Search Results (3,935)

The relevance of this study is determined by the need for a scientifically grounded assessment of environmental risks associated with rocket launches and by the necessity of ensuring environmental safety in areas potentially affected by space activities. Comprehensive monitoring of rocket-stage impact zones and adjacent populated areas is especially important because pollutant distribution depends on natural, climatic, and spatial factors. This study assesses the environmental impact of the “Soyuz-2.1a” launch with the “Progress MS-29” cargo spacecraft in Kazakhstan using integrated field monitoring, laboratory analysis, and geoinformation methods. The work should be interpreted as a single-event environmental monitoring assessment, while historical monitoring data from 2020–2023 were used only as a retrospective comparative background for the U-25 impact area and were not included in the main BACI statistical analysis. The study covered the launch site, adjacent populated areas, and the U-25 stage impact zone. A before–after control-impact (BACI) design with distance stratification and consideration of wind direction was applied to identify post-launch changes. Measurements below the limit of detection and limit of quantification were processed using censored-data methods, including Regression on Order Statistics (ROS) and the Kaplan–Meier estimator. Spatial analysis was used to generate concentration fields, contour maps, and risk zones, revealing an anisotropic distribution of environmental stress in the downwind sector. An integrated hazard quotient (HQ) metric was applied to compare air, water, and soil conditions on a unified scale. The results indicate that the post-launch impact was localized and time-limited, with the greatest sensitivity observed in the soil component of the U-25 zone during the early post-launch period. Atmospheric air and water indicators remained within regulatory limits in populated areas. The proposed approach combines BACI monitoring, censored-data analysis, spatial modeling, and GIS-based visualization, providing a reproducible framework for the environmental assessment of rocket-stage impact areas. The practical recommendations include staged post-launch monitoring, temporary restriction of access to high-stress zones, primary reclamation of contaminated soil, and the use of WebGIS tools to support environmental decision-making. Full article

Remote alpine lakes on the Xizang Plateau are important archives for tracing the long-range atmospheric transport (LRAT) of persistent organic pollutants, yet historical records of polybrominated diphenyl ethers (PBDEs) from this region remain scarce. The main objective of this study was to reconstruct the historical record of PBDEs in Yamzho Yumco sediments and to evaluate whether this record reflects source evolution, atmospheric transport, deposition, and post-emission environmental fractionation in a remote alpine receptor system. To achieve this objective, 17 PBDE congeners were determined in a ²¹⁰Pb- and ¹³⁷Cs-dated sediment core spanning 1930–2023. Σ₁₇PBDE concentrations ranged from 5.80 to 263.13 pg/g dw, and depositional fluxes ranged from 2.67 to 121.04 pg/cm²/yr, both showing a marked increase after the 1970s and remaining elevated after 2000. Lower-brominated congeners, especially BDE-47, dominated the core, whereas nona- and deca-BDEs appeared mainly in recent sediments, indicating progressive source evolution in recent decades. Tri- to penta-BDEs remained the dominant homologue fraction throughout the record, while elevated post-2000 BDE-47/BDE-99 ratios point to congener-selective environmental fractionation during atmospheric transport and deposition. Together, these results suggest that Yamzho Yumco sediments preserve not only the history of regional PBDE input, but also the coupled imprint of source evolution, transport-related fractionation, and delayed environmental response in a remote high-altitude receptor system. This study highlights the value of Xizang Plateau Lake sediments for process-based interpretation of POP fate in mountain environments. Full article

