Seabird eggs are considered a favourable matrix for monitoring marine pollutants and are widely used as higher trophic level indicators. Persistent organic pollutants such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and other organochlorine compounds (OCs) as well as metals have been shown to have deleterious impacts on seabirds. The Northern Gannet Morus bassanus is an avian sentinel; the largest breeding seabird in Ireland and an obligate piscivore. Gannet eggs were collected from two island colonies off the east coast of Ireland in locations with divergent history of industrialisation. Contaminant levels were measured and differences in concentrations between colonies compared. Stable isotope ratios of carbon (δ₁₃C) and nitrogen (δ₁₅N) were measured in each egg to understand the influence of diet and trophic position on contaminant levels detected. Significantly higher levels of Σ14PCBs, Σ7PBDEs and total mercury were detected in Gannet eggs from Lambay Island near Dublin (Ireland’s industrialised capital city) compared to Great Saltee Island. No differences were observed in levels of other OCs (HCB, ΣHCH, ΣCHL, ΣDDT) between the two colonies. Though Gannets travel significant distances when foraging for food, tracking studies have demonstrated that birds from proximal breeding colonies maintain exclusive feeding areas. Stable isotope ratio analysis in this study demonstrated that Gannets at both locations occupy similar dietary niches, indicating that dietary differences may not be the driver of differing contaminant levels between colonies. Levels of persistent pollutants in the Gannet eggs fall below most existing thresholds for adverse effects and are within internationally reported values. Recent population growth and range expansion of Gannets in Ireland suggest that persistent pollutants are not having an immediate impact on the Gannet population. This study will inform potential monitoring programmes that can help Ireland achieve good environmental status under the European Union’s Marine Strategy Framework Directive.

Complex air pollutant sources and distinct meteorological conditions resulted in unique wintertime haze pollution in the Harbin-Changchun (HC) metropolitan area, China’s only national-level city cluster located in the severe cold climate region. In this study, field observation and air quality modeling were combined to investigate fine particulate matter (PM₂.₅) pollution during a six-month long heating season in HC’s central city (Harbin). The model significantly underpredicted PM₂.₅ and organic carbon (by up to ∼230 μg/m³ and 110 μgC/m³, respectively, in terms of daily average) when levoglucosan concentrations were above 0.5 μg/m³. Based on a synthesis of levoglucosan concentrations and fire counts, the large gaps were attributed to underestimation of open burning emissions by the model. However, the model tended to overpredict elemental carbon (more significantly at higher NO₂), likely pointing to an overestimation of vehicle emissions. With increasing levoglucosan, the difference between observed and simulated nitrate (nitrateₒbₛ ‒ nitrateₘₒd, i.e., Δnitrate) showed a transition from negative to positive values. The positive Δnitrate were attributed to underprediction of the open-burning related nitrate, whereas the negative Δnitrate were likely caused by overprediction of nitrate from other sources (presumably vehicle emissions). The dependence of Δnitrate on levoglucosan indicated that with stronger impact of open burning, the overprediction effect was gradually offset and finally overwhelmed. Influence of open burning on sulfate formation was evident as well, but less apparent compared to nitrate. This study illustrates how the uncertainties in open burning emissions will influence PM₂.₅ simulation, on not only primary components but also secondary species.

