Organic phosphorus flame retardants (OPFRs) and bisphenols (BPs) originate in a range of consumer-based products, building materials and vehicles. With expanding human activities in the warming Arctic, these compounds may become more prevalent in remote regions which can harm the local ecosystems. The goal of this research was to assess the occurrence and chemical concentration of OPFRs and BPs in waste-, surface and drinking waters in the capital region of Reykjavík, Iceland (64°N, 244 thousand inhabitants). OPFRs were detected in most municipal wastewater, storm drain and detention pond samples during warm and cold seasons. Among the eight targeted high-volume production OPFRs, Tris(2-chloroisopropyl) phosphate (TCIPP) measured in the highest concentrations (maximum 650 ng/L), followed by Tris(2-chloroethyl) phosphate (TCEP; < 350 ng/L), Triphenyl phosphate (TPhP, < 220 ng/L), Tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and Triethyl phosphate (TEP), which peaked around 100 ng/L in surface waters. Among the six BPs observed, the heat tolerant Bisphenol S (BPS) and its novel derivative BPS-MAE, were most frequently detected both in waste and surface waters, at concentrations < 17 ng/L. OPFRs and BPs were rarely detected in the groundwater source used for drinking. The annual wastewater plant emissions from a 40 km2 catchment servicing ∼100,000 residents were estimated as 0.7-1 kg/year for each of the commonly detected OPFRs, except for TCIPP (∼20 kg/yr). Stormwater was estimated to contribute less to the annual urban loading than municipal wastewater, because of a lower annual volume and lower concentrations (TCIPP, BPS-MAE). These initial results suggest that TPhP discharged from a preliminary wastewater treatment plant may pose medium risk to aquatic ecology. Untreated urban stormwater, particularly from light industrial catchments, can contribute to medium risk of TCEP and TDCIPP, and potentially high risk of TPhP. Therefore, stormwater should not be neglected as a significant pathway of OPFRs and BPs to aquatic environments.
Wastewater surveillance (WWS), a public health tool used primarily for infectious diseases in the U.S., might have expanded applications in select settings for substance use. Drug overdose is a leading cause of premature death across the US and in Marin County, California. In 2023, Marin County piloted a WWS program to detect fentanyl, norfentanyl (a fentanyl metabolite), xylazine, cocaine, and methamphetamine and evaluate its potential use in an Overdose Alert System. A mixed-methods study was implemented to assess correlations between substance concentrations in wastewater and emergency medical service (EMS) encounters for nonfatal opioid overdoses and overdose deaths and the acceptability of WWS for overdose prevention. Spearman's rho rank correlation and unadjusted Poisson regression models were used to evaluate associations between wastewater measures and overdoses. Norfentanyl wastewater levels were correlated with EMS confirmed opioid overdoses one and three weeks later (ρ = 0.39, p < 0.001), and associated with a 16% increase in fentanyl-involved fatal drug overdoses three weeks later (IRR = 1.16, 95% CI: 1.10-1.21). Over half of respondents supported WWS for overdose alerts. Among respondents at an increased risk of witnessing or experiencing an overdose, 39% reported that they would take action if wastewater showed presence of a new drug or a spike in levels. Respondents also indicated concerns about privacy, and potential changes in policing resulting from WWS. Jurisdictions might consider setting population size sampling limits and data sharing guidelines when using WWS. WWS could be useful in community-based settings for primary prevention and early intervention planning and complement other surveillance methods.