Biomass burning is a major source of atmospheric pollution. However, rapid and quantitative assessment of particulate matter in smoke plumes remains challenging, owing to the physical uncertainties, limited coverage, and labor-intensive quality control of conventional monitoring approaches. Existing image-based deep learning methods typically address either smoke detection or air quality assessment separately. To address this gap, we develop a Unified Smoke Detection and Aerosol Estimation Framework (SDAF), a three-stage deep learning approach evaluated using a smoke-rich airborne dataset. The framework integrates smoke localization with PM₁ estimation by combining a YOLOv11-based detector with an optimized convolutional neural network. The model achieves high accuracy under in-plume conditions (R² of 0.985). However, its performance degrades under out-of-plume conditions due to substantial differences in visual features between the two domains. Consequently, direct across-domain transfer performs poorly, whereas region of interest (ROI)-level fine-tuning substantially improves performance for out-of-plume images (R² of 0.621). Despite these promising results, fundamental limitations remain. Image-based PM₁ estimation is intrinsically ill-posed due to the non-unique mapping between visual observations and particle mass. Overall, the framework enables an integrated workflow from smoke localization to quantitative PM₁ estimation using image data alone, offering a scalable solution for biomass burning monitoring and air quality assessment while highlighting the fundamentally indirect nature of image-based PM₁ inference relative to spatially resolved retrievals. Full article

The interaction between airborne allergens and environmental microplastics is an emerging concern in the context of increasing plastic pollution and allergic disease prevalence. In this study, we investigated the molecular interaction between Cry j 1, the major allergen of Japanese cedar (Cryptomeria japonica) pollen, and polyethylene terephthalate (PET) microplastic surfaces using all-atom molecular dynamics simulations integrated with computational epitope selection analyses. The simulations showed that Cry j 1 adsorbs onto PET primarily through hydrophobic and van der Waals interactions, with residues Pro165, Ala227, Tyr228, and Val163 contributing prominently to surface association. Mapping of selected epitope regions indicated that several linear B-cell epitopes remained solvent exposed following adsorption, whereas two CD4⁺ T-cell epitope regions (T5 and T6) contributed more directly to PET interaction. PET adsorption was accompanied by moderate changes in conformational dynamics, including reduced residue-level flexibility and localized secondary-structure adjustments, while the overall protein fold remained structurally stable throughout the simulation. Small decreases in radius of gyration and solvent-accessible surface area suggested mild adsorption-associated compaction rather than major unfolding. These findings indicate that PET association can influence the structural dynamics and interfacial behavior of Cry j 1 without extensive disruption of its global architecture. Because the study is entirely computational, the immunological implications remain hypothetical and require experimental validation. Nevertheless, this work provides a molecular-level framework for understanding how airborne microplastics may influence allergen behavior and protein-surface interactions in polluted atmospheric environments. Full article

A three-year (January 2020–December 2022) daily dataset of 16 polycyclic aromatic hydrocarbons (PAHs) collected in parallel with PM_2.5 and a suite of meteorological variables at a coastal Mediterranean urban site in southern Italy (Pomigliano d’Arco, Campania) is presented and analysed. Raw PAH time series were decomposed into a long-term trend component (LT), a seasonal component (ST), and a residual component (RT) using an iterative missing-value-robust Kolmogorov–Zurbenko (KZ) moving-average filter. Spearman rank correlations between PAH concentrations and four meteorological predictors (mean temperature, relative humidity, mean wind speed, and maximum wind speed) were computed for each congener. Diagnostic molecular ratios—Fla/(Fla + Pyr), BaP/BghiP, Indeno[1,2,3-cd]pyrene/(IcdP + BghiP), and BaA/(BaA + Chr)—were evaluated seasonally and interpreted jointly with an information-theoretic Bayesian mixture modelling procedure (SNOB/MML) and with the documented susceptibility of some PAH ratios, especially BaP-containing ratios, to atmospheric ageing, phase repartitioning and summer photodegradation. Total PAH concentrations (sum of 16 congeners) ranged from <1 ng m⁻³ in summer to 46 ng m⁻³ during winter high-pollution episodes, with BaP peaking at ≈6.7 ng m⁻³. Because BaP was measured in the PM_2.5 fraction, comparisons with the EU annual target value of 1 ng m⁻³ established for PM₁₀-bound BaP are treated as indicative context only, not as formal compliance statements. Pronounced seasonal variability was driven primarily by residential heating emissions, and the incremental lifetime cancer risk (ILCR) for inhalation exposure reached $1.03\times {10}^{-4}$ (95% CI: $0.88$–$1.20\times {10}^{-4}$) during the heating season under a continuous outdoor-exposure worst-case scenario. The absolute ILCR magnitude is conditional on the selected TEF scheme and on the adopted BaP unit-risk coefficient; under an additional indoor-dominated scenario (16 h day⁻¹, infiltration factor 0.6), the corresponding risk remained above the conventional ${10}^{-6}$ benchmark. An anomalous near-background PAH signal during spring 2020 is attributed to the COVID-19 national lockdown, which reduced total PAH concentrations by approximately 85% relative to the seasonal component predicted by the iterative moving-average filter for the same calendar window. Source apportionment via diagnostic ratios identifies residential/biomass combustion as the dominant cold-season source and vehicular emissions as the prevailing warm-season source. These results provide a novel characterisation of PAH pollution dynamics in the undersampled southern Mediterranean and provide evidence to support targeted abatement policies. Full article

