The subcellular partitioning approach provides useful information on the location of metals within cells and is often used on organisms with high levels of bioaccumulation to establish relationships between the internal concentration and the potential toxicity of metals. Relatively little is known about the subcellular partitioning of metals in wild fish with low bioaccumulation levels in comparison with those from higher contaminated areas. This study aims to examine the subcellular partitioning of various metals considering their chemical affinity and essentiality at relatively low contamination levels. Class A (Y, Sr), class B (Cu, Cd, MeHg), and borderline (Fe, Mn) metal concentrations were measured in livers and subcellular fractions of yellow perch (n = 21) collected in Lake Saint-Pierre, QC, Canada. The results showed that all metals, apart from MeHg, were distributed among subcellular fractions according to their chemical affinity. More than 60% of Y, Sr, Fe, and Mn were found in the metal-sensitive fractions. Cd and Cu were largely associated with the metallothionein-like proteins and peptides (60% and 67% respectively) whereas MeHg was found mainly in the metal-sensitive fractions (86%). In addition, the difference between the subcellular distribution of Cu and other essential metals like Fe and Mn denotes that, although the essentiality of some metals is a determinant of their subcellular distribution, the chemical affinity of metals is also a key driver. The similarity of the subcellular partitioning results with previous studies on yellow perch and other fish species from higher contaminated areas supports the idea that metals are distributed in the cellular environment according to their chemical properties regardless of the bioaccumulation gradient.

Contamination of heavy metals is a serious threat, which causes threats to the environment. Our study aimed to determine the role of endophytic bacteria in Cd phytoremediation and heavy metal ATPase gene expression. Cadmium (Cd) resistant endophytic bacteria were isolated from Solanum nigrum on LB agar plates, contaminated with 0–30 mg/L Cd. The phosphate solubilization and indole-3-acetic acid (IAA) production of endophytes were estimated by growing them on Pikovskaya agar medium and GC-MS analysis, respectively. An experiment in a pot was performed to evaluate the effects of bacteria on rice plants contaminated with 5–25 mg/L of Cd. Expression of Cd response genes was quantified through qRT–PCR and Cd translocation from one part to another part of the plant was measured through the ICP. BLAST alignment of 16 S-rDNA gene sequences confirmed the bacterial isolates as Serratia sp. AI001 and Klebsiella sp. Strain AI002. Both strains tolerated Cd up to 25 mg/L and produced 27–30 μg/mL of IAA. Inoculation of AI001 and AI002 improved plant growth dynamics (i.e., plant length, biomass, chlorophyll contents), relieved electrolyte leakage, and improved reduced glutathione significantly (P < 0.05). The inoculation of AI001 and AI002 significantly (P < 0.05) induced the expression of heavy metal ATPase genes ie., “HMA2, HMA3, and HMA4” and Cd translocation compared to uninoculated plants. Both AI001 and AI002 exhibited very prominent plant-growth-promoting and Cd phytoremediation properties. The results revealed that isolates also contributed a lot to the expression of rice plant heavy metal ATPase genes and in the Cd translocation in the plant.

Predicting the occurrence of algal blooms is of great importance in managing water quality. Moreover, the demand for predictive models, which are essential tools for understanding the drivers of algal blooms, is increasing with global warming. However, modeling cyanobacteria dynamics is a challenging task. We developed a multivariate Chain-Bernoulli-based prediction model to effectively forecast the monthly sequences of algal blooms considering hydro-environmental predictors (water temperature, total phosphorus, total nitrogen, and water velocity) at a network of stations. The proposed model effectively predicts the risk of harmful algal blooms, according to performance measures based on categorical metrics of a contingency table. More specifically, the model performance assessed by the LOO cross-validation and the skill score for the POD and CSI during the calibration period was over 0.8; FAR and MR were less than 0.15. We also explore the relationship between hydro-environmental predictors and algal blooms (based on cyanobacteria cell count) to understand the dynamics of algal blooms and the relative contribution of each potential predictor. A support vector machine is applied to delineate a plane separating the presence and absence of algal bloom occurrences determined by stochastic simulations using different combinations of predictors. The multivariate Chain-Bernoulli-based prediction model proposed here offers effective, scenario-based, and strategic options and remedies (e.g., controlling the governing environmental predictors) to relieve or reduce increases in cyanobacteria concentration and enable the development of water quality management and planning in river systems.

Biodegradable cellulosic pulp foams with robustness and water resistance are urgently needed in nowadays to replace petroleum-based plastic foams for environmental sustainability. In this work, a facile protocol to fabricate robust poly-lactic acid (PLA) coated cellulose foams (PCCF) was developed through a combined water-based foaming and PLA melt-coating process using pulp as the raw material. In the synthesis, the so-called PLA coating was realized through melting PLA powders dispersed between fibers by an in-situ heating and post cooling process. Performance tests revealed that the incorporation of PLA coating significantly enhances mechanical strength, water stability, and biodegradability of the synthesized PCCF samples compared with conventional cellulosic foams. Specifically, the low-density PCCF were observed with mechanical strength up to 81.24 kPa, high water stability, and more than 95% degradation in 56 days. As the fabrication process is simple and pulp is highly cost competitive, our proposed synthesis strategy makes the PCCF a promising substitute for petroleum-based plastic foams at large-scale production.