Controlling and remediating heavy metal(loid) contamination in groundwater at complex industrial sites remains challenging due to mixed pollution sources and strong subsurface heterogeneity, which hinder precise source apportionment and targeted risk management. We develop a machine learning coupled framework that integrates Self-Organizing Maps (SOM), K-means clustering, positive matrix factorization (PMF), geological-hydrogeological modeling, and Monte Carlo simulation to enable source-pathway-receptor contamination characterization, source identification, transport simulation, source-specific health risk assessment, and pollution zoning. Applied to an aluminum-processing site in southwest China, the framework showed that 84.6% of groundwater samples were contaminated. The most elevated metals were Fe, Al, and Mn, while mean concentrations of Fe, Al, Mn, As, Ni, and Pb exceeded the Chinese Class III groundwater standards. The hybrid Spearman-SOM-PMF model resolved three primary sources: spray coating and aluminum finishing (57.6%), geogenic background mixed with wastewater leakage (37.5%) and copper smelting and surface oxidation (4.9%). Groundwater flow simulation and three-dimensional geological characterization have shown that the regional hydraulic gradient and preferential pathways are the main factors affecting contaminant dispersion. A probabilistic health risk assessment has pinpointed the spray coating and aluminum finishing as the key sources for control, responsible for 51.0% of carcinogenic risk and 44.7% of non-carcinogenic risk. Combining SOM-K-means clustering with source-specific risks, we delineated risk-based management zones and identified Cluster II as the priority control area. This integrated framework provides a transferable approach for precise remediation and sustainable redevelopment of complex industrial sites.
For Water Distribution Networks (WDS) to be sustainably operated, hydraulic reliability, leak detection, and energy-efficient operation are essential. Although the data-driven hydraulic modeling problem has been advanced by recent developments in Graph Neural Networks (GNNs), the existing solutions are black-box predictors that lack the ability to directly enforce the physical conservation laws, which makes them less robust, interpretable, and reliably performing. The research proposes PI-HydroGNN, a physics-informed spatiotemporal graph learning framework for water distribution system monitoring and control. The framework integrates established modeling components within a unified architecture and incorporates hydraulic mass balance, energy conservation, and pressure-dependent leakage dynamics directly into the optimization objective, improving physical consistency and robustness. Three benchmark networks (Net3, C-Town, and Anytown) with stochastic demand variations and artificial leakage scenarios over a 60-day horizon are used in the extended period EPANET simulations to evaluate the framework. Compared to the data-driven baselines, PI-HydroGNN achieves 9.6% savings in pump energy use, an F1-score improvement of 0.922 for leakage detection, and a 39.9% reduction in pressure prediction RMSE, while also decreasing pressure violation rates by 68.9%. The model demonstrates strong generalization across benchmark networks under varying demand and leakage conditions. The findings show that a high-quality and functionally well-integrated digital twin for WDS operation can be obtained by incorporating physical principles into graph-based learning. PI-HydroGNN demonstrates strong potential for digital twin applications in water distribution system management.
Growing imbalance between freshwater availability and demand, driven by population growth, infrastructure constraints, and climate variability, has increased the need for reliable long-horizon forecasting of freshwater withdrawal and desalination dynamics on a per-capita basis. Although transformer-based models can capture complex temporal dependencies, their performance is highly sensitive to hyperparameter configuration, especially for multivariate and nonstationary environmental data. This study proposes a data-driven framework that integrates the Frequency Enhanced Decomposed Transformer (FEDformer) with the Improved Horse Herd Optimization algorithm (iHOW) for systematic hyperparameter optimization. The framework constructs policy-relevant per-capita indicators from country-level time-series data and evaluates the optimized model through controlled comparison with multiple metaheuristic optimizers under identical computational budgets. The iHOW-optimized FEDformer achieves the best overall performance, with a mean squared error of [Formula: see text], root mean squared error of [Formula: see text], Pearson correlation coefficient of 0.986, and Nash-Sutcliffe efficiency of 0.985. Convergence analysis further shows that iHOW reaches lower best-fitness values more rapidly and more stably than the competing optimizers. Repeated-run uncertainty summaries, omnibus statistical comparison, a lightweight hyperparameter-optimization budget sensitivity study, and a quantitative feature-importance analysis further strengthen the empirical characterization of model performance and stability under the evaluated design. Additional robustness experiments indicate that the framework preserves useful predictive structure across longer forecasting horizons, input-perturbation scenarios, temporal aggregation levels, and alternative missing-data treatments. Architecture ablation further shows that the gains depend materially on FEDformer's frequency-aware, decomposition-based, and multivariate design. Overall, the proposed framework provides a robust, transparent, and computationally reasonable tool for long-term water-resource assessment and policy-oriented analysis of freshwater stress and desalination reliance under the evaluated data, assumptions, and computational budget.
