urban growth, and industrial development. Approximately 20% of the coastal zone is estimated to correspond to the metropolitan areas of Guaymas and Empalme, where the greatest ecological risk occurs, and these represent opportunities to promote coastal management processes aimed at ecosystem restoration and planned urban development to prevent the loss of coastal ecosystem functions and the services they provide to society. Full article

Vegetation spring phenology in drylands is sensitive to climatic and anthropogenic pressures, yet the nonlinear responses of the start of the growing season (SOS) across different vegetation types remain inadequately quantified. Here, we extracted the start of the growing season from 2001 to 2020 Moderate-Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series for stable vegetation areas on the Mongolian Plateau (MP) and applied Extreme Gradient Boosting (XGBoost) models with Shapley Additive Explanations (SHAP) analysis to six environmental drivers—precipitation, temperature, windspeed, livestock density, population density, and elevation—across forests, shrublands, and grasslands. The SOS displayed pronounced spatial heterogeneity, with earlier onset in northern forests and shrublands and delayed onset in southern arid grasslands. Forests and shrublands exhibited significant advancing trends of 6.8 and 6.4 days per decade, respectively, while grasslands showed no significant trend. Temperature dominated the SOS variability across all vegetation types, yet the relative importance of other drivers varied; windspeed notably influenced forests, whereas precipitation and elevation were critical for grasslands and shrublands. SHAP analysis revealed strong nonlinearities and threshold effects, including a U-shaped temperature response and a 350 mm precipitation threshold in grasslands, beyond which the SOS responses markedly shifted. These results highlight the vegetation-specific and nonlinear nature of phenological regulation in drylands, suggesting that phenology prediction and ecosystem monitoring should explicitly incorporate vegetation type and threshold-based climatic responses. Full article

With the global increase in microplastic pollution, even environments considered pristine have shown signs of being affected by these contaminants. In this context, it becomes essential to conduct studies that identify and quantify the presence of microplastics in remote regions such as Antarctica. This continent is particularly relevant due to its low anthropogenic influence and its essential role in regulating planetary ecosystems and biodiversity. In this study, 49 Antarctic samples were analyzed using pretreatment techniques with NaCl and ZnCl₂ saline solutions, followed by fluorescence microscopy using Nile Red dye to estimate the microplastic abundance index. Both solutions showed good performance in the separation and identification of particles. Approximately 37% of the samples showed contamination by potential microplastics (PMPs), with a higher concentration of particles retained on paper filters and fibers observed in the supernatants. The results indicate that the presence of MPs in Antarctica is irregular and not ubiquitous, differing from other studies that suggest a wider distribution. It is speculated that the observed contamination results from oceanic transport from other regions of the planet and from sources associated with human activities on the Antarctic continent (e.g., tourism and research). Full article