Industrial seabed mining is expected to cause significant impacts on marine ecosystems, including physical disturbance and the generation of plumes of toxin-laden water. Portmán Bay (NW Mediterranean Sea), where an estimated amount of 60 Mt of mine tailings from sulphide ores were dumped from 1957 to 1990, is one of the most metal-polluted marine areas in Europe and worldwide. This bay can be used to assess the impact on marine ecosystems of particle settling from sediment plumes resulting from mine tailings resuspension. With this purpose in mind, we conducted a field experiment there to investigate subsequent effects of deposition of (artificially resuspended) contaminated sediments on (i) prokaryotic abundance and meiofaunal assemblages (in terms of abundance and diversity), (ii) the availability of trophic resources (in terms of organic matter biochemical composition), and (iii) a set of ecosystem functions including meiofaunal biomass, heterotrophic C production and C degradation rates. The results of this study show that mine tailings resuspension and plume deposition led to the decline of prokaryotic abundance and nematode's biodiversity. The later decreased because of species removal and transfer along with particle resuspension and plume deposition. Such changes were also associated to a decrease of the proteins content in the sediment organic matter, faster C degradation rates and higher prokaryotic C production. Overall, this study highlights that mine tailing resuspension and ensuing particle deposition can have deleterious effects on both prokaryotes and nematode diversity, alter biogeochemical cycles and accelerate C degradation rates. These results should be considered for the assessment of the potential effects of seabed mineral exploitation on marine ecosystems at large.

Graphene oxide (GO) has been widely studied and applied in numerous industrial fields and biomedical fields for its excellent physical and chemical properties. Along with the production and applications of GO persist increasing, the environmental health and safety risk (EHS) of GO has been widely studied. However, previous studies almost focused on the biotoxicity of pristine GO under a relatively high exposure dose, without considering its transformation process within environmental and biological mediums. Meanwhile, its secondary toxicity or synergistic effects have not been taken seriously. Here, two different kinds of artificial lung fluids were adopted to incubate pristine GO to mimic the biotransformation process of GO in the lung fluids. And, we explored that biotransformation within the artificial lung fluids could significantly change the physicochemical properties of GO and could enhance its biotoxicity. To reveal the synergistic effects of GO and toxic metal ions, we uncovered that GO could enhance the intracellular content of metal ions by inhibiting the efflux function of ATP binding cassette (ABC) transporters which are distributed on the cellular membrane, and artificial lung fluids incubation of GO could enhance this synergistic effect. Finally, toxic metal ions induced a series of toxic reactions through oxidative stress response and promoted cell death. Moreover, consistent with the results of in vitro experiments, the lungs of mice exposed to GOs combined with Cd exhibited significant inflammation and oxidative stress compared with Cd treatment alone, and it was more remarkable within the mice which were treated with bio-transformed GOs. In summary, this study explored the impact and mechanism of biotransformation of GO in the lung fluids on the synergistic and secondary effects between GO and metal ions.

Granular activated carbon (GAC) has been used to remove per- and polyfluoroalkyl substances (PFASs) from industrial or AFFF-impacted waters, but its effectiveness can be low because adsorption of short-chained PFASs is ineffective and its sites are exhausted rapidly by co-contaminants. To increase adsorption of anionic PFASs on GAC by electrostatic attractions, we modified GAC's surface with the cationic polymer poly diallyldimethylammonium chloride (polyDADMAC) and tested its capacity in complex water matrices containing dissolved salts and humic acid. Amending with concentrations of polyDADMAC as low as 0.00025% enhanced GAC's adsorption capacity for PFASs, even in the presence of competing ions. This suggests that electrostatic interactions with polyDADMAC's quaternary ammonium functional groups helped bind organic and inorganic ions as well as the headgroup of short-chain PFASs, allowing more overall PFAS removal by GAC. Evaluating the effect of polymer dose is important because excessive addition can block pores and reduce overall PFAS removal rather than increase it. To decrease the waste associated with this adsorption strategy by making the adsorbent viable for more than one saturation cycle, a regeneration method is proposed which uses low-power ultrasound to enhance the desorption of PFASs from the polyDADMAC-GAC with minimum disruption to the adsorbent's structure. Re-modification with the polymer after sonication resulted in a negligible decrease in the sorbent's capacity over four saturation rounds. These results support consideration of polyDADMAC-modified GAC as an effective regenerable adsorbent for ex-situ concentration step of both short and long-chain PFASs from real waters with high concentrations of competing ions and low PFAS loads.

