Earth and Environmental Sciences

Lack of regular monitoring of water sources may lead to undetected contamination, posing serious health risks and necessitating regular water quality assessments. Sampling for physicochemical, microbial analyses, and online surveys across three higher education institutions was done to evaluate water quality. Spatiotemporal variations among physicochemical parameters showed that the pH, EC, and TDS decreased during the wet season, reflecting the dilution effect of rain. However, DO increased from 0.67 to 4.83 ppm, indicating better aeration. PCA showed seasonal variability, whereas the correlation matrix highlighted both positive and negative interrelationships between temperature-pH (- 0.25), DO-ORP (0.11), and TDS-EC (1.00). Potentially toxic metals were either negligible or not detected. Metagenomics revealed the presence of 29 bacterial phyla, 61 classes, 124 orders, 241 families, and 457 genera. Canonical correspondence analysis showed the influence of Mo, EC, salinity, and TDS on Bacteroidota, Chloroflexota, Cyanobacteriota, and Planctomycetota, whereas Verrucomicrobiota, Acidobacteriota, Chlamydiota, Candidatus Melainabacteria, Bdellovibrionota, and Deinococcota were affected by Ni, pH, and COD. Pathogen mapping revealed the presence of Vibrio, Pseudomonas, Enterobacter spp., etc., responsible for diseases such as cholera, diarrhea, and typhoid. Also, occupants' perception about the water quality emphasizes the need for better management of drinking water in HEIs.

Stream chemistry and ecosystem function are being transformed by abrupt acceleration of sulfide-mineral oxidation in permafrost-underlain headwater catchments of the Yukon and Mackenzie river basins-the two largest (sub)Arctic rivers in North America. Over the past decade, dozens of acidic (pH ~3) seepages have emerged in these headwaters, causing vegetation dieback and mobilizing metals at acutely toxic concentrations in receiving streams. Acid generated during sulfide-mineral oxidation also accelerates carbon dioxide emissions by driving carbonate-mineral dissolution. Downstream (sub)Arctic rivers show statistically significant multidecadal increases in sulfate concentrations, yet their metal concentrations remain stable because of attenuation and dilution processes. Headwater stream acidification signals a major perturbation in metal, carbon, and sulfur cycling linked to permafrost thaw with far-reaching consequences for water resources, northern communities, ecosystem health, and Earth's biogeochemical future.

The role of active faults in driving rock uplift is well known, but their influence on rock damage and erosional efficiency remains unclear globally. Using 1744 beryllium-10 ( 10 Be)–derived erosion rates, we show that erosional efficiency is elevated on average within ~15 kilometers of a fault trace and decreases with distance, up to ~100 kilometers. Reverse faults and those longer than 140 kilometers show the strongest effects. This length scale of decay suggests that tectonic damage extends beyond fault-core pulverization on primary faults, possibly including fracturing or grain-to-grain contact weakening due to seismic shaking and distributed deformation on complex fault networks. Machine learning identified fault proximity as a dominant control on erosional efficiency, exceeding precipitation and lithology, particularly when a measure of seismic shaking is included. These findings indicate that active tectonics are associated with erosion not only through uplift but also by enhancing erosional efficiency through long-range rock damage.

The uneven global distribution of plant diversity remains a fundamental question in biogeography. Using dated phylogenies of >300,000 plant species and ancestral biogeographical stochastic mapping, we show that in situ speciation is the predominant process underlying extant plant diversity and accounts for 78% of biogeographic events across realms. The Neotropic contributed 37% of in situ speciation, likely owing to its role as a center of species diversification. Dispersal between realms was less frequent (16% of events) but facilitated floristic exchanges, especially in the Eastern Hemisphere. Extinction was least frequent but more pronounced in East Asia. These findings support the tropical conservatism hypothesis in which many clades originated in the tropics and only recently expanded into temperate zones, where limited time and biome conservatism have restricted speciation and diversity.

facies derived from carbonate dissolution, with negligible saline influence from Triassic evaporites. Stable isotopes confirm exclusively meteoric recharge following a distinct altitude gradient, identifying a regional mixing zone that integrates convergent flows from both mountain domains. Crucially, a significant positive correlation between nitrate concentrations and tritium activity demonstrates that aquifer vulnerability is intrinsically linked to the rapid transmission of modern recharge. These findings underscore the necessity for differentiated management strategies that incorporate the specific hydrodynamic memory and transit times of these critical karst systems to ensure regional water security.

