The Netherlands experiences significant environmental impacts from reactive nitrogen, particularly ammonia (NH3), whose long-term deposition harms soil, water, and biodiversity. NH3 is emitted mainly from agriculture and its levels can be very high and variable in intensive livestock areas. Although monitoring stations are set up across multiple locations, data gaps may still arise due to issues with measurement instruments. Therefore, there is a need for models that can reliably fill in these missing observations. In this study, we first applied Linear Regression, Random Forest, and Gated Recurrent Unit (GRU) models to predict one day ahead NH3 concentrations at six sites (De Zilk, Valthermond, Vredepeel, Wekerom, Wieringerwerf, Zegveld) in the Netherlands. All models captured daily NH3 trends, with Random Forest initially performing best (R2 up to 0.59 at Valthermond). Predictions were strongly driven by lagged NH3 values with wind speed and precipitation contributing moderately. After correcting for prediction lag caused by autocorrelation, the linear regression performed best at most sites (with best performance observed at Zegveld with R2 of 0.84) and was used for gap filling. It maintained reasonable accuracy despite sparse observations (every 2-7 days), with most sites (De Zilk, Valthermond, Vredepeel, Wekerom, Zegveld) exhibiting a significant correlation of almost or more than 0.5 even at 7 days measurement gaps. Additionally, we noted that historical data from existing sites could be effectively used to fill gaps at newly established locations that exhibited similar distributions of NH3.

Cadmium (Cd) is a persistent environmental pollutant with a biological half-life of several decades in animals. However, the osteotoxic effects in the mammalian skeletal system and their underlying mechanisms remain unclear. Using 374 control-observation comparisons from 47 studies, we systematically evaluated Cd-associated skeletal toxicity through meta-analysis and machine learning. The results indicate that Cd exposure significantly impairs overall bone health (13.68%, P < 0.001). TRACP5b (61.52%, P < 0.001) and CTX-I (35.29%, P < 0.01) showed the strongest responses, whereas BMD (10.28%, P < 0.001) and body weight (6.06%, P < 0.001) changed more moderately. TRACP5b responded approximately sixfold more strongly than BMD, supporting bone resorption markers as more sensitive early-warning indicators of Cd-induced skeletal toxicity. The XGBoost model demonstrated the best performance on the test set (R2 = 0.752, RMSE = 0.325), highlighting its strong potential for predicting Cd-induced bone toxicity risk. SHAP analysis identified response indicators (9.5%-23.3%) and Cd concentration plus duration (18%) as major contributors to osteotoxic response variation. Biologically, these findings indicate that Cd-associated osteotoxicity is characterized by heterogeneous sensitivity across bone-remodeling endpoints, while exposure concentration and duration modulate the magnitude of this multi-target skeletal response. These findings provide a basis for refining cadmium risk assessment and screening early-warning biomarkers.

A four-year study (2019-2022) was conducted on water, bottom sediments, and hydromacrophytes collected from three rivers: Strzeżenica River, Unieść River, and Dzierżęcinka River which discharge coastal Lake Jamno (Poland). A total of 168 water samples, 168 bottom sediment samples, and 426 aquatic plant samples were analyzed. The presence of aluminum in the components of the aquatic environment was determined against the background of hydrochemical parameters. Environmental quality was assessed using contamination and accumulation indices (MPI, BCF, CF, Cf, DC). Aluminum concentrations in river water ranged from 0.0187 to 0.2788 mg Al·dm-3 and remained below the environmental threshold of 0.4 mg Al·dm-3. Mean concentrations in water were 0.0845, 0.0986, and 0.1048 mg Al·dm-3 in the Strzeżenica, Unieść, and Dzierżęcinka rivers, respectively. In contrast, substantially higher Al concentrations were recorded in bottom sediments, reaching mean values of 4137.43 mg·kg-1 in Strzeżenica, 267.23 mg·kg-1 in Unieść, and 971.49 mg·kg-1 in Dzierżęcinka. Mean Al concentrations in aquatic plants were 1690.67, 826.16, and 1125.66 mg·kg-1, respectively. The MPI for water was low in all rivers (0.0670-0.0812), whereas substantially higher values were recorded for sediments (70.77-504.77) and plants (650.47-989.90). The highest accumulation and contamination were observed in the Strzeżenica River, where the contamination factor (Cf) reached 4.1374 and the integrated degree of contamination (DC) for the studied river system was 5.3761. Bioaccumulation factors relative to water (BCFW) reached 29,278.55 in Strzeżenica, compared with 11,950.47 and 19,040.71 in Unieść and Dzierżęcinka, respectively. These results demonstrate a clear contrast between the relatively low Al burden in the water column and its substantial accumulation in sediments and aquatic plants. Bottom sediments therefore represent the major reservoir of Al in the studied river systems and may constitute an important secondary source of metal exposure to aquatic biota. The findings highlight the importance of multi-matrix monitoring of aluminum in coastal river ecosystems, as water-column measurements alone may underestimate the long-term accumulation and environmental burden of this metal.