Metal-free single heteroatom (N, O, and B)-doped coconut-shell biochar (denoted as N-CSBC, O-CSBC, and B-CSBC, respectively) were fabricated in a one-step pyrolysis process to promote peroxymonosulfate (PMS) activation for the elimination of sulfathiazole (STZ) from aquaculture water. B-CSBC exhibited remarkably high catalytic activity with 92% of STZ degradation in 30 min attributed to the presence of meso-/micro-pores and B-containing functional groups (including B–N, B–C, and B₂O₃ species). Radical quenching tests revealed SO₄•⁻, HO•, and ¹O₂ being the major electron acceptors contributing to STZ removal by PMS over B-CSBC catalyst. The B-CSBC catalyst has demonstrated high sustainability in multiple consecutive treatment cycles. High salinity and the presence of inorganic ions such as chloride, enhanced the performance of the sulfate radical-carbon-driven advanced oxidation processes (SR–CAOPs) as pretreatment strategy that significantly facilitated the removal of STZ from aquaculture water. Furthermore, a potential sulfonamide-degrading microorganism, Cylindrospermum_stagnale, belonging to the phylum Cyanobacteria, was the dominant functional bacteria according to the results of high-throughput 16S rRNA gene sequencing conducted after the B-CSBC/PMS treatment. This study provides new insights into the SR–CAOP combined with bioprocesses for removing STZ from aqueous environments.

Plume chasing is cost-effective, measuring individual, on-road vehicular emissions. Whereas, wake-flow-generated turbulence results in intermittent, rapid pollutant dilution and substantial fluctuating concentrations right behind the vehicle being chased. The sampling duration is therefore one of the important factors for acquiring representative (average) concentrations, which, however, has been seldom addressed. This paper, which is based on the detailed spatio-temporal dispersion data after a heavy-duty truck calculated by large-eddy simulation (LES), examines how sampling duration affects the uncertainty of the measured concentrations in plume chasing. The tailpipe dispersion is largely driven by the jet-like flows through the vehicle underbody with approximate Gaussian concentration distribution for x ≤ 0.6h, where x is the distance after the vehicle and h the characteristic vehicle size. Thereafter for x ≥ 0.6h, the major recirculation plays an important role in near-wake pollutant transport whose concentrations are highly fluctuating and positively shewed. Plume chasing for a longer sampling duration is more favourable but is logistically impractical in busy traffic. Sampling duration, also known as averaging time in the statistical analysis, thus has a crucial role in sampling accuracy. With a longer sampling (averaging) duration, the sample mean concentration converges to the population mean, improving the sample reliability. However, this effect is less pronounced in long sampling duration. The sampling accuracy is also influenced by the locations of sampling points. For the region x > 0.6h, the sampling accuracy is degraded to a large extent. As a result, acceptable sample mean is hardly achievable. Finally, frequency analysis unveils the mechanism leading to the variance in concentration measurements which is attributed to sampling duration. Those data with frequency higher than the sampling frequency are filtered out by moving average in the statistical analyses.

Heavy metal pollution and the potential for co-selection of resistance to antibiotics in the environment is growing concern. However, clear associations between heavy metals and antibiotic resistance in river systems have not been developed. Here we investigated relationships between total and bioavailable heavy metals concentrations; metal resistance gene (MRG) and antibiotic resistance gene (ARG) abundances; mobile genetic elements; and the composition of local bacterial communities in low and high metal polluted rivers in UK and India. The results indicated that MRGs conferring resistance to cobalt (Co) and nickel (Ni) (rcnA), and Co, zinc (Zn), and cadmium (Cd) (czcA), and ARGs conferring resistance to carbapenem and erythromycin were the dominating resistant genes across the samples. The relative MRGs, ARGs, and integrons abundances tended to increase at high metal polluted environments, suggesting high metals concentrations have a strong potential to promote metal and antibiotic resistance by horizontal gene transmission and affecting bacterial communities, leading to the development of multi-metal and multi-antibiotic resistance. Network analysis demonstrated the positive and significant relationships between MRGs and ARGs as well as the potential for integrons playing a role in the co-transmission of MRGs and ARGs (r > 0.80, p < 0.05). Additionally, the major host bacteria of various MRGs and ARGs that could be accountable for greater MRGs and ARGs levels at high metal polluted environments were also identified by network analysis. Spearman's rank-order correlations and RDA analysis further confirm relationships between total and bioavailable heavy metals concentrations and the relative MRG, ARG, and integron abundances, as well as the composition of related bacterial communities (r > 0.80 (or < −0.80), p < 0.05). These findings are critical for assessing the possible human health concerns associated with metal-driven antibiotic resistance and highlight the need of considering metal pollution for developing appropriate measures to control ARG transmission.