Groundwater contamination in industrial parks often involves overlapping inputs of nitrogen, chlorinated solvents, and dissolved salts, making source identification difficult. In this study, 45 shallow groundwater samples from a typical industrial park on the northern margin of the Hohhot Basin were investigated using hydrochemical analysis, PMF, and nitrate dual isotopes coupled with MixSIAR. The results showed pronounced salinity enrichment, high mineralization, elevated ammonium, and chlorinated hydrocarbon contamination. NH4+ exceeded the Chinese groundwater standard in 77.78% of samples, whereas vinyl chloride exceeded the WHO guideline value in all samples. Hydrochemical analysis indicated that groundwater chemistry still retained a water-rock interaction background, but had been significantly overprinted by anthropogenic inputs. PMF resolved six factors and showed that groundwater pollution was mainly controlled by high mineralization, high-ammonium wastewater input, and dissolved inorganic salt enrichment, whereas chlorinated-solvent industrial pollution had strong diagnostic significance. MixSIAR identified industrial wastewater as the largest nitrate contributor under both prior settings, followed by fertilizer-derived nitrification, whereas mountain-front soil background contributed comparatively less. These results indicate that the combined PMF-MixSIAR framework is effective for identifying mixed groundwater contamination in industrial parks.

Seagrass ecosystems play a crucial role in coastal carbon dynamics, yet their contribution to soil organic carbon (SOC) storage is underexplored in many areas and especially in African waters. This study assessed seagrass cover, species composition, and SOC stocks in the Lamu Archipelago, Kenya, comparing Marine Protected Areas (MPAs), Locally Managed Marine Areas (LMMAs), and unmanaged sites. Additionally, it investigated the relationships between management stratgeies and pertinent physical and chemical parameters. SOC was measured using the Loss on Ignition method and expressed as Mg C ha⁻¹. SOC stocks were higher in MPAs (89.16 ± 30.88 Mg C ha⁻¹) than in unmanaged areas, while SOC stocks in LMMAs were comparable to those in MPAs. While the MPA was associated with higher SOC stocks, these patterns may also reflect underlying environmental differences among sites, including sediment texture. SOC variability was strongly associated with sediment type, canopy cover, and disturbance intensity, with fine-grained sediments, particularly clay, linked to enhanced carbon retention. Higher SOC stocks co-occurred with the presence of large, persistent seagrass species such as Thalassodendron ciliatum and Enhalus acoroides in managed areas. This study provides the first field-based SOC estimates for Lamu's seagrass meadows, highlighting the potential of LMMAs within broader blue carbon conservation strategies.

As the "Resource Lifeline" strategy of the China National Gold Group (CNGG) extends to greater depths, its subsidiary mines encounter severe challenges, primarily characterized by tectonic fracturing, intense hydrothermal alteration, and data scarcity. Crucially, traditional empirical stability classifications function as mere "static snapshots" that fail to capture the nonlinear accumulation of hidden hazards, rendering them ineffective for early warning in complex deep environments. To bridge this gap, this study proposes a data-driven stability assessment framework that seamlessly integrates unsupervised structural typing with nonlinear phenomenological evolution. Diverging from reliance on subjective experience, this study first extracts the intrinsic geometric features of 40 typical goafs using K-means clustering to establish an objective structural typology. Subsequently, an Analytic Hierarchy Process (AHP)-Entropy combined weighting model reveals that hydro-environmental factors account for over 50% of the total risk contribution, highlighting the overwhelming statistical significance of water-rock coupling in driving instability. To quantify the continuous progression from a metastable to a high-risk state, a non-linear dynamic evolution model based on the logistic map is introduced. By incorporating the comprehensive static risk index, this model effectively characterizes the nonlinear damage amplification process. The derived critical threshold (Rc = 0.57) accurately delineates high-risk zones, providing a transparent, quantitative paradigm for prioritizing the remediation of concealed hazards in data-scarce deep mining operations.