Onion (Allium cepa L.) is one of the major vegetable crops grown in Ethiopia. Although its productivity depends on optimization of irrigation water depth and fertilizer application rates, there is limited scientific evidence on the optimal nitrogen rate and irrigation depth in our study area. Therefore, this study investigated the interactive effects of different irrigation depths and nitrogen fertilizer rates on onion yield and resource use efficiency. A field experiment was conducted over two dry seasons (2019-2020) using nine treatment combinations, consisting of three irrigation depths and three nitrogen rates, arranged in a 3 × 3 factorial randomized complete block design with three replications. Prior to analysis, data were tested for normality and homogeneity. Subsequently, data were analyzed using a general linear model, and means were compared using LSD at P < 0.05. Results demonstrated that irrigation depth was the dominant factor (P < 0.001), followed by nitrogen level (P < 0.05). Although marketable yield increased consistently with the combined increase of both inputs, rising from 15.94 ± 0.72 ton ha⁻¹ in T1 to 31.30 ± 1.20 ton ha⁻¹ in T9, this trend alone does not determine optimal management. Based on multi-criteria analysis, treatment T6 (100% of crop water requirement combined with 125% nitrogen) was identified as optimal, recording the highest irrigation water productivity (4.85 kg m⁻³) and economic irrigation water productivity (121.27 ETB m⁻³), along with improved cation exchange capacity (11.433 ± 0.968 meq/100 g soil), reflecting enhanced nutrient retention. Accordingly, T6 is recommended as the most suitable strategy for improving sustainable onion productivity in the study area and in regions with similar agro-ecological conditions.
Marine aquaculture is expanding globally, yet its ecological impacts on microbial communities across the seawater and sediment compartments remain poorly understood. The aim of this study was to assess how the aquatic microbial communities respond to contrasting levels of aquaculture impact, moving beyond the site-specific approach that characterized most previous research. We investigated five mariculture sites, collecting seawater and sediment samples from aquaculture areas (i.e., nearby fish cages) and non-aquaculture control areas. Microbial community profiles were analyzed through 16S rRNA gene amplicon sequencing to explore taxonomic composition and diversity, test for compartment and impact-related differences, and identify discriminant taxa across fish farms. Moreover, sediment organic matter quality was characterized through proteins, lipids, carbohydrates, and biopolymeric carbon (BPC) to evaluate the association between enrichment of aquaculture-driven organic matter and benthic microbial community profiles. Our results revealed that surface seawater assemblages were dominated by site-specific taxa and did not differ significantly between aquaculture and non-aquaculture areas. In contrast, aquaculture sediments exhibited reduced diversity and a community shift toward anaerobic and sulfate-reducing taxa, with positive correlations to enhanced protein and lipid deposition. Benthic microbial responses were associated not only with the quantity but also with the biochemical quality of sedimentary organic matter. By integrating multi-site analyses, this study shows that aquaculture-related organic enrichment is associated with consistent microbial community patterns across distinct environments, providing a basis for the development of sediment-focused monitoring approaches in aquaculture.