Atmospheric microplastics (AMPs), as a globally prevalent environmental pollutant, have attracted increasing attention from the academic community in the past decade. This study aims to systematically explore the historical background, development trajectory, and evolutionary trends of global atmospheric microplastic research through bibliometric analysis. Based on 1385 relevant studies retrieved from the Web of Science core collection, knowledge graph analysis was conducted using the CiteSpace and VOSviewer tools. The results indicate that research on AMPs has gone through three distinct stages: the budding exploration period (2014–2016), the steady growth period (2016–2019), and the explosive expansion period (2020–2025). In the initial stage, people lacked understanding of AMPs, with a low publication volume and research focused on “occurrence and source”. During the steady growth stage, the number of publications increased, and researchers’ research areas focused on source analysis. During the explosive growth stage, the number of publications reached its peak, and research on AMPs gradually developed from the initial description of phenomena and method development to a comprehensive research direction involving multiple regions, media, and methods. It is worth noting that China has the highest research output on AMPs globally and occupies a dominant position in atmospheric microplastics research. Therefore, this study establishes a knowledge framework for global atmospheric microplastics research, identifies current research gaps, and provides comprehensive references for subsequent academic exploration and environmental governance practices. Full article

The interplay between the environmental exposome and the cancer genome remains a critical gap in precision oncology. While somatic mutational signatures—genomic fossils imprinted by exposures such as ultraviolet radiation; tobacco smoke; and industrial pollutants—are well characterised for their etiological significance; their functional impact on therapeutic efficacy remains largely unexplored. We hypothesised that these environmental genomic scars induce distinct pharmacogenomic vulnerabilities and resistance mechanisms that vary by geographical exposure patterns. This study employs two complementary analytical frameworks. First, a linear regression-based pharmacogenomic screen across four datasets (GDSC1, GDSC2, CTRP, CCLE; 1001 cell lines, 31 cancer types) identified 608 statistically significant (p < 0.01) mutational signature–drug interactions, revealing that UV-associated signature SBS7a is associated with broad-spectrum therapeutic resistance, including to BRAF inhibitors (PLX-4720, p < 10⁻⁴), while pollution-driven oxidative stress (SBS18) is associated with sensitivity to p38 MAPK inhibition (VX-702, r = −0.45, p < 10⁻⁹). Second, an XGBoost predictive model trained exclusively on 33,679 GDSC2 records using a 1265-feature matrix integrating 40 SBS signatures, drug chemistry descriptors, proteomic features, and two satellite-derived environmental variables (NASA PM_2.5 and UV)—achieved R² = 0.7973 on a 20% holdout set (grouped cross-validation R² = 0.7296). SHAP analysis revealed that satellite-derived PM_2.5 (Zone_PM25) ranked 7th of 1265 features, exceeding all 40 individual SBS mutational signatures. Synthesising these findings with satellite-derived atmospheric data, we constructed an exploratory spatially interpolated risk surface spanning 122 nations, generating the hypothesis that uniform drug efficacy assumptions may not apply globally. These findings suggest that a patient’s environmental exposure history may constitute a measurable pharmacogenomic variable. This exploratory framework warrants validation in independent datasets and with individual-level geographic data before clinical application. Full article