Accurately identifying the driving mechanisms of carbon emissions from energy consumption is crucial for regional low-carbon transition. However, existing studies predominantly focus on statistical regression or trend extrapolation, lacking systematic characterization of multi-scale causal mechanisms and comprehensive evaluation of multi-scenario pathways. Therefore, this study integrates multi-source data on socioeconomic conditions, land use, and climate in the Pearl River Delta urban agglomeration (PRD) from 2000 to 2022. It constructs an integrated multi-source data-deep learning model evaluation-interpretability analysis -causal identification-scenario prediction. Key variables were identified using Sharpley Additivity Explanation (SHAP), followed by quantification of net effects and transmission pathways via causal graphs. Scenario prediction for carbon emissions from energy consumption (CE) were conducted using sub-scale optimal models. The results indicate (1) Scale-specific modeling indicates that the Sparrow Search Algorithm-optimized Convolutional Long Short-Term Memory Network (SSA-ConvLSTM) performs best at the pixel scale, while the Ister-Transformer deep learning model-which integrates temporal and spatial features-is optimal at the county and city scales. These models can be utilized for rolling evaluation and calibration. (2) SHAP analysis reveals a "scale synergy-morphological threshold/saturation-efficiency offsetting" relationship. Causal inference further demonstrates that pixel-scale PGDP exerts a negative effect on carbon emissions. At the county scale, GDP and JCQ primarily influence emissions through population, while at the city scale, population's direct impact on emissions is most significant. (3) Scenario simulations indicate that policy implementation should be stratified: municipal-scale "total volume constraints," county-scale "compact development and stock efficiency enhancement," and pixel-scale "energy efficiency and technological offsetting." The integrated framework of causal identification-interpretative analysis-scenario forecasting proposed in this study provides robust support for scientific carbon emission prediction and regional low-carbon policy formulation.

Curcumin-mediated silver nanoparticles (Curc-AgNPs) are promising biogenic nanomaterials in medical and environmental applications. However, their ecotoxicological impact to non-target aquatic species remains understood. This study assessed the toxicity of Curc-AgNPs in the neotropical freshwater snails Biomphalaria glabrata, considering multiple developmental and post-hatching endpoints, including embryonic mortality, hatching success, developmental progression, heart rate, embryonic cell viability, and mortality of newly hatched snails. Curc-AgNPs (14 ± 4 nm) were synthesized by reducing AgNO3 with curcumin and characterized by multiples techniques. Curc-AgNPs induced mortality, hatching inhibition, developmental delay, decreased heart rate and cell viability in a time- and concentration-dependent pattern. The cumulative developmental toxicity was confirmed by declining 50% effective concentration (LC50) to embryos (20.96 mg L[-1] at 24 h to 1.47 mg L[-1] at 168 h) and newly hatched snails (53.7 mg L[-1] at 24 h to 37.5 mg L[-1] at 120 h). Curc-AgNPs almost completely inhibited snail hatching at concentrations ≥ 1.88 mg L[-1] and delayed embryonic development, mainly at gastrula and trochophore stages. Sub-lethal effects were observed in terms of cardiac activity (heart rate reduced by ∼41% at 1.88 mg L[-1]) and reduced cell viability in embryos exposed to Curc-AgNPs at concentration ranging 0.18 to 0.75 mg L[-1]. Also, Curc-AgNPs induced higher toxicity in embryos than in newly hatched B. glabrata, indicating that the early developmental stages of gastropod are more susceptible to the toxicity of Curc-AgNPs. Overall, Curc-AgNPs exhibited pronounced embryotoxicity and stage-dependent molluscicidal effects. Although toxic, these concentrations exceed predicted environmental levels, representing hazard, not environmental risk.