The penetration of surfactant solutions into triglycerides (TAG) competes with the delamination of TAG films along the substrate interface, governing cleaning efficiency. Quantifying the relative kinetics of these processes is needed to predictively develop the next-generation surfactant formulations. We developed a combined spectroscopic and optical imaging framework, supported by diffusion modeling, to quantify both normal (Z) and lateral (XY) bulk and interfacial diffusion processes and their dependence on substrate wettability. While ATR-FTIR spectroscopic imaging resolved lateral (XY) front propagation along the TAG-substrate interface, simultaneous optical brightfield imaging quantified bulk morphological changes. A model surfactant mixture of sodium docecyl sulphate (SDS) and N,N-dimethyldodecylamine N-oxide (DDAO) (3:1) at 1.5% was employed, and experiments were conducted on hydrophobic (water contact angle, θwater ≈ 90∘) and hydrophilic (θwater ≈ 20∘) substrates to elucidate the role of surface interactions. Employing a one-dimensional Fickian diffusion model, an effective bulk diffusion coefficient in the Z-direction is extracted, in good agreement with optical measurements of XY bulk diffusion (Deff≈6×10-12 m2s-1). ATR-FTIR imaging revealed faster interfacial delamination dynamics on hydrophilic substrates, whereas hydrophobic substrates showed kinetics commensurate with bulk diffusion. Diffusion in sessile TAG droplets exhibits quantitatively faster kinetics, attributed to the 3-dimensional geometry. Overall, we establish a versatile, label-free, robust analytical methodology for quantifying diffusion of surfactant solutions and the interfacial response in TAG films, to support the design of effective cleaning formulations.
Microalgae play an important role in microalgae-bacteria symbiotic systems (MABS), and their growth directly affects purification efficiency. This study investigated the mechanistic role of microalgae growth-promoting bacteria in MABS, focusing on the screened strain Niallia circulans Q3. Through whole-genome sequencing, microscopic characterization, and validation in actual aquaculture effluent, the facilitative effects of Q3 on microalgal proliferation and aquaculture water purification were systematically elucidated. Results indicated that Q3 mitigated oxidative stress via antioxidant defense, promoted microalgal growth through multi-pathway synthesis of phytohormones, and enhanced phosphorus bioavailability through a sugar metabolism-driven acidification-chelation-hydrolysis mechanism. The presence of prophage-encoded auxiliary metabolic genes might further expand the metabolic versatility and stress resilience of the host bacterium, thereby stabilizing the MABS structure. Application in real effluent treatment demonstrated that supplementation with Q3 restructured the inter-algal microbial community, optimized nitrogen and phosphorus metabolic pathways, and significantly increased microalgal biomass and nutrient removal efficiency. This work provides both a theoretical foundation and practical strategies for the development of efficient microalgal production and aquaculture wastewater purification systems.
Environmental change is a physical and psychosocial stressor that generates varied emotional responses with implications for mental health and wellbeing. Existing reviews on environmental change, emotions and mental health are heavily dominated by studies from high-income settings and rarely examine how emotional responses are conceptualised in African contexts. Here, we synthesise evidence linking environmental emotions with wellbeing in Africa and critically examine the theoretical foundations of the existing literature. Sixty-three studies were reviewed. Findings indicate that negative emotions dominate the literature, particularly anxiety and fear. These emotions are consistently associated with adverse mental health outcomes, including depression, psychological distress, post-traumatic stress, suicidality, and functional impairments. Some studies captured culturally specific expressions of distress, such as kutekateka munonga (excessive thinking) and kuliblikia (water related worry/unease). Other studies document positive emotions: hope, optimism, pride, gratitude, and resilience, that support adaptive capacity, collective coping, and dignity in the face of environmental change. Theoretical frameworks were predominantly drawn from psychology, anthropology, geography, and political ecology, with most studies adopting Western-origin theories without explicit adaptation to African contexts. Indigenous methodologies and frameworks were largely absent. Environmental emotions research in Africa reveals the psychological burdens and the resilience of communities experiencing ecological stress, even though there are significant methodological and theoretical gaps. We therefore emphasise the need for culturally grounded and Indigenous methodologies and for systematic adaptation and validation of theories and measures to better capture the lived realities of African communities experiencing ecological change.