Understanding the variations in the bidirectional reflectance distribution function (BRDF) and albedo over snow surface under various conditions is important for interpreting the surface–atmosphere processes of the cryosphere, and the kernel-driven model is among the most popular methods to obtain this information for a comprehensive analysis. Recently, the RossThick-LiSparseReciprocal-Snow (RTLSRS) model was developed to better characterize the anisotropic reflectance of snow and shows strong potential for integration into operational remote sensing algorithms for snow BRDF/albedo retrieval. To comprehensively test the ability of the RTLSRS model to reproduce snow reflectance, the fitting accuracy to different multi-angular data derived from ground, tower, aircraft, and satellite platforms across the full optical wavelength range were demonstrated in this study. Special attention in this study was directed to analyzing the model performance under extreme illumination observation geometries, particularly with respect to the retrieval accuracy and stability under large Solar Zenith Angles (SZAs) and different Relative Azimuth Angles (RAAs). The model performance for silt-polluted snow surface with different concentrations is also assessed to provide necessary supplementation, relative to “pure” snow surface in the previous study. The main findings of this study are summarized as follows: (1) The RTLSRS model exhibits strong robustness under various SZAs; even when the SZA exceeds 80°, the model maintains high accuracy in BRDF reconstruction, with root mean square error (RMSE) values below 0.05. (2) The model also demonstrates satisfactory inversion capability when observations deviate from the principal plane (PP); the model can achieve fitting accuracy with R² approaching 0.5 and RMSE below 0.05 for MODIS data. (3) In the spectral range below 1300 nm, the RTLSRS model effectively reconstructs the scattering characteristics of snow surfaces with light impurity levels (<20 g/0.5 m²). (4) The spectral shape of snow reflectance remains consistent across different view zenith angles (VZAs) in general. However, the variations caused by different SZAs can be as high as 38.49% and such SZA-induced difference can result in WSA estimation discrepancy of up to 63.43%. This comprehensive assessment further affirms and demonstrates the applicability of the RTLSRS model for the first time in fitting observations across different platforms with various optical wavelengths and geometries, and provides an improved understanding to analyze BRDF variations for the user community. Full article

Micro(nano)plastics (MNPs) represent a pervasive and escalating threat to global ecosystems and human health. This review provides a critical synthesis of MNPs’ exposure risks across marine, atmospheric, and terrestrial compartments, with a distinct emphasis on identifying cross-media linkages and methodological inconsistencies that limit current risk assessments. Within marine environments, pollution hazard indices reveal significant spatial heterogeneity, yet their utility is constrained by the absence of toxicity weighting and particle characteristic integration. Atmospheric exposure profiles show variable risks, and the MNPs’ concentration in indoor air (up to 15.8 particles/m³) is significantly higher than in outdoor environments, posing a greater inhalation risk to infants and children who spend more time indoors. A marked increase in MNPs’ concentrations within agricultural soils is identified, where the MNP content in mulched soils (average: 570.2 particles/kg) is more than twice that of non-mulched soils (259.6 particles/kg). Critically, studies have now detected MNPs within human tissues, including the blood, intestines, liver, kidneys, tonsils, and brain, highlighting an urgent need to elucidate their multi-organ toxicity mechanisms, with a novel synthesis of gut–brain axis disruption and transgenerational effects. By integrating exposure dynamics with mechanistic toxicity data, this review advances a cross-system framework that identifies priority research directions, namely standardized detection methodologies, combined pollutant toxicity, and cross-system toxicity mechanisms, which are essential for informing mitigation strategies amid this escalating public health crisis. Full article