Achieving advanced nitrogen removal in municipal wastewater treatment plants remains challenging under low-strength influent and seasonal temperature fluctuations. Here, we optimized a full-scale anaerobic/aerobic/anoxic process (40,000 m3/d) and evaluated its year-round performance for influent with biochemical oxygen demand of 49.1 ± 9.9 mg/L and total nitrogen of 18.2 ± 1.4 mg/L. By reducing the air-water ratio to 0.39 and shortening the anaerobic hydraulic retention time to 1.8 h, the system achieves effluent total nitrogen as low as 3.3 mg/L and maintains 4.1 mg/L even as the temperature declines from 24.6 °C to 11.3 °C. The combined measures preserve intracellular carbon in the anaerobic zone and limit aerobic over-oxidation, enabling sustained endogenous denitrification in the downstream anoxic zone and clarifier. Endogenous denitrifiers and hydrolytic bacteria are selectively enriched, and functional genes associated with intracellular carbon metabolism and denitrification show higher abundance. Compared to the parallel anaerobic/anoxic/oxic process treating the same influent, chemical use decreases by 40%, sludge production by 8%, and aeration energy by 73%. This work demonstrates that full-scale implementation of this process provides an energy-efficient solution for low-strength municipal wastewater treatment. Authors report an optimized full-scale anaerobic/aerobic/anoxic process for low-strength municipal wastewater, achieving advanced nitrogen removal and reduced energy, chemical, and sludge outputs by regulating air-water ratio and hydraulic retention times.

The spatial distributions of plant functional traits observed today are living imprints of current environmental gradients and past selection, offering insight into how plants have adapted to their environments. What remains insufficiently understood is how traits combine and coordinate across environments, and whether such coordination reflects organizing principles in ecology that can improve modeling of ecosystem functional diversity and decadal-scale carbon exchange. Here we present DifferLand, a differentiable hybrid model that learns high-dimensional, coordinated environment-trait relationships directly from multi-modal satellite and in situ observations. DifferLand reveals a small number of latent axes that represent how suites of plant traits jointly shape vegetation dynamics and carbon-water fluxes, enabling the model to capture both long-term adaptation patterns and short-term responses to meteorological variability, and to outperform models that rely solely on plant functional types in spatial generalization. The spatialization network learns nonlinear interactions between plant functional attributes and environmental gradients, organizing latent ecological parameters that represent functional traits at the global scale. This latent environment-trait structure reveals large-scale patterns of ecosystem functional diversity and improves the spatial generalization of terrestrial biosphere models.

The rise of antibiotic-resistant infections, particularly those involving biofilms, presents a significant global health threat. Phage therapy, the use of bacteriophages as antimicrobial agents, offers promising solutions to this crisis. A critical component of phage therapy is the assessment of phage efficacy, in both the presence and absence of antibiotics, prior to clinical application. While considerable progress has been made using planktonic bacterial cultures, there remains an urgent need for standardized methods to evaluate phage efficacy against biofilms. In this study, we address this gap by systematically comparing ten different methods for quantifying phage activity in biofilm settings. Each method was evaluated using a panel of five anti-Pseudomonas aeruginosa phages, which were tested against both planktonic and biofilm cultures. Based on these comparisons, we propose a robust pipeline for detecting phage activity in biofilms. This pipeline, termed CApEsid biOfilm, integrates modified colony-forming unit (CFU) assays using stainless steel washers, crystal violet staining, extracellular DNA quantification using a dye, and extracellular ATP measurements. The pipeline was further validated with additional bacterial species and their respective phages. We also demonstrate its utility in detecting interactions between phages and antibiotics. Overall, this work presents a foundational pipeline that may enhance the clinical matching of phages for treating biofilm-associated infections, thereby improving the outcomes of phage therapy.