Integrated CO2 capture and methanation (ICCM) is a promising route for converting CO2 into synthetic natural gas using renewable H2. ICCM requires a material to capture carbon and make them available for subsequent hydrogenation. This study compares Na-Ni-Al dual-function materials prepared by sol-gel and impregnation route and examines the effects of the sodium precursor. This study compares sol-gel and impregnation routes to examine how synthesis-dependent organization of Na-derived sorption domains and Ni active sites affects ICCM performance. The optimized NaNiAl-SG-CO3 exhibits superior performance, delivering a desorbable CO2 capacity of 461.85 μmol·g[-1] and a CH4 yield of 380.88 μmol·g[-1] at 340 °C, representing 30.7% higher yield and 24.8% higher peak rate than the impregnation-derived counterpart, along with enhanced CH4 selectivity and cyclic stability. The sol-gel material achieved this higher methane yield despite having a lower BET surface area. CO2 temperature-programmed desorption showed a different distribution of carbon-release temperatures, while temperature-programmed hydrogenation showed CH4 formation at lower temperature. The results indicate that synthesis-dependent changes in carbon retention and hydrogenation response are relevant to material performance. These findings provide an experimental basis for developing noble-metal-free materials for cyclic CO2 utilization.

Waste-derived materials can supply phosphorus-binding surfaces, mineral precursors, electron donors, alkalinity, and porous carriers for nitrogen (N) and phosphorus (P) removal from eutrophic waters. However, reported performance is difficult to compare because studies differ in nutrient forms, influent loads, hydraulic conditions, test duration, and removal endpoints. This review evaluates steel slag, red mud and bauxite residue, ferruginous and sulfur-bearing mining residuals, magnesian wastes, agricultural ash, and biochar, focusing on composition, modification, removal mechanisms, process configuration, and long-term operation. Three findings emerge. First, compositions favorable for N removal may not favor P removal: sulfur-siderite media showed the highest reported N-removal rate at 25% siderite, but the highest P-removal rate at 75%. Second, beneficial interaction is clearest when one material function removes a measurable limitation on another process. For example, alkaline slag mitigates acidification during sulfur-autotrophic denitrification, while Ca, Mg, and Fe phases retain phosphate. Third, dominant limitations shift during operation from initial dissolution and reaction kinetics to intraparticle transport, surface passivation, clogging, breakthrough, and possible nutrient re-release. Organic-matter and bloom-derived metabolite loading can reverse iron-based phosphorus retention and therefore belongs in any realistic test protocol. Material formulation should therefore address electron supply, proton balance, oxygen distribution, and accessible P-reactive phases rather than rely on a fixed waste-mass ratio. Simultaneous concentration decreases should be distinguished from true process interaction using equal-load single-function controls and measurements of net N2 production and stable or exported P. Continuous-flow studies in real waters should report breakthrough, head loss, leaching, greenhouse-gas emissions, and spent-media behavior to establish whether short-term removal persists throughout material service life under realistic hydraulic conditions and variable water quality.

Urban greenspace exposure significantly impacts health within densely built environments. However, commonly used greenspace indicators, such as the Normalized Difference Vegetation Index and Green View Index, often yield divergent estimates of exposure. This reduces comparability across greenspace-health studies and leads to inconsistent findings. While recent research has identified that several factors (e.g., slope, building density) contribute to these discrepancies, these factors often co-occur to form complex geographic contexts. Yet, few studies have systematically examined how these co-occurring environmental factors form geographic contexts and subsequently contribute to these measurement differences. This study fills this gap by designing a context-sensitive diagnostic framework to elucidate these measurement discrepancies. We applied this framework in Hong Kong to evaluate five commonly used greenspace indicators, including Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green View Index, and three-dimensional vegetation metrics like Vegetation Volume Index and Canopy Volume Index, to investigate how these indicators vary across different geographic contexts. The findings reveal three context-dependent patterns of divergence among greenspace indicators: differences in measurement sensitivity between satellite indicators, observation-perspective differences between overhead measures and street-level visibility, and contrasts between two-dimensional and three-dimensional representations of vegetation structure. Drawing on these diagnostic insights from the Hong Kong case study, we developed a practical decision-support protocol that links indicator selection to measurement focus, observation perspective, and geographic context. This empirical application illustrates how the framework can support more context-sensitive interpretation of greenspace exposure indicators and inform indicator selection in high-density urban environments.