Dioxins are highly persistent organic pollutants that exist in soil. Their hydrophobic and lipophilic characteristics facilitate long-term stability, posing high risks to the ecosystem and human health. They can be released by different sources, such as the incineration of waste materials, industrial activities, the production of pesticides, and natural or accidental events like forest fires. Dioxins accumulate in food chains and persist in the environment because dioxins are less volatile as well as chemically stable and can strongly bind to organic matter. The accumulation and persistence of dioxins in aquatic and terrestrial systems make them a significant threat to the environment, even at very low concentrations. This review explains the key sources of dioxin-contaminated soil, including industrial emissions and atmospheric deposition, and assesses the associated risks. The transport, places of contamination, and overall status of dioxins are also highlighted in this study. The review also examines the mechanisms of dioxin toxicity, focusing on their interference with hormonal functions and gene expression, as mediated through the aryl hydrocarbon receptor (AhR). This AhR activation leads to gene responses and causes immunotoxicity, endocrine disruption, and oxidative stress. Furthermore, various remediation strategies like biological, physical, and chemical remediation are discussed here as effective approaches for reducing ecological and health risks and promoting soil sustainability. Full article

Landscape pattern is closely associated with pollution in rapidly urbanizing watersheds, but most studies still focus on single pollutants or single environmental media. This study developed a watershed-based framework to compare coupled water and air pollution in the Liaohe River Basin, China. A total of 156 hydrologically connected sub-basins were used as common spatial units. Landscape metrics were calculated for 2000, 2010, and 2020. Total nitrogen and total phosphorus loads were simulated using the Soil and Water Assessment Tool, while annual mean PM_2.5 and O₃ concentrations were aggregated from gridded products to the same sub-basin scale. Coupling coordination degree was used to identify relative co-pollution patterns within the aquatic and atmospheric systems. GeoXGBoost with spatial block cross-validation was used to evaluate predictive performance, and GeoSHAP was used to interpret model-based predictor contributions. The aquatic coupled pollution index was predicted more accurately than the atmospheric index, indicating a stronger landscape association with nutrient coupling. Cropland proportion was the most stable predictor of aquatic coupling, whereas forest proportion was the most stable predictor of atmospheric coupling. These results suggest that water-oriented management should focus on cropland structure and ecological buffering, while air-oriented management should emphasize forest continuity and fragmentation control. The framework provides a spatially explicit basis for differentiated watershed management and territorial spatial planning. Full article

Volatile organic compounds can aggravate the atmospheric pollution and health risks due to their high toxicity and photochemical reactivity. Herein, a series of cobalt aluminate spinel catalysts with high efficiency was fabricated via a cost-efficient solvothermal method. Plentiful oxygen vacancies with negative charge were introduced adjacent to the octahedrally coordinated Co³⁺ species in CoAl₂O₄ catalysts, thereby generating the synergetic Co³⁺-oxygen vacancy (Ov) sites, which facilitated the rapid activation and migration of oxygen species. Accordingly, the superior catalytic activity was observed for 1Al-1Co even with lower cobalt due to the presence of abundant Co³⁺-Ov sites, revealing the predominant roles of synergetic sites in the toluene oxidation. Moreover, the 1Al-1Co catalyst exhibited the optimal intrinsic catalytic performance with the lowest activation energy of 161.2 kJ·mol⁻¹ and the highest specific toluene reaction rate of 3.18 × 10⁻⁵ mmol·h⁻¹·m⁻². In situ DRIFTS results further verified that oxygen vacancies and active Co³⁺ species could synergistically boost highly reactive oxygen species, which rapidly oxidize benzoate into maleic anhydride, achieving the efficient complete oxidation of toluene. Full article