Estuarine sediments are both critical sinks and potential secondary sources of heavy metals, with environmental risks determined not only by total concentrations but critically by geochemical speciation. The eastern Lingdingyang, a highly industrialized urban-estuarine interface in the Guangdong-Hong Kong-Macao Greater Bay Area, remains largely understudied despite decades of intense anthropogenic stress. This study analyzed total and 0.1 M HCl-extractable labile concentrations of seven priority heavy metal(loid)s (Cu, Zn, Pb, Cr, Cd, Hg, As) in 132 surface sediment samples collected in the eastern coastal waters of Lingdingyang. Enrichment factor (EF) and positive matrix factorization (PMF) models were applied for source apportionment, while an integrated risk framework coupling the Canadian Sediment Quality Guidelines (CSQG), Risk Assessment Code (RAC), and a four-quadrant classification was employed to evaluate potential ecological and screening-level human health risks. Results revealed pronounced spatial heterogeneity with marked north-south decreasing gradients for Cu, Zn, Cr, and Cd, with hotspots concentrated in Jiaoyi Bay, Maozhou River estuary and adjacent Shajing-Fuyong Industrial Parks. Four major sources were quantified: PCB manufacturing and electroplating (38.2%), electronics and chemical industries (26.7%), historical coal combustion (18.5%), and natural lithogenic weathering (16.6%). Cd, Cu, and Zn exhibited high labile proportions and strong total-labile correlation. ~ 9.85% of stations were classified as priority control sites, with Cu dominating non-carcinogenic risks and Cd driving widespread potential carcinogenic risks. These findings fill a critical regional research gap and provide robust geochemical evidence for targeted pollution mitigation in industrialized coastal zones.
Wheat (Triticum aestivum L.), playing a significant role in providing food security and agricultural economy, is one of the most important cereals in the world. The present experiment aimed to determine the optimal levels of organic compounds (fulvic acid, humic acid, and amino acids) to promote sustainable wheat (cv. Taktaz) cultivation in dry and semi-dry regions while reducing dependency on irrigation water. The experiment was conducted as a split-factorial based on a randomized complete block design (RCBD) with three replications during two cropping years, 2023-2025. Results indicated that three-way interactions were statistically significant at the 0.01 level for all traits except number of fertile spikes and number of grains per spike. According to the polygon view of the traits, applying high amounts of fulvic acid as well as average amounts of the amino acid can have positive effects on controlling stress. In addition, increasing the concentration of humic acid can compensate for low concentrations of compounds like fulvic acid and amino acids. According to the treatment stability diagram, treatments 3 (humic acid 12 L h- 1) and 6 (amino acid 1.5 L h- 1, humic acid 12 L h- 1) under normal irrigation conditions, and 27 (fulvic acid 6 L h- 1, amino acid 3 L h- 1, humic acid 12 L/ha) under drought stress conditions, were selected as desirable treatments. The fact that increasing organic matter, like fulvic acid and amino acids, is helpful in plant metabolism regulation and resistance enhancement against drought stress reveals the effects of compounds included in these treatments on the plant's resistance to the stress. The treatment with the highest amount of organic compounds (6 L ha- 1 fulvic acid, 3 L ha- 1 amino acid, 12 L ha- 1 humic acid) was identified as the treatment with positive coefficients in relation to the first two components in both years. Under drought stress conditions in both years, grain yield had positive coefficients for the first two principal components. Likewise, flag leaf width had positive effects on the fourth component in both years. Treatments with high fulvic acid and medium humic acid (3 L ha- 1 fulvic acid, 1.5 L ha- 1 amino acid, 12 L ha- 1 humic acid; 6 L ha- 1 fulvic acid; and 6 L ha- 1 fulvic acid, 8 L ha- 1 humic acid) consistently appeared with strong relationships in the correlation network in both years. In general, treatments with moderate fulvic acid and high humic acid can be selected as desirable treatments under both normal and stress conditions. Selecting these treatments indicated that using fulvic acid and humic acid, along with an amino acid that plays a significant role, had the highest positive effects on yield improvement under both normal and irrigation stress conditions.