Quorum sensing (QS)-based bioaugmentation is promising for accelerating biofilm establishment and bioreactor start-up. However, its effectiveness is determined by biotic interactions between exogenous QS bacteria and indigenous microorganisms, which is shaped by the ecological roles of strain-specific traits and inoculation sequence. This study systematically investigated strain-specific biotic interactions between four QS strains (wastewater-derived strain X3, AM7 and AM9, and Pseudomonas aeruginosa PAO1) with forty non-QS strains under three inoculation strategies with different inoculation time (i.e., one-step mixing, pre-inoculation and post-addition). Biotic interactions associated with resource competition and quorum quenching (QQ) activity were distinguished using model strain Escherichia coli with strong substrate uptake capability and Rhodococcus sp. BH4 with QQ activity. The QS-mediated biofilm regulation was jointly shaped by strain-specific characteristics and inoculation sequence. The pre-inoculation strategy enhanced biofilm induction by AM9 and X3, alleviated negative interactions for AM7, but intensified inhibition by PAO1. By contrast, the post-addition strategy strengthened biofilm reduction by AM9, X3 and AM7, while it enhanced biofilm induction by PAO1. Resource competition alone was insufficient to suppress QS-mediated biofilm induction. However, QQ activity induced by BH4 significantly reduced extracellular polymeric substance (EPS) production and QS-mediated biofilm induction, particularly for X3 and AM7, distinguishing as the major ecological constraint. Notably, AM9 with strong QS activity maintained biofilm-promoting capability. This study provides ecological principles for QS strain selection and inoculation optimization, facilitating the improvement of QS-based bioaugmentation for rapid start-up of biofilm-based processes.

Climate change-induced heat exposure is an emerging public health concern with potential mental health consequences, including suicide risk. Yet, in climate-vulnerable low- and middle-income countries the association between heat exposure and suicide risk, and the mediating mechanisms underlying this connection, remain underexplored. Using a nationally representative two-round panel survey from Bangladesh (n=7,492), we empirically examined whether poor sleep quality and emotional dysregulation mediate the relationship between exposure to extreme heat and suicide risk. Risk was assessed using a validated suicide cognitions scale across two seasonal rounds surveying the same individuals. Exposure to days ≥28°C over a two-week period was the lowest temperature threshold significantly associated with elevated suicide risk, with the highest risk detected at ≥35°C. At this 35°C threshold, 29.5% of the total association was mediated through poor sleep quality and 1.8% through emotional dysregulation. Risk was notably higher during the summer, and among less educated and poorer populations. This study provides novel evidence from a climate-vulnerable country on psychosocial mechanisms connecting heat and suicidality. As heat extremes intensify across the Global South, targeted mental health interventions, both infrastructural and psychological, may need consideration in climate adaptation strategies to protect the well-being of at-risk populations.

Efficient removal of the emerging organic contaminant bisphenol A (BPA) remains an important challenge for sustainable water treatment. Herein, a series of BSO-Bi2O3 heterojunction composites were synthesized via a facile in situ precipitation strategy to enhance visible-light photocatalytic degradation of BPA. Structural characterizations confirmed intimate interfacial contact between two components, facilitating strong electronic coupling across the BSO-Bi2O3 interface. Among all as-prepared samples, the composite BSO-5%Bi2O3 exhibited the highest photocatalytic performance, achieving nearly 90% BPA removal within 80 min, significantly outperforming pristine Bi2O3 and Bi12SiO20. The enhanced photocatalytic performance was mainly attributed to extended visible-light absorption, accelerated charge separation, and efficient interfacial charge transfer. Trapping experiments and ESR analyses revealed that superoxide radicals (·O2[-]) and holes (h[+]) were the dominant reactive species involved in the degradation process. Electrochemical measurements combined with density-functional theory (DFT) calculations further revealed favorable interfacial charge redistribution and enhanced charge-transfer kinetics, supporting an S-scheme charge-transfer pathway that preserves charge carriers with strong redox capabilities. Moreover, the composite BSO-5%Bi2O3 maintained excellent recycling stability and structural integrity after repeated use. This work provides an effective strategy for constructing efficient bismuth-based S-scheme photocatalysts for the photocatalytic removal of emerging organic contaminants.

