No anthropogenic pollutant is more widespread in the aquatic and terrestrial environment than microplastic; however, there are large knowledge gaps regarding its origin, fate, or temporal variations in the oceans. In this study, we analyzed sediment trap material from the deep subtropical Northeast Atlantic (2000 m) in a long-term record (2003–2015) to assess the role of the deep ocean as a potential sink of microplastics. Microplastic particles were identified in all 110 analyzed samples with flux rates of 1.13–3146.81 items d⁻¹ m⁻². Calculated microplastic mass fluxes ranged between 0.10 and 1977.96 μg d⁻¹ m⁻², representing up to 8% of the particle flux. Between years, the composition of the different polymers changed significantly, dominated by polyethylene, whose amount was correlated with the lithogenic input. The correlation between polyethylene and the lithogenic fraction was attributed to an air transport pathway from northeast Africa and surrounding regions. The second most abundant polymer detected in our study was polyvinyl chloride, which is not correlated with lithogenic or biogenic particle flux fractions. Instead, we observed seasonality for polyvinyl chloride with recurring high fluxes in winter before the plankton bloom and significantly lower amounts in summer. Other polymers identified were polypropylene, polyethylene terephthalate, and lower numbers of polystyrene and polymethyl methacrylate. The average microplastic particle size for all samples and polymers was 88.44 ± 113.46 μm, with polyethylene and polyvinyl chloride having the highest proportion of small particles (<100 μm). Our findings provide first insights into temporal variations of sinking microplastics, which are crucial for understanding the fate of plastic in the oceans.

Marine microplastics (MPs) pose a risk to human health through accumulation in maricultural organisms, particularly bivalves. Various studies have reported the presence of MP particles in Pacific oysters (Crasostrea gigas). In this study, we investigated the size-specific ingestion and egestion of polystyrene (PS) MPs by Pacific oysters. The cultivation density of C. gigas was maintained at 1 L of filtered seawater per oyster (n = 5) during the MP ingestion and egestion experiments. On exposure to 300 n/L of PS MP fragments for 7 d, 60.4% of the PS was ingested within 6 h (7.25 × 10² ± 1.36 × 10² n/indv.), and the ingestion was saturated at 12 h (1.2 × 10³ ± 2.2 × 10² n/indv.) in C. gigas. The maximum MP ingestion capacity (Igₘₐₓ) of a single Pacific oyster was 73.0 ± 16.3 n/g wet weight. Further, 62.9% of the PS MP particles were egested for 7 d from the saturated single C. gigas. Ingestion and egestion varied according to the PS MP size. In the case of <50 μm PS MP, ingestion rate was low but MP amount and net-ingestion efficiency was significantly higher than other PS MP sizes. In addition, egestion, egestion rate, and net-egestion efficiency for <50 μm PS MPs were significantly higher than other PS MP sizes. Therefore, smaller MPs (<50 μm) normally exhibit the highest ingestion and egestion rates; therefore, the 50–300 μm size fraction exhibited the highest residual possibility (particles >1000 μm were excluded). Additionally, considering the net-egestion efficiency, the most economical and efficient depuration period was 24 h. This study clarifies the size-specific MP accumulation in oysters, and the egestion results suggest that the potential risk of MPs to human health through the intake of maricultural products could be reduced by depuration.

Paraquat, a widely used herbicide, causes environmental pollution, and liver injury in humans and animals. As a natural compound in fruits, ellagic acid (EA) shows anti-inflammatory and antioxidant effects. This study examines the beneficial effects of dietary EA against the paraquat-induced hepatic injury and further explores the underlying molecular mechanisms using a piglet model. Post-weaning piglets are fed basal diet supplemented with 50 mg/kg, 100 mg/kg, or 200 mg/kg EA for 3 weeks. At week 2, hepatic injury is induced by 4 mg/kg paraquat followed by 7 days recovery. EA supplementation significantly mitigates paraquat-induced hepatic fibrosis, steatosis, and high apoptotic rate. In agreement, EA supplementation reduces serum pro-inflammatory levels, ameliorates inflammatory cells infiltration into hepatic tissue, which are associated with suppressed NF-κB signaling during paraquat exposure. In addition, EA supplementation significantly improves activities of antioxidative enzymes which were correlated with activated Nrf2/Keap 1 signaling during paraquat exposure. Furthermore, EA supplementation restores cecal microbial community during paraquat exposure. The protective effect of EA is strongly linked with increased relative abundance of Lactobacillus reuteri and Lactobacillus amylovorus. Taken together, EA supplementation effectively reduced the occurrence of hepatic oxidative damage and inflammation induced by paraquat through modulating cecal microbial communities, which provides a novel nutritional therapeutic strategy for hepatic injury.

Ambient particles with aerodynamic diameter <0.1 μm (PM₀.₁) have been suggested to have significant health impact. However, studies on the association between long-term PM₀.₁ exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006–2009 average PM₀.₁ concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM₀.₁ concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM₀.₁ concentration was associated with a 5.75 (95% Confidence interval, 3.24–8.25) mg/dl and a 6.05 (2.85–9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10–1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM₀.₁ exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

Batch sorption of metformin hydrochloride (MET) onto a specially designed biochar mix consisting of both macro (MAC) and micro (MIC) algae, rice husk and pine sawdust was conducted. Pyrolysis of both MAC and MIC algae mixture was done followed by chemical activation with hydrogen-peroxide. Additionally, sorption of MET under the influence of pH was separately investigated. Batch studies of isotherms were well described by Freundlich model with high non-linearity and Freundlich exponent values ranged anywhere from 0.12 to 1.54. Heterogeneity of MET adsorption to the bonding sites was attributed to the surface functional groups of the modified biochar. Amongst the four biochars, the activated macroalgae biochar (MACAC) and microalgae biochar (MICAC) depicted favourable adsorption of MET with maximum adsorption at pH 7. Up to 76% of MET removal from the environment was obatained using the MACAC biochar. Scanning electron micrographs coupled with energy dispersive X-ray, as well as elemental analyses confirmed formation of oxygen containing surface functional groups due to activation strengthening chemisorption as the main sorption mechanism. Further, Fourier transform infra-red spectroscopy and other surface functional group analyses along with Zeta potential measurements reinforced our proposed sorption mechanism. Lowest zeta potential observed at pH 7 enhanced the electrostatic force of attraction for both the biochars. Negative zeta potential value of the biochars under different pH indicated potential of the biochars to adsorb other positively charged contaminants. From a techno-economic perspective, capital expenditure cost is not readily available, however, it is envisaged that production of pyrolyzed biochar from algal biomass could make the process economically attractive especially when the biochar could be utilised for high-end applications.

Per- and polyfluoroalkyl substances (PFAS) have become a target of rigorous scientific research due to their ubiquitous nature and adverse health effects. However, there are still gaps in knowledge