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants linked to adverse health effects. Recent epidemiological data suggest an association between PFAS exposure and hearing loss, but underlying mechanisms remain unclear. This study examined PFAS-induced auditory dysfunction in mice exposed to a mixture of five PFAS compounds (2 mg/L each) in drinking water for seven weeks. Ldlr−/− mice were used due to their susceptibility to metabolic dysfunction, a risk factor for hearing loss. Auditory brainstem responses (ABR) indicated that PFAS exposure significantly elevated hearing thresholds by 18–33 dB across multiple frequencies. Distortion product otoacoustic emissions (DPOAEs) revealed impaired outer hair cell (OHC) function, and immunohistochemical analysis indicated a 20% OHC loss in the basal turn of the cochlea. In addition, PFAS exposure reduced ABR wave-1 amplitudes, and caused a 50% reduction in spiral ganglion cell density, indicating impaired auditory nerve function. Overall, this study provides the first evidence for PFAS-induced high-frequency hearing loss in mice. The findings further indicated that cochlear OHCs and spiral ganglion neurons are potential targets in PFAS-induced hearing loss. Together, these data suggest that PFAS exposure elicits a multifaceted ototoxic response, affecting both sensory and neural elements of the cochlea.

Co-exposure to heavy metals can result in additive or synergistic toxicity in the brain, culminating in neurotoxicity. This study investigated the neurotoxic effects of a low-dose mixture of two toxic heavy metals-lead (Pb, 20 mg/kg) and aluminium (Al, 35 mg/kg)-and one essential metal, manganese (Mn, 0.564 mg/kg), on the cerebellum of rats. Animals were divided into five groups (n = 5) and orally treated for 90 days as follows: Group I received normal drinking water and served as the control; Group II received a heavy metal mixture of Pb (20 mg/kg), Al (35 mg/kg), and Mn (0.564 mg/kg) body weight; Group III received Pb (20 mg/kg) alone; Group IV received Al (35 mg/kg) alone; and Group V received Mn (0.564 mg/kg) alone. Chronic exposure to heavy metals resulted in a significant (p < 0.05) reduction in rotarod performance compared with the control group, indicating impaired cerebellar motor function. The low-dose heavy metal mixture significantly depressed antioxidant defences (p < 0.05), increased lipid peroxidation (p < 0.05), elevated amyloid-β peptide levels (Aβ₁-₄₀ and Aβ₁-₄₂) (p < 0.05), and markedly reduced occludin expression (p < 0.05) in the cerebellum relative to controls. These biochemical alterations were more pronounced in the mixture-exposed group than in animals treated with individual metals. Overall, chronic low-dose exposure to an environmentally relevant heavy metal mixture induces cerebellar neurotoxicity through enhanced amyloid-β accumulation and downregulation of occludin, a key tight junction protein, in adult male Wistar rats. These findings underscore the role of mixed metal exposure in amyloid-β dysregulation, tight junction disruption, and cerebellar dysfunction.

Mangrove forests fringe the highly dynamic, mud-dominated Guianas coast, where wave-induced mobility of Amazon-derived mudbanks drives rapid coastal accretion and erosion. In French Guiana, this geomorphic instability reorganizes mangrove distribution, creating mosaics of successional stages in which stand development rarely approaches long-term equilibrium. However, it remains uncertain whether a single age-biomass relationship can represent contrasting coastal Avicennia-dominated stands and heterogeneous estuarine Rhizophora-dominated stands in this system. This study evaluates how effectively stand age, reconstructed from historical imagery, predicts stem diameter at breast height (DBH) and aboveground biomass (AGB) of Avicennia germinans and Rhizophora spp. along this coast, using chronosequence data spanning pioneer to mature stands. DBH was measured in the field, and AGB was estimated using locally validated allometric equations. Four empirical growth models (power, Gompertz, logistic, and monomolecular) were fitted using nonlinear least squares to describe age-structure and age-biomass relationships. Stand age strongly predicted DBH in Avicennia germinans but explained less variation in AGB and in both DBH and AGB for Rhizophora spp., and differences among growth functions were small. In this mud‑dominated setting, stand‑age models perform well for coastal mangroves but are less informative for estuarine mangroves. Under ongoing climate and environment‑driven change, this study highlights the need to complement stand age with environmental and structural covariates when modelling mangrove biomass and carbon stocks in both coastal and estuarine systems.