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) are well-characterized toxic atmospheric pollutants, whereas much less is known about their brominated analogues, polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs). Here, a year-round active sampling campaign was conducted in Guangzhou, a subtropical megacity in southern China, to simultaneously investigate atmospheric PCDD/Fs and PBDD/Fs in paired gas- and particle-phase samples. The annual mean total concentration of PBDD/Fs (1,435±1,338 fg m[-3]; range: 279-10,403 fg m[-3]) was comparable to that of PCDD/Fs (1,892±1,762 fg m[-3]; range: 313-11,456 fg m[-3]), and both compound classes were higher during winter-spring and lower in summer, although the seasonal contrast was weaker for PBDD/Fs. Backward trajectory and concentration-weighted trajectory analyses revealed stronger continental transport influence on PCDD/Fs, whereas PBDD/Fs showed weaker transport dependence and a more regionally confined pattern centered over the Pearl River Delta and coastal South China. Source apportionment associated PCDD/Fs mainly with industrial thermal processes, waste/biomass combustion, and aged regional background transport, while PBDD/Fs were more closely linked to brominated precursor- and material-related processes, possible traffic-related inputs and episodic thermal activities. PBDD/Fs were more strongly particle-bound than PCDD/Fs. However, PCDD/Fs exhibited systematic temperature-dependent partitioning and reasonable agreement with equilibrium-based models, whereas highly brominated PBDFs showed weak temperature dependence and poor model agreement, suggesting additional influences from source-related inputs, particle removal, and other non-equilibrium processes. Mean carcinogenic risks ranged from 6.75×10[-7] to 3.29×10[-6] across age groups, with the highest value observed for adults, while hazard quotients remained far below unity. These findings demonstrate distinct source, transport, and partitioning controls for PCDD/Fs and PBDD/Fs and support their independent atmospheric assessment.

Conventional water treatment processes exhibit inherent limitations in the removal of trace emerging micropollutants. To address this challenge, we rationally designed ultrathin Fe-doped nanosheets via a one-step etching strategy using ferrous sulfate. This approach simultaneously transformed pristine granular ZIF-8 into a layered architecture and facilitated the uniform incorporation of iron active sites. The as-prepared catalyst was subsequently employed in a visible-light-driven peracetic acid (PAA) activation system for the efficient degradation of micropollutants. The etching treatment not only substantially increased the specific surface area of the nanosheets relative to their bulk counterparts but also ensured homogeneous dispersion of Fe species, thereby establishing stable Fe[2+]/Fe[3+] redox cycling centers that significantly accelerate electron transfer kinetics. In the ZIF-8-Fe-Nanosheets/PAA/simulated sunlight system, sulfamethazine (SMT) achieved near-complete degradation within 50 min. Moreover, the catalyst exhibited excellent broad-spectrum degradation activity, robust pH adaptability across a range of 3-9, and strong resistance to coexisting matrix constituents in real water samples. Radical quenching experiments identified hydroxyl radicals ([•]OH) and singlet oxygen ([1]O2) as the dominant reactive oxygen species. Three plausible SMT degradation pathways were proposed, and toxicity assessment using quantitative structure-activity relationship analysis indicated lower biotoxicity of the transformation products compared to the parent compound. Overall, this work validates the Fe-doped nanosheet catalyst as an efficient PAA activator, and more broadly, paves the way for expanding PAA-based catalytic oxidation toward practical water treatment.

6-PPD quinone (6-PPDQ) is a fat-soluble pollutant. Considering important link between fat-soluble pollutants and nuclear hormone receptors (NHRs), we here systematically identified NHRs in the intestine in response to 6-PPDQ in nematodes. Among 140 intestinal NHRs genes, expression of 35 intestinal NHRs genes was dysregulated by 0.1-10 μg/L 6-PPDQ. Moreover, 6-PPDQ intestinal toxicity was aggravated by intestinal RNAi of nhr-8, nhr-12, nhr-31, nhr-41, nhr-67, nhr-68, nhr-80, nhr-232 and sex-1, and inhibited by intestinal RNAi of daf-12, nhr-3, nhr-14, nhr-22, nhr-84, nhr-120, and nhr-142. Furthermore, during control of 6-PPDQ intestinal toxicity, for underlying molecular basis, these candidate 16 intestinal NHR genes exhibited their function by modulating Mn-SODs, mitochondrial UPR, endoplasmic reticulum UPR, and their related molecular signals. Our observations highlight crucial role of NHRs in regulating 6-PPDQ intestinal toxicity by modulating certain intestinal protective responses.