The anaerobic/aerobic/anoxic (AOA) process offers a low-carbon pathway for biological nitrogen removal from low carbon-to-nitrogen (C/N) ratio municipal wastewater, yet its complete greenhouse gas (GHG) footprint across gas and liquid phases remains unresolved. This study systematically quantified gaseous and dissolved CH4, CO2, and N2O at each operational stage of a laboratory-scale AOA system using phase-resolved monitoring. The system achieved stable nitrogen removal of 86.2%, with a CO2-equivalent direct gaseous emission factor was 25.2%-36.6% lower than that of the conventional wastewater treatment processes. However, phase-resolved accounting revealed that dissolved GHGs constituted the dominant fraction of total GHG footprint, with an intensity of 0.780 kg CO2e m⁻³-3.3-fold higher than direct gaseous emissions (0.237 kg CO2e m⁻³)-exposing a critically underreported hidden carbon reservoir. N2O was the principal climate driver, contributing 88.7% of total GHG intensity (1.010 kg CO2e m⁻3). The aerobic stage emerged as the primary emission hotspot (0.424 kg CO2e m⁻3), with N₂O accounting for 93.1% (0.395 kg CO2e m⁻3) of its intensity, potentially associated with hydroxylamine-related pathways under partial nitritation conditions and the enrichment of Nitrosomonas. In the anoxic stage, Bacteroidota and GAOs may participate in endogenous carbon cycling and denitrification, facilitating dissolved N2O reduction. These findings demonstrate that accurate GHG accounting for AOA systems must integrate concurrent gas-liquid phase monitoring, and that targeted aeration control to suppress aerobic N2O generation is essential for achieving genuinely carbon-neutral nitrogen removal.
IrO2 as the most stable electrocatalyst for acidic oxygen evolution reaction (OER) suffers from its low activity and the limited abundance in earth crust. Doping is one of promising strategies to enhance the OER activity and stability of IrO2. Herein, an interstitial carbon-doped IrO2 (Cin-IrO2) catalyst is prepared for acidic OER. The Cin-IrO2 shows an OER overpotential of 227 mV at 10 mA cm-2, a mass activity of 565.1 A gIr -1 at 1.53 V, and a 2000-h stability with a degradation rate of 0.04 mV h-1. The enhanced OER activity and stability originate from the formation of C─Ir bonds in the Cin-IrO2, which results in a prominent down-shift of Ir d-band center and the up-shift of O p-band center. Such variations of electronic states not only optimize the adsorption of OER intermediates but also increases the covalence of Ir─O bond. The Cin-IrO2 also enables an intra-surface hydrogen abstraction from *OOH to produce *OO, which also enhances the OER activity. The Cin-IrO2-based proton exchange membrane (PEM) water electrolyzer delivers a ultrasmall cell voltages of 1.51 V at 1 A cm-2 and 1.96 V at 3 A cm-2. Our findings demonstrate a new method for enhancing the acidic OER performance of IrO2.
Developing highly active and durable acidic oxygen evolution reaction (OER) electrocatalysts remains a central challenge for proton-exchange membrane water electrolysis (PEMWE). Here, we combine theory-guided design, atomic-layer engineering, and operando spectroscopy to create a structurally robust, mechanistically tuned Ru-based catalyst. Density functional theory reveals that depositing W1O3 onto RuO2 maximizes Ru and O vacancy formation energies, outperforming other tested transition metals. Guided by this, we employ atomic layer deposition to construct atomically coupled W-O-Ru interfacial units on RuO2 (W-O-RuO2), generating a tensile-stressed surface while preserving the rutile core. Comprehensive in situ spectroscopy and mass spectrometry demonstrate that this architecture effectively suppresses lattice-oxygen activation, shifting the reaction from a lattice-oxygen mechanism to a more reversible adsorbate evolution mechanism. Operando x-ray absorption spectroscopy confirms the dynamic stability of the W-O-Ru interface during OER, which evolves into a resilient, mildly compressive (1%) state without degrading. Consequently, W-O-RuO2 demands a mere 168 mV overpotential at 10 mA cm- 2 and sustains 1 A cm- 2 in a PEMWE device for 1000 h with an ultra-low degradation rate of 63.3 µV/h. This work establishes interfacial unit engineering as a generalizable blueprint for designing exceptionally stable acidic OER catalysts.
