Environmental Monitoring and Assessment最新文献

To investigate the spatiotemporal variability of lead (Pb) in mining environments, 100 topsoil samples were collected from different locations across a semi-arid mining district in western Iran over a 4-month monitoring period, with sampling conducted at different sites in each month. Key explanatory variables, namely, pH, electrical conductivity (EC), soil organic carbon (SOC), zirconium (Zr), and elevation and slope as topographic attributes alongside normalized difference vegetation index (NDVI), were integrated into the Geographic and Temporal Weighted Regression (GTWR) framework. Pb was selected because of its strong association with mining activities, high environmental persistence, and ecological significance. The effectiveness of the GTWR model was evaluated and compared with Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR) and Temporally Weighted Regression (TWR) using multiple statistical evaluation metrics and model-fitting criteria. In addition, the ecological implications of Pb contamination were assessed using the risk quotient (RQ) index. The evaluation metrics demonstrated the superiority of GTWR (R² = 0.79) over the other models. The results indicate that Pb distribution was influenced by geological, geochemical, and biological factors, with Zr showing a predominantly spatially positive association, EC exhibiting spatially variable effects, and NDVI and pH showing relatively stable temporal associations with Pb. Furthermore, RQ values exceeded the ecological threshold throughout the study area, indicating widespread potential ecological risk. Integrating GTWR with ecological risk assessment provides a useful framework for characterizing heterogeneous Pb patterns and supporting the identification of priority areas for environmental monitoring and risk management in mining-affected landscapes.

Ground-level ozone (O₃) has become a major challenge for air quality improvement in China, but its short-term variability is controlled by complex interactions among pollutant persistence, precursor conditions, and meteorological factors. In this study, hourly air quality observations and ERA5 reanalysis meteorological data for an urban monitoring site in Wuhan during 2019-2025 were integrated to evaluate O₃ temporal variability and interpretable machine learning prediction. Three models, namely, deep neural network (DNN), random forest (RF), and extreme gradient boosting (XGBoost), were compared using baseline and lag-enhanced feature sets, and SHapley Additive exPlanations (SHAP) were used to interpret predictive contributions. O₃ remained at relatively high levels during 2019-2025, with exceedances of the national grade II standard in 2019, 2023, and 2024, while most primary pollutants generally declined. O₃ exhibited a unimodal diurnal cycle with afternoon peaks at 14:00-16:00 and a seasonal pattern of summer > spring > autumn > winter. The enhanced XGBoost model achieved the best short-term prediction performance, with R² = 0.9756 and RMSE = 6.35 μg m^-3 on the test set. SHAP analysis showed that the 1-h lagged O₃ concentration was the dominant predictor, indicating strong short-term persistence rather than independent chemical forcing. NO₂ and lagged NO₂ showed negative predictive contributions, consistent with the expected role of NO titration under high-NOₓ conditions, whereas temperature and radiation-related variables showed positive contributions. These results suggest that interpretable machine learning can help identify the statistical conditions associated with O₃ variability, but the absence of direct VOC observations means that O₃ sensitivity and VOC-related control implications should be further verified using VOC measurements or chemical transport/observation-based modeling.

Riverine hypoxia, oxygen depletion in flowing waters, poses ecological risk, yet its spatial and temporal dynamics remain poorly characterized. This study presents a novel risk-based spatiotemporal framework for assessing riverine hypoxia across Indian river systems, utilizing 18,976 site-year summary data points (annual minimum, mean, maximum) across 87 sub-basins over 17 years. We conceptualized 'contextual hypoxic risk' as the probability of summary statistics falling below a critical threshold (4.0 mg L⁻¹), distinguishing emerging, intermittent, and perennial hypoxic conditions. Hypoxic risks were estimated under an empirical Bayes (Poisson-Gamma hierarchical framework) to address overdispersion and stabilize standard error. Sub-basin-level aggregation mitigated site selection bias, yielding hydrologically meaningful and analytical units that facilitates policy decision. Of observations, 47% (8914) were emerging hypoxic events, 7% (1328) intermittent, and 1% (190) perennial. At least one severe hypoxic event (DO < 2.0 mg L⁻¹) occurred at approximately 25% of sites-significantly exceeding the global average (12.6%). Spatial analysis revealed pronounced heterogeneity, with hypoxic risk ranging from 0 to 50%, and northwestern and Gangetic sub-basins exhibiting high hypoxic risks and faster intensification. While hypoxic occurrences revealed upward national trend, hypoxic risk showed transient patterns. Space-time interaction analysis indicated statistically significant accelerating risk trajectories-particularly for perennial and intermittent types-across six key sub-basins. By coupling probabilistic risk modelling with spatial smoothing and trajectory steepness diagnostics, this framework quantifies both spatial variability and temporal intensification of riverine hypoxia. The scalable, reproducible framework is applicable to other developing regions. Findings underscore urgent need for adaptive, sub-basin-scale management to prevent progressive establishment of chronic hypoxic regimes in India's river systems.