Potentially toxic elements (PTEs) contamination of agro-ecosystems poses significant threats to food safety and public health. Study investigated the occurrence, sources, and human health risks of PTEs (As, Pb, Cd, Co, Cr, Hg, Ni, Cu, Fe, Mn, Se, Zn, Th, and V) in irrigation water (n = 1), agricultural soils (n = 9 composite samples), and vegetables (onion, cabbage, and amaranth; n = 36 composite samples) collected in August 2024 from the Mubuku Irrigation Scheme, western Uganda. Elemental concentrations were determined using inductively coupled plasma-optical emission spectroscopy. Health risks were assessed using hazard quotient, hazard index (HI) and total cancer risk (TCR) models, complemented by Monte Carlo simulation (MCS; 10,000 iterations) to address exposure variability and uncertainty. More than 20% of detected PTEs in vegetables exceeded WHO/FAO limits. Arsenic (2.22-3.57 mg/kg), lead (2.02-3.66 mg/kg), and mercury (0.42-0.61 mg/kg) consistently exceeded guideline values (0.1, 0.3, and 0.001 mg/kg, respectively), with amaranth as the highest accumulator. Irrigation water contained elevated As (1.56 mg/L) and Pb (2.73 mg/L). Estimated HI values indicated considerable non-carcinogenic risks (HI > 1). TCR and MCS exceeded acceptable thresholds (10⁻⁶-10⁻⁴), highlighting probable lifetime cancer risks and the need for targeted risk management interventions.

Urban heat islands (UHI) significantly elevate land surface temperatures (LST) in high-density subtropical cities like Osaka, Japan, exacerbating energy demand, health risks, and climate vulnerability. This study investigates LST drivers using freely accessible Landsat 9 data (August 27, 2024) and OpenStreetMap (OSM) building footprints at 100 m resolution. Due to the absence of reliable 3D height data, we focus on vegetation indicators (mean NDVI and vegetation fraction) and basic 2D morphology (building coverage ratio [BCR] and building area density ratio [BADR], assuming uniform 10 m height) as a pragmatic open-data baseline. Vegetation metrics show weak positive associations with LST (Pearson r = 0.173 for NDVI_mean, 0.114 for VegFrac), while 2D morphology exhibits negligible links (r ≈ 0.008). These results highlight the limited explanatory power of planimetric indicators alone in humid subtropical settings. Machine learning models (Random Forest [RF], XGBoost [XGB], Artificial Neural Network [ANN]) substantially outperformed multiple linear regression (R² = 0.045), with XGB achieving the highest performance (R² = 0.233, RMSE = 29.6 °C). NDVI_mean dominated feature importance (55.3%). Spatial predictions identified LST hotspots in central districts (high BCR, low vegetation), where partial dependence analysis suggests an indicative marginal LST reduction of ≈ 1.0-1.5 °C associated with a 10% point increase in VegFrac (model-derived statistical association, not causal; subject to considerable uncertainty due to the modest R² and excluded confounders). Results emphasize the need for multi-variable frameworks incorporating 3D morphology (e.g., sky view factor, height variation), landscape patterns, and meteorological factors to enhance predictive accuracy and inform targeted greening, ventilation corridors, and cool materials in Osaka's urban planning. As a replicable, low-cost open-data baseline, this study offers practical insights for resource-constrained subtropical cities, contributing to Sustainable Development Goals (SDGs) 11 and 13.