In this study, we present a machine-learning approach—a land use random forest (LURF) model—to produce daily PM₁₀ concentration maps at a 1 km resolution across the Campania region for the year 2022. The model combines daily measurements from 13 ARPA Campania monitoring stations with a wide set of spatial and atmospheric information. The predictors include population, land cover, road network, ERA5 meteorological data, satellite aerosol observations from MODIS, output from the CHIMERE chemistry transport model, and a flag identifying days affected by Saharan dust transport. The model is trained and validated using a station-based cross-validation scheme that accounts for spatial correlation between sites. Under this scheme, the LURF reproduces observed concentrations with substantially smaller errors than the raw CHIMERE output (RMSE of 11.0 vs. 23.6 $\mathsf{\mu }$g m⁻³). CHIMERE concentrations and ERA5 meteorology emerge as the most informative predictors, while the dust flag specifically improves the representation of episodic high-PM₁₀ events. The resulting 1-km maps reveal clear urban–rural contrasts. They identify pollution hotspots in the Naples metropolitan area and along major motorways that are not visible in coarser model outputs. Probabilistic exceedance maps further show that meeting the future 2030 EU limit value of 20 $\mathsf{\mu }$g m⁻³ will be challenging across much of the metropolitan area. Overall, the proposed framework provides a low-cost, practical tool for high-resolution PM₁₀ exposure assessment, supporting epidemiological studies, environmental justice analyses, and air quality management in regions with complex terrain and limited monitoring coverage. Full article

The anthropogenic transformation of the steppe zone in the southern East European Plain has led to the destruction and catastrophic fragmentation of natural ecosystems. Due to the presence of highly fertile lands and the deposits of the Donetsk coal basin, up to 90% of the territory is occupied by agricultural and industrial activities, urban agglomerations, other settlements, and extensive transportation networks. The predominant use of introduced species in artificial plantings (within the city limits, the ratio of species to quantity is 7:3) leads to the widespread spread of alien species, further isolation of natural habitats, and their subsequent degradation. The problem of preserving natural ecosystems and restoring a stable balance in their functioning can be solved through the widespread introduction of native species into all types of plantings capable of serving as ecological corridors. In this regard, we analyzed the key characteristics of native tree and shrub species that determine their functional value. The results indicate that of the 85 native plant species, only two cannot be used because they carry pests and diseases dangerous to agricultural crops. The remaining 83 species are suitable for various planting types, based on a set of individual characteristics, and 29 of these are universal for all planting types. Outside urban ecosystems, these 83 native species can completely replace introduced species. Within urban ecosystems, the need for their combination remains. Despite a number of advantages identified in native species in conditions of anthropogenic pollution (relatively high viability, long lifespan, good resistance to mechanical stress), native species lack a number of categories of traits necessary for the more effective functioning of urban green infrastructure. Among them, there is an insufficient number of tall species (>25 m) and conifers, which are more effective in purifying and improving the health of the atmosphere, as well as beautifully flowering and generally highly decorative species necessary for recreational areas and other territories that, among other things, perform esthetic functions. Full article

Uncontrolled scrap tire fires represent high-intensity episodic emission events that pose severe toxicological threats to urban environments. This study employs atmospheric dispersion modelling to quantify the impact of a tire stockpile fire on a distal educational receptor, evaluating two distinct dynamic stages of the event: an initial high-intensity open flame scenario (E1, 4 h) and a prolonged smouldering/suppression scenario (E2, 6 h), induced by firefighting interventions. Results reveal extreme pollutant loading at the receptor site during E1, with PM₁₀ and SO₂ concentrations peaking at 23,766 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$ and 7821 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$ respectively, indicating an immediate risk of acute respiratory distress. The organic fraction was dominated by volatile organic compounds (VOCs) (8691 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$) and a ∑16 PAHs flux of 313.9 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$. Toxicological assessment identified Benzo[a]pyrene (BaP) as the primary driver of health hazards, contributing approximately 70% to the carcinogenic risk profile. A critical disparity was observed between Mutagenic Equivalency (MEQ) of 18.32 and Toxic Equivalency (TEQ) of 15.37, suggesting that standard monitoring significantly underestimates the biological threat to sensitive paediatric populations. These findings demonstrate that acute, oxygen-limited tire combustion creates a concentrated toxic slug of high-molecular-weight PAHs. The study underscores the necessity of integrating mutagenicity-based models into emergency response protocols to accurately safeguard vulnerable communities against the long-term toxicological legacy of elastomer thermolysis. Full article