Herein, we report the optimization of nitrogen (N) doping in TiO₂ nanotubes to achieve the enhanced photocatalytic efficiencies in degradation of dye and H₂ gas evolution under solar light exposure. TiO₂ nanotubes have been produced via hydrothermal process and N doping has been tuned by varying the concentration of urea, being the source for N, by solid-state dispersion process. The structural analysis using XRD showed the characteristic occupancy of N into the structure of TiO₂ and the XPS studies showed the existence of Ti–N–Ti network in the N-doped TiO₂ nanotubes. The obtained TEM images showed the formation of 1D tube-like structure of TiO₂. Diffuse reflectance UV–Vis absorption spectra demonstrated that the N-doped TiO₂ nanotubes can efficiently absorb the photons of UV–Vis light of the solar light. The optimized N-doped TiO₂ nanotubes (TiO₂ nanotubes vs urea @ 1:1 ratio) showed the highest degradation efficiency over methyl orange dye (∼91% in 90 min) and showed the highest rate of H₂ evolution (∼19,848 μmol h⁻¹.g⁻¹) under solar light irradiation. Further, the recyclability studies indicated the excellent stability of the photocatalyst for the durable use in both the photocatalytic processes. The observed efficiency was ascribed to the optimized doping of N-atoms into the lattices of TiO₂, which enhanced the optical properties by forming new energy levels of N atoms near the valence band maximum of TiO₂, thereby increased the overall charge separation and recombination resistance in the system. The improved reusability of photocatalyst is attributed to the doping-induced structural stability in N-doped TiO₂. From the observed results, it has been recognized that the established strategy could be promising for synthesizing N-doped TiO₂ nanotubes with favorable structural, optical and photocatalytic properties towards dye degradation and hydrogen production applications.

The current study for the first time demonstrates the interference of a free-living, N₂-fixing, and nanoparticle (NP) tolerant Azotobacter salinestris strain ASM recovered from metal-polluted soil with tomato plant-metal oxide NPs (ZnO, CuO, Al₂O₃, and TiO₂) interactions in a sandy clay loam soil system with bulk materials as control. Tomato plants were grown till full maturity in soils amended with 20–2000 mg kg⁻¹ of each metal-oxide NP with and without seed biopriming and root-inoculation of A. salinestris. A. salinestris was found metabolically active, producing considerably high amounts of bioactive indole-3-acetic-acid, morphologically unaffected, and with low alteration of cell membrane permeability under 125–1500 μgml⁻¹ of NPs. However, ZnO-NPs slightly alter bacterial membrane permeability. Besides, A. salinestris secreted significantly higher amounts of extracellular polymeric substance (EPS) even under NP exposure, which could entrap the NPs and form metal-EPS complex as revealed and quantified by SEM-EDX. NPs were also found adsorbed on bacterial biomass. EPS stabilized the NPs and provided negative zeta potential to NPs. Following soil application, A. salinestris improved the plant performance and augmented the yield of tomato fruits and lycopene content even in NPs stressed soils. Interestingly, A. salinestris inoculation enhanced photosynthetic pigment formation, flower attributes, plant and fruit biomass, and reduced proline level. Bacterial inoculation also reduced the NP’s uptake and accumulation significantly in vegetative organs and fruits. The organ wise order of NP’s internalization was roots > shoots > fruits. Conclusively, A. salinestris inoculation could be an alternative to increase the production of tomato in metal-oxide NPs contaminated soils.

Microorganism-assisted phytoremediation is being developed as an efficient green approach for management of toxic metals contaminated soils and mitigating the potential human health risk. The capability of plant growth promoting Actinobacteria (Streptomyces pactum Act12 - ACT) and Firmicutes (Bacillus subtilis and Bacillus licheniformis - BC) in mono- and co-applications (consortium) to improve soil properties and enhance phytoextraction of Cd, Cu, Pb, and Zn by Brassica juncea (L.) Czern. was studied here for the first time in both incubation and pot experiments. The predominant microbial taxa were Proteobacteria, Actinobacteria and Bacteroidetes, which are important lineages for maintaining soil ecological activities. The consortium improved the levels of alkaline phosphatase, β-D glucosidase, dehydrogenase, sucrase and urease (up to 33%) as compared to the control. The bacterial inoculum also triggered increases in plant fresh weight, pigments and antioxidants. The consortium application enhanced significantly the metals bioavailability (DTPA extractable) and mobilization (acid soluble fraction), relative to those in the unamended soil; therefore, significantly improved the metals uptake by roots and shoots. The phytoextraction indices indicated that B. juncea is an efficient accumulator of Cd and Zn. Overall, co-application of ACT and BC can be an effective solution for enhancing phytoremediation potential and thus reducing the potential human health risk from smelter-contaminated soil. Field studies may further credit the understanding of consortium interactions with soil and different plant systems in remediating multi-metal contaminated environments.