Extensive application of the widely used herbicide glyphosate has made it a ubiquitous environmental pollutant. In our previous study in 2019, glyphosate and its metabolite aminomethylphosphonic acid (AMPA) were detected in Baltic Sea waters for the first time. Initial evidence from that study suggested that glyphosate might be more persistent than AMPA. Our goal was to expand upon these preliminary findings by providing a more comprehensive temporal and spatial assessment for the Baltic Sea. In order to examine glyphosate and AMPA seasonal fluctuations and spatial distribution, we analyzed surface water samples from (1) the Baltic Sea, taken during winter and summer of 2020, (2) from a coastal site over the course of a year, and (3) from two selected tributaries. Glyphosate and AMPA were detected at all study sites and concentrations varied seasonally and spatially. In winter 2020, Baltic Sea surface water median concentrations were 0.21 and 2.52 ng L-1 for glyphosate and AMPA, respectively, while 0.53 and 1.03 ng L-1 were determined in summer 2020; median concentrations at the coastal site were 0.96 and 2.81 ng L-1, over the entire year. Measured glyphosate concentrations at the tributaries and the coastal site indicate potential for temporary medium risk to aquatic organisms. Results from a seawater degradation experiment using isotopically labelled substrates suggest that AMPA is removed faster than glyphosate. This supports the observed distribution pattern for both compounds in the Baltic Sea.
PBDEs are persistent organic pollutants used as flame retardants in consumer products. Despite regulatory restrictions in Europe, their persistence, bioaccumulation, and long-range transport remain environmental concerns. This systematic review assessed the occurrence, distribution, and congener-specific patterns of PBDEs across European environmental compartments and examined the implications of legacy sources and regulatory frameworks. The review followed PRISMA guidelines and was registered in PROSPERO (CRD420251207298). Peer-reviewed studies were retrieved from Ovid, Scopus, and Web of Science up to November 2025. In total, 181 studies met the inclusion criteria. Data were synthesized across air, water, sediments, soils, snow/firn, and sludge. Study quality and risk of bias were assessed using the SURE checklist. PBDEs were widely detected across Europe in both impacted and remote environments, with distributions strongly dependent on matrix type. Water generally showed lower, more transient concentrations, whereas sediments, sludge, and some soils acted as major reservoirs. BDE-209 dominated particle-rich matrices, including sediments, wastewater-related systems, and deposition, while lower-brominated congeners such as BDE-47 and BDE-99 were more prominent in air and soils. The highest burdens were typically linked to urban, industrial, wastewater-affected, and waste-handling environments, whereas alpine, Arctic, and background sites showed lower but measurable contamination. Several studies reported declining trends, especially in air and soil, but continued detection reflected persistence in legacy materials, recycled products, contaminated reservoirs, and waste streams. PBDEs remain environmentally relevant across Europe despite regulatory controls. Their persistence across compartments and continued release from legacy sources highlight the need for harmonized multi-matrix monitoring, improved QA/QC reporting, and greater attention to BDE-209, transformation products, and replacement flame retardants.
Fjords in Chilean Patagonia are highly dynamic systems shaped by land-derived inputs, oceanic exchange, and volcanic activity. Prior to the elaboration of the present article, no in-depth investigation had been undertaken into the anoxic or euxinic conditions of fjords in this region. Consequently, the present research represents an interdisciplinary oceanographic approach to studying Quitralco Fjord (45.6° S, 73.1° W; 2022-2025) and provides the first evidence of a volcanically influenced euxinic fjord in Chilean Patagonia. A subsurface anoxic layer, beginning between 90 and 120 m and extending to the basin floor (~ 160 m), was shown to exhibit elevated temperatures and high concentrations of H2S, consistent with inputs of volcanically derived fluids. A bubble-like acoustic scattering and the detection of CH4 within this layer suggest an external input of the gas into the water column. Although largely stagnant, this layer shifted vertically over time, likely driven by interannual deep-water renewal. Within the euxinic layer, nitrate was completely depleted, while high phosphate (20 μm) and ammonium (25 μm) concentrations indicated an active sulfur cycle. A pronounced deep fluorescence maximum was also detected in the dark, anoxic basin, attributed to fluorescent dissolved organic matter (fDOM) dominated by two humic-like components (C1245(350)-440 and C3270(400)-505) with high aromaticity. Microbial community composition changed markedly across the redox gradient, while geochemical and microbiological fingerprints exhibited shifts in metabolic potential through the water column. Geological emissions of H2S from the seabed and microbial sulfate reduction may contribute to the observed H2S accumulation, enhancing and sustaining euxinic conditions, thereby strongly influencing the basin's biogeochemical cycles. Overall, the present study reveals a previously unrecognized link between volcanic activity and fjord biogeochemistry, documenting for the first time the development of euxinic conditions in a Patagonian fjord in Chile.