Ecosystems provide critical services essential for human well-being and environmental sustainability. This study examines the impacts of land use land cover (LULC) dynamics on ecosystem service values (ESVs) in Hoto area, South Ethiopia, from 1993 to 2023. Using multispectral Landsat imagery, analyzed with ERDAS IMAGINE 2014 and ArcGIS 10.8, six LULC classes were identified: barren land, forest, grazing land, farmland, shrubland, and settlement. The analysis reveals a significant decline in forest cover (from 24.9% to 11%, net loss of 55.69%) and grazing land (from 13.5% to 9.9%), alongside expansions in settlement (from 4.6% to 7.0%), barren land (from 2.1% to19.5%), and shrubland. Total ESVs decreased from US$ 4.35 million in 1993 to US$ 3.33 million in 2023, driven primarily by deforestation, overgrazing, and land degradation, which impaired key services like food production, water regulation, and erosion control. The decline was most pronounced in regulating services (-29.4%), which dominated the total ESV. Overall, these findings underscore the urgent need for targeted policy interventions, including reforestation of degraded lands, promotion of sustainable agroforestry, protection of remaining forest patches, and regulating grazing to restore critical ecosystem services and to improve local livelihoods in the study area.

Pharmaceuticals and personal care products are emerging pollutants since they persist for for an extended period and can harm the environment. This study assessed the prevalence, spatial distribution, and ecological risk of triclosan, naproxen, diclofenac, norfloxacin, and caffeine in surface and groundwater at 30 locations in Bengaluru and Mysuru, India. We used SPE-HPLC to look at the compounds and the risk quotient method to look at the ecological risk across different aquatic trophic levels. All target PPCPs were detected across the study area. Ecological risk assessment showed that the highest risk quotient values for norfloxacin, diclofenac, naproxen, triclosan, and caffeine were about 2, 13, 0.7, 8, and 16, respectively. Caffeine, diclofenac, and triclosan consistently exceeded over the high-risk threshold (RQ > 1), while norfloxacin was exhibited moderate risk and naproxen was in the low to middle of the risk range. The results show that urban aquatic ecosystems in southern India indicate substantial pharmaceutical contamination. This is primarily due to untreated sewage from households, hospital waste, and poor wastewater management. The high ecological risks linked to multiple compounds underscore the necessity for ongoing monitoring, enhanced wastewater treatment technologies, and risk-based management strategies to mitigate pharmaceuticals and personal care products pollution and safeguard aquatic ecosystems and public health.

Prenatal exposure to trace metal elements remains a significant public health concern, particularly because these elements can cross the placental barrier and accumulate in fetal tissues. Meconium and neonatal hair are commonly used as non-invasive biomarkers of intrauterine exposure; however, their comparative behavior and degree of agreement remain insufficiently understood. This study aimed to quantify concentrations of lead (Pb), cadmium (Cd), chromium (Cr), and nickel (Ni) in paired meconium and neonatal hair samples and to evaluate differences and associations between these two biological matrices. A cross-sectional study was conducted on 50 healthy full-term neonates in Latakia, Syria, during August 2025. Paired meconium and neonatal hair samples were collected within the first 24 h after birth. Following microwave-assisted acid digestion, trace metal concentrations were measured using graphite furnace atomic absorption spectrometry. Data distribution was assessed using the Shapiro-Wilk test. Due to non-normality, paired comparisons were performed using the Wilcoxon signed-rank test, and correlations were evaluated using Spearman rank correlation coefficients. All four trace metal elements were detected in both matrices. Meconium concentrations were consistently higher than those measured in neonatal hair, with statistically significant differences observed for all analyzed elements (p < 0.001). Correlation analysis showed weak and non-significant associations between meconium and neonatal hair concentrations for Pb, Cr, and Ni, while Cd showed a modest but non-significant correlation. These findings indicate limited agreement between the two biological matrices. Meconium exhibited higher trace metal concentrations than neonatal hair, suggesting a broader accumulation of prenatal exposure. However, the weak correlations between matrices indicate that they may capture different exposure characteristics rather than serving as interchangeable biomarkers. Further studies incorporating maternal and environmental data are needed to better interpret these differences.Trial registration: Not applicable.