Heavy metal pollution in paddy fields has caused widespread concerns due to the threat to food safety. The present study used low-cost sugarcane bagasse (SB) and two sugarcane bagasse materials modified with citric-acid (SSB) and citric-acid/Fe₃O₄ (MSB) to investigate their effects on the bioavailability of Cd in soil and Cd accumulations in rice in a pot experiment. The three organic amendments significantly decreased the Cd accumulation in plants by limiting its mobilization in soil. The MSB and SSB but not SB increased the soil pH and immobilized the Cd in soil significantly during the 120-day experiment. The amendments decreased Cd bioavailability through transforming to the stable fraction throughout the whole growth stage. The functional groups in the amendments (-OH, –COOH, C–O, -COO⁻ and Fe–O) and precipitates [Cd(NO₂)₂K(NO₂)₂, Cd(OH)₂ and Cd₇₅Zn₂₅Fe₂O₄] played active roles in Cd immobilization. Moreover, the three organic materials increased the content of Fe–Mn plaque on rice roots, which prevented its transport from soil to rice roots further. We also found that Fe competed with Cd for transporters and reduced potential Cd uptake and translocation in rice tissues. The addition of MSB and SB but not SSB inhibited the rice growth compared to the unamended control, indicating the potential of SSB in situ remediation. These results provide valuable information to use organic amendments for Cd passivation in soil and food safety.

Air pollution is a complex process and is affected by meteorological conditions and other chemical components. Numerous studies have demonstrated that data-driven spatio-temporal prediction models of PM₂.₅ concentration are comparable with the model-driven model. However, data-driven models are usually depending on the statistical correlation between PM₂.₅ and other factors and have challenges in dealing with causality in complex systems. In this paper, we argue that domain knowledge should be incorporated into data-driven models to enhance prediction accuracy and make the model more physically realistic. We focus on the influence of dynamic wind-field on PM₂.₅ concentration distribution and fuse the pollution diffusion distance with the deep learning model based on a wind-field surface. In order to model spatial dependence between monitoring stations, which is dynamic and anisotropic because of the wind-field, we proposed a hybrid deep learning framework, dynamic directed spatio-temporal graph convolution networks (DD-STGCN). It expanded the ability to deal with space-time prediction in the continuous and dynamic wind-field. We used a directed graph time-series to describe the vertex state and topological relationship between vertices and replaced traditional Euclidean distance with wind-field diffusion distance to describe the proximity relationship between vertices. Our experiment results demonstrated that the DD-STGCN model achieved a better prediction ability than LSTM, GC-LSTM, and STGCN models. Compared to the best comparison model, MAPE, MAE, and RMSE were improved by 10.2%, 9.7%, and 9.6% in 12 h on an average, respectively. The performance of our model was further tested during a haze period. In the case that two models both considered the effect of wind, compared with the pure data-driven model, our model performed better in prediction distribution and showed the benefit of spatial interpretability provided by domain knowledge.

A green approach using hydrogen peroxide (H₂O₂) to intensify the fuel properties of spent coffee grounds (SCGs) through torrefaction is developed in this study to minimize environmental pollution. Meanwhile, a neural network (NN) is used to minimize bulk density at different combinations of operating conditions to show the accurate and reliable model of NN (R² = 0.9994). The biochar produced from SCGs torrefied at temperatures of 200–300 °C, duration of 30–60 min, and H₂O₂ concentrations of 0–100 wt% is examined. The results reveal that the higher heating value (HHV) of biochar increases with rising temperature, duration, or H₂O₂ concentration, whereas the bulk density has an opposite trend. The HHV, ignition temperature, and bulk density of biochar from torrefaction at 230 °C for 30 min with a 100 wt% H₂O₂ solution (230-100%-TSCG) are 27.00 MJ∙kg⁻¹, 292 °C, and 120 kg∙m⁻³, respectively. This HHV accounts for a 29% improvement compared to that of untorrefied SCG. The contact angle (126°), water activity (0.51 aw), and moisture content (7.69%) of the optimized biochar indicate that it has higher resistance against biodegradation, and thereby can be stored longer. Overall, H₂O₂ is a green treatment additive for SCGs solid fuel. This study has successfully produced biochar with greater HHV and low bulk density at low temperatures. The green additive development can effectively reduce environmental pollutants and upgrade wastes into resources, and achieve “3E”, namely, environmental (non-polluting green additives), energy (biofuel), and circular economy (waste upgrade). In addition, the produced biochar has great potential in the fields of bioadsorbents and soil amendments.