Industrial waste sites containing naturally occurring radioactive material represent long-term and globally relevant environmental challenges, particularly where chemical and radiological stressors affect terrestrial and aquatic ecosystems. The study site is a legacy alum shale mining waste pile and is one of the most contaminated sites in Sweden. Ongoing exothermic reactions within the pile maintain elevated temperatures, creating a challenging and complex environment with evolving contaminant mobility and exposure pathways. As the pile cools, increased water infiltration is expected to increase leaching of heavy metals and radionuclides into the environment. Thus, a comprehensive radiological characterisation and ecological risk assessment was conducted across multiple compartments to evaluate current and future environmental impacts. A total of 68 samples of soil, shale ash, sediment, surface water, groundwater, and plants were analysed for radionuclides from the 238U and 232 Th decay series. Ambient dose rates were measured in situ, and radiological risk to humans and non-human biota was assessed using the ERICA Tool. Activity concentrations and dose rates across the surface of the site showed pronounced spatial variability associated with the presence of alum shale residues. Among the analysed radionuclides, 230Th dominated in soil and shale ash, uranium isotopes in surface water, and 210Po in vegetation. Soil-to-plant concentration ratios for uranium, thorium, radium, and polonium were generally low, averaging a few percent across 15 plant species, indicating limited bioavailability despite elevated source term concentrations. Similar ratios were observed for isotopes of the same element, suggesting that gamma spectrometry, when applicable, could provide a cost-effective alternative for large-scale environmental risk assessment. The ecological risk assessment indicated that radiological risk to biota at the waste pile and aquatic systems cannot be considered negligible. Although radiological risk to members of the public from external exposure was low, prolonged daily visits revealed potential doses approaching regulatory reference levels.
The past decade has seen increased research interest on the possible alternatives to cement in concrete and mortar, with materials that are environmentally friendly, economical, and socially inherent. However, recycling, reusing, and regenerating methods may be used to harness the potential benefits of agricultural/industrial wastes as alternatives. The utilization of these recyclables as supplementary and alternative resources yields notable energy conservation and a reduction in cement consumption, thus contributing to the mitigation of carbon dioxide (CO₂) emissions in the environment. Moreover, groundnut shell ash (GSA) is utilized as a substitution for cement in the mixture. The proportion of cement substitution with GSA ranged from 0% to 20% in order to examine the characteristics of concrete and mortar. Concrete samples were cast and tested at 7th, 14th, 28th, and 90th days. Cube, cylinder, and prism specimens were cast for assessing the compressive, flexural, and splitting tensile strengths of concrete consistently. It was discovered that the highest compressive and splitting tensile strengths were 13.39% and 12.69%, respectively, over the control at 90 days, and the flexural strength was 10.64% at 28 days of curing over the control for 10% GSA cement replacement. Also, the water absorption, and drying shrinkage dropped with the increased content of GSA. Besides, the utilization of GSA in the mixture has reduced the embodied carbon. Furthermore, utilizing ANOVA, response prediction approaches were produced at a 95% significance level. The models demonstrated R² ranging from 96 to 99%. Therefore, the research study's findings indicate that the addition of GSA in concrete positively affects the concrete and mortar properties and recommends a 10% substitution of cement in the mixture.