The current study assess the degree of pollution in two harbors (Madaia and Saha) located in the southwestern Red Sea, Saudi Arabia with potential impacts on the intervening control coastline. This study deals with the integration between polluted and non-polluted areas. The general physicochemical study, PAHs determination, Pesticide residue evaluation, the most important heavy metals analysis and halophiles investigation are accomplished. 1) According to PAHs determination, 1-methyl-Naphthalene was predominant at Madaia Harbor, 2-methyl-Naphthalene at Saha Harbor, and Acenaphthene at the control coastline. 2) According to pesticide residue evaluation, twenty-one pesticide residues were analyzed, with terbufos, methyl parathion, and malathion detected at the highest concentrations across all sites. 3) According to heavy metal analysis, As, Hg and Pb record the highest concentration at Control coastline. 4) According to halophiles investigation, slight to moderate levels of halophilic bacteria were observed at both harbors, while halophilic yeasts were present at all study sites. Correlation and simple linear regression analyses indicated that pollution at the control coastline was negatively influenced by discharges from both harbors, with Saha Harbor being the primary source, although Madaia Harbor also had significant impacts.

Abstract This study explores a sustainable approach to simultaneously valorising municipal solid waste and remediating nitrate-contaminated water by generating an engineered adsorbent from refuse-derived fuel (RDF) via a thermochemical pathway. RDF feedstock was pyrolysed at 500 °C in a pilot-scale rotary kiln to produce RDF500 char, subsequently modified using zinc chloride in 2:1 wt.% ratio (RDF500-2) to enhance surface functionality and adsorption performance. Modification with ZnCl 2 has been extensively studied, and when handled properly, it does not pose greater environmental risks, thereby supporting sustainability aspects. Furthermore, characterisation through FTIR, BET, and SEM confirmed the introduction of oxygenated groups (–OH, –COOH, –C=O), increased surface heterogeneity, and the development of a micro-mesoporous structure conducive to nitrate adsorption. Fixed-bed column experiments were performed under varying operational conditions, including bed height (5–10 cm), influent flow rate (3–7 mL min -1 ), and initial nitrate concentration (67–185 mg L -1 ) utilising RDF500-2, to determine breakthrough behaviour and adsorption kinetics. The maximum adsorption capacity was 21.32 mg g -1 , corresponding to 89% nitrate removal efficiency under optimal conditions. The kinetic modelling using Thomas, Yoon–Nelson, Adams–Bohart, Wolborska, and Dose–Response models exhibited an excellent correlation (R 2 &gt; 0.98), with the Dose–Response and Thomas models showing the best predictive accuracy for column optimisation. A scale-up analysis for a 100 L min -1 continuous flow system predicted 80% removal efficiency, confirming the practical applicability of modified RDF char (RDF500-2).

The Arctic is experiencing unprecedented environmental change, with diminishing sea ice reshaping marine ecosystems. The narwhal (Monodon monoceros) exhibits strong site fidelity during seasonal movements and continued sea-ice decline has the potential to alter important habitats. This study aimed to understand narwhal presence at different sea-ice stages by combining long-term passive acoustic monitoring (PAM) with satellite-derived sea ice data from Inglefield Bredning, Northwest Greenland (June 2022-September 2025). Generalized linear mixed models (GLMMs) revealed a highly significant effect of sea-ice stage on narwhal acoustic activity (p < 0.001). Activity peaked during partial ice cover (β = 1.73 ± 0.17, p < 0.001) but declined sharply under open-water and freeze-up conditions (β = - 0.98 ± 0.19, p < 0.001). These results demonstrate that narwhal presence is closely synchronized with sea-ice timing and extent, emphasizing the marginal ice zone as a key ecological feature that narwhals exploit, likely because it provides both feeding opportunities and refuge from predators. Continued loss of seasonal sea ice is therefore expected to alter narwhal movement patterns, potentially increasing fjord residency and reducing inter-fjord movements. Such behavioural shifts could have cascading ecological effects, altering prey dynamics and reducing genetic exchange among regional narwhal groups.