Paraquat (PQ), a widely used herbicide and well-known oxidative stress inducer, has been linked to numerous neurodegenerative diseases, but the underlying mechanism(s) remains unknown. Circular RNAs (circRNAs) have recently been reported to be associated with oxidative stress in Parkinson's disease. Herein, we performed methylated RNA immunoprecipitation and RNA sequencing assays for mouse neuroblastoma (Neuro-2a) cells and successfully established a positive link between the alteration of circRNAs driven by m⁶A modification and PQ-induced oxidative stress. We observed oxidative stress and antioxidative stress present distinct m⁶A modification pattern of circRNAs as well as biological effect. Gene ontology and pathway analysis predicted that differentially m⁶A-methylated and expressed circRNAs are highly clustered in pathways associated with function and development of nervous system, including axon cargo transport, nervous system development, long-term potentiation, and neurotrophic signaling pathways. Moreover, we demonstrated that the alteration of m⁶A-methylated circRNAs upon PQ exposure could be partially reversed by N-acetylcysteine pretreatment. The mechanistic analysis further demonstrated that N-acetylcysteine pretreatment attenuated the decreased expression of target genes (UBC and PPP2CA) induced by PQ. These findings revealed distinct patterns of differentially m⁶A-modified circRNAs, indicating that m⁶A could participate in a specific regulatory network of circRNAs to modulate the expression of downstream genes in response to PQ-induced oxidative stress. In conclusion, our work established a link between m⁶A modification of circRNAs and PQ-induced oxidative stress, and further studies are required to explore the underlying molecular mechanisms associated with PQ-induced neurotoxicity.

Hydraulic fracturing has become widely used in recent years to access vast global unconventional sources of oil and gas. This process involves the injection of proprietary mixtures of water and chemicals to fracture shale formations and extract the hydrocarbons trapped within. These injection fluids, along with minerals, hydrocarbons, and saline waters present within the formations being drilled into, return to the surface as flowback and produced water (FPW). FPW is a highly complex mixture, containing metals, salts and clay, as well as many organic chemicals, including polycyclic aromatic hydrocarbons such as phenanthrene. The present study sought to determine the effects of temperature on the accumulation of phenanthrene in rainbow trout (Oncorhynchus mykiss). This model organism resides in rivers overlapping the Montney and Duvernay formations, both highly developed formations for hydraulic fracturing. Rainbow trout acclimated to temperatures of 4, 13 and 17 °C were exposed to either 5% or 20% FPW, as well as saline mixtures representing the exact ionic content of FPW to determine the accumulation of radiolabelled ¹⁴C phenanthrene within the gill, gut, liver and gallbladder. FPW exposure reduced the overall accumulation of phenanthrene in a manner most often similar to high salinity exposure, indicating that the high ionic strength of FPW is the primary factor affecting accumulation. Accumulation was different at the temperature extremes (4 and 17 °C), although no consistent relationship was observed between temperature and accumulation across the observed tissues. These results indicate that several physiological responses occur as a result of FPW exposure and water temperature change which dictate phenanthrene uptake, particularly in the gills. Temperature (and seasonality) alone cannot be used to model the potential accumulation of polycyclic aromatic hydrocarbons after FPW spills.