Plastic pollution raised great environmental concerns due to its persistence and widespread presence. To model ecological impacts, such as ingestion by wildlife, information on the abundance and dimensions of plastic particles is fundamental. Our study examined the relationships between size dimensions (length, area, circumference) of individual particles and the length of particles, their concentration, and cumulative surface area. Plastic particles were collected with trawl nets from upstream and downstream sites in two Dutch rivers in 2023 and 2024. Particle dimensions, including length (defined as the longest axis), surface area, circumference, and the number of particles, were measured. Geometric means of particle concentrations and cumulative surface area concentrations were calculated for equal-sized bins based on length and plotted against particle length on a log-log scale. Reduced major axis and ordinary linear least squares regressions determined the power relationships between size dimensions of individual particles. For length-based bins, we evaluated how concentrations and total surface area co-varied with length classes. Size dimensions were strongly and positively related, indicating differences in shape across size classes. Contrary to previous research, the length of plastic particles was not strongly correlated to their concentration in the Meuse River and varied between sampling locations. The cumulative surface area concentration increased significantly with length. The findings of the study should be viewed with caution, as they were based on two Dutch rivers. Even greater caution is warranted for the relationships between particle length and concentration, and between particle length and cumulative surface area, as they were based solely on measurements in the Meuse.

Doochi, a traditional Korean dish made from boiled shark skin and intestine, may be a source of mercury exposure. In 2013, total mercury was measured in untreated fragments of boiled shark skin from 32 purchased servings of Doochi and of 32 raw skins sold as its ingredient. In 2022, another serving was separated into the skin and intestine, each fully homogenized and analyzed in triplicate at an accredited laboratory. The geometric mean was 0.349 µg/g in the boiled skin fragments and 0.122 and 0.137 µg/g in the outer and inner layers of the raw skin. After homogenization, the boiled skin contained 2.667-2.882 µg/g and the intestine 0.295-0.333 µg/g. The homogenized boiled skin exceeded the European total mercury limit of 1.0 µg/g for shark, and its estimated methylmercury concentration exceeded the Korean limit of 1.0 µg/g for deep-sea fish. Fragment concentrations varied 167-fold and were more dispersed than in raw skin (Levene's test, p < 0.001). Hazard quotients against the methylmercury reference dose were 0.15 to 0.57 under traditional ceremonial consumption, and exceeded 1 at 10 to 36 servings per year depending on the assumptions; the corresponding intakes were 7 to 25% of the provisional tolerable weekly intake under that pattern and reached it at 22 to 81 servings per year. Under the assumptions of this analysis, exposure at the traditional consumption frequency was below the reference dose, but frequency warrants attention as the dish becomes more widely available, particularly for individuals of lower body weight.

Tarballs, the weathered residues of petroleum hydrocarbons, are a recurring feature along the west coast of India, yet their role as carriers of toxic and carcinogenic compounds remains insufficiently quantified. This study presents a comprehensive assessment of the distribution, composition, abundance and carcinogenic potential of polycyclic aromatic hydrocarbons (PAHs) in pelagic and beached tarballs collected along the Eastern Arabian Sea and the adjacent coastal regions (2018-2024). Results indicate that both pelagic and beached tarballs are dominated by low and medium-molecular-weight(LMW) PAHs, with phenanthrene consistently identified as the most abundant compound. Total PAH concentrations were markedly higher in pelagic tarballs than in beached tarballs. Diagnostic PAH ratios and principal component analysis suggest that the observed differences in PAH composition between pelagic and beached tarballs are consistent with the effects of environmental weathering. Assessment based on benzo[a]pyrene toxic equivalents (BaP-TEQ) and carcinogenic PAH fraction (cPAH%) indicates higher carcinogenic potential in pelagic tarballs, whereas beached tarballs exhibited greater spatial variability in PAH composition. Despite evidence of weathering, carcinogenic PAHs persisted in both tarball types, with some locations exhibiting notably elevated contributions. Overall, the study demonstrates that pelagic tarballs function as mobile vectors of carcinogenic hydrocarbons in the marine environment, while beached tarballs act as persistent secondary sources of contamination.. These findings highlight the potential environmental concern associated with tarball-derived PAHs and underscore the need for sustained monitoring and management of petroleum residues along coastal ecosystems.