As a predominantly agrarian nation, cutting emissions from agriculture is essential to achieving its “dual carbon” targets. The primary source of agricultural production, cultivated land, has a major impact on the sector’s total carbon emissions. However, the spatial correlation network features have received little attention in previous investigations, which have mostly concentrated on driving variables and emission measurements. Examining the spatial network characteristics of cultivated land carbon emissions (CLCE) provides a basis for promoting coordinated regional emission reduction. This study integrates the carbon emission coefficient method, standard deviational ellipse, ESDA, a modified gravity model, and social network analysis to reveal the spatiotemporal evolution and spatial network structure of CLCE in China from 2000 to 2023. The main findings of this study are as follows: (1) China’s CLCE increased overall, with fluctuations, from 6028.83 × 104 t in 2000 to a peak of 9111.60 × 104 t in 2015, before decreasing to 7555.91 × 104 t in 2023. (2) Spatially, the center of gravity of CLCE has continuously shifted northwestward, exhibiting a significant positive spatial autocorrelation characterized mainly by “high-high” clustering. (3) CLCE demonstrates a clear networked spatial structure, with increasing overall spatial connection strength, good connectivity, and stability, though the overall network compactness remains to be improved. (4) The spatial network of CLCE exhibits a “core–periphery” structure, with Shandong, Jiangsu, Henan, Hebei, Anhui, Hubei, and Sichuan serving as long-term core provinces, while the northwest and northeast regions are mostly located at the periphery. The research offers theoretical support for developing low-carbon agricultural strategies and promoting coordinated regional emission reduction policies in China.

Abstract The delineation of the Wildland-Urban Interface (WUI) is fundamental for wildfire risk management, yet it is highly sensitive to the underlying building data used. Global building datasets offer unprecedented coverage but may introduce biases by including different types of built-up structures, potentially leading to an overestimation of exposure and a misallocation of critical resources. This study aims to map the WUI and assess wildfire exposure in mainland Portugal by comparing the efficacy of different building datasets: the official residential database (BGE21), Microsoft Building Footprints (MSB24), and the World Settlement Footprint (WSF19). We employed a point-based mapping methodology (100-m radius, &gt; 6.17 buildings/km 2 ) to classify WUI into Intermix and Interface zones. Our analysis revealed that the choice of dataset drastically alters WUI estimates. MSB24, which includes all structure types, identified 67% more buildings than the residential-focused BGE21, resulting in a 73% larger WUI area. Spatial agreement was low, with only 46% of the total WUI area being identified by all three datasets, falling to just 29% for the more vulnerable Intermix zones. While MSB24 showed high recall (0.97 Intermix , 0.99 Interface ), its precision was low (0.43 Intermix , 0.67 Interface ), confirming a significant overestimation of critical zones. Analysis of wildfire perimeters (2000–2023) showed that burned area within the WUI was disproportionately higher in years with smaller total fire extent (e.g., 2006, 2018) rather than in megafire years (e.g., 2003, 2017). We conclude that while global datasets like MSB24 are valuable for emergency response due to their high coverage, their use for preventive planning and resource allocation may cause inefficiencies. We recommend that local authorities prioritize validated residential data, like BGE21, for strategic wildfire prevention and mitigation planning in Portugal to ensure resources are targeted efficiently.

Climate and land use change are reshaping species distributions globally, yet their combined effects remain underexplored, particularly for wide-ranging carnivores. Here, we assessed the joint impact of climate and land use change on the future distribution of the Caucasian lynx (Lynx lynx dinniki) across its entire range. Using a fine-tuned MaxEnt model, we projected habitat suitability to 2050 under two socio-economic scenarios (SSP1-2.6 and SSP5-8.5), incorporating current and future climate and land cover data. Habitat patches were classified as breeding or stepping-stones based on size thresholds, and landscape metrics were used to evaluate structural changes. Our projections indicated substantial habitat loss (31-33%) and gain (14-34%), with the most severe losses expected in the southern range, particularly in the Zagros and southern Anatolian mountains. Center of gravity analysis suggested a northward shift in suitable habitats, partially compensating for southern declines. However, increased fragmentation and isolation were evident under all scenarios. These findings emphasize the urgency of conservation strategies that maintain connectivity, protect stepping-stone habitats, and support adaptive land use planning. Enhancing corridor networks and addressing conservation gaps, especially in emerging northern ranges, will be critical for ensuring the long-term viability of the Caucasian lynx in a rapidly changing landscape.