The European Union Water Framework Directive (WFD) requires member states to assess the ecological status of surface waters using biological quality elements (BQEs). Although the WFD includes intercalibration procedures to harmonise class boundaries, differences between national assessment systems may affect the comparability of ecological status classifications, particularly in transboundary rivers. This study evaluated the consistency of Portuguese and Spanish ecological status assessments in 32 water bodies across Iberian transboundary rivers in the Minho, Lima, Douro, Tagus and Guadiana basins, using data collected between 2019 and 2021. Comparisons included fish, macrophytes, benthic macroinvertebrates and diatoms. Biological assemblages, ecological quality ratios (EQRs) and ecological quality classifications were analysed. Results differed markedly among BQEs. Fish showed no significant differences in assemblage composition or EQR values between countries and a moderate positive correlation in ecological quality classifications. Macroinvertebrates displayed weak compositional separation, no differences in EQR values and a weak, nonsignificant positive correlation between countries. Macrophytes showed significant compositional differences despite similar EQR distributions and a weak, nonsignificant positive correlation in ecological quality classifications. Diatoms showed the strongest divergence, with clear assemblage separation, higher EQR values in Spain and a very weak, nonsignificant negative correlation between countries. Final ecological classifications also showed a weak, nonsignificant positive correlation between countries. These findings show that formal intercalibration alone does not guarantee operational comparability in shared river systems. Cross-border assessment consistency depends strongly on the BQEs considered and on methodological differences between national monitoring systems, highlighting the need for improved harmonisation of monitoring procedures and taxonomic practices.

Contamination by microplastics is an emerging environmental problem that is widely distributed across continental aquatic environments and may cause ecological impacts. This study evaluated the occurrence, concentration, and chemical and morphological characteristics of microplastics in surface waters and sediments from Lake Canaçari, comparing two areas with different land-use patterns within a floodplain system in the Central Amazon. Microplastics were detected in all sampled areas. In surface water, concentrations ranged from 0 (no microplastic particles detected in one sample) to 1,000 microplastics·m⁻³ (405 ± 298 microplastics·m⁻³), while in sediments, they ranged from 7 to 307 microplastics·kg⁻¹ (77 ± 104 microplastics·kg⁻¹). No significant differences in microplastic concentrations were observed between fishing and human-settlement areas. The particles were predominantly blue fibers (< 1,000 μm). Among the spectroscopically analyzed particles, polyethylene was the most frequently identified polymer, while copper phthalocyanine pigments, including Pigment Blue 15 and Pigment Green 7, were also detected by FTIR and/or Raman spectroscopy. Overall, the results suggest that Lake Canaçari may act as a transport pathway, redistribution zone, and retention compartment for microplastics; however, seasonal sampling is needed to confirm how these processes vary throughout the hydrological cycle. These results reinforce the role of Amazonian floodplain systems in the regional dynamics of microplastics and highlight the need for monitoring and management strategies that incorporate seasonal hydrological connectivity at the basin scale.

Increasing metal contamination in aquatic ecosystems threatens environmental sustainability, aquatic organisms, and public health by promoting the accumulation of toxic elements in fish tissues. This study evaluated the bioaccumulation of toxic metals and essential elements in the liver, gills, and muscles of wild and farm-reared Cirrhinus mrigala collected from the River Jhelum and local fish farms, respectively. Fish health was assessed through hematological, biochemical, and histopathological analyses. Results showed higher metal concentrations in wild fish compared with farm-reared specimens. The liver exhibited highest accumulation, followed by the gills and muscles. Among essential elements, calcium (Ca) and magnesium (Mg) were the most abundant, whereas nickel (Ni), chromium (Cr), and arsenic (As) were the predominant toxic metals. Wild fish exhibited marked hematological and biochemical alterations, while histopathological analyses revealed severe tissue damage in the gills, liver, and muscles. Human health risk assessment indicated minimal risk from farm-reared fish consumption, whereas wild fish from the River Jhelum may pose significant health concerns. Overall, the study highlights the ecological deterioration of the investigated river system and emphasizes the urgent need for effective mitigation strategies, including improved waste management practices, continuous environmental monitoring, and regular limnological assessments to safeguard aquatic ecosystems and public health.

Rapid, nondestructive assessment of particulate mass on leaves could support monitoring of urban vegetation, but models developed for one species may perform differently on another. We evaluated transfer from Ligustrum japonicum 'Howardii' (180 leaves) to Photinia × fraseri 'Red Robin' (45 leaves), sampled in park, street, and industrial zones in Nanjing, China. Reflectance spectra were measured before particle removal, and mass per unit leaf area recovered by washing and filtration was used as the quantitative reference. We evaluated two tasks separately: classification of functional-zone labels and prediction of particulate mass. Models were fitted on the source species, and candidate preprocessing and wavelength schemes were compared on the target samples. Joint exclusion of selected endpoint and water-related intervals yielded 91.1% target classification accuracy among the tested schemes. For mass prediction, the full-spectrum model performed best among the tested alternatives, but direct predictions for all 45 target leaves showed limited absolute agreement (R² = 0.265) and positive bias. Linear output correction used 15 target reference leaves, with five per zone, and was tested on the remaining 30 leaves in each of 50 repeated splits. Corrected test R² averaged 0.797 ± 0.042. The results support reference-assisted monitoring within this species pair. Unmeasured deposit and leaf properties limit mechanistic interpretation. Reference uncertainty, leaf dependence, and target-based scheme selection require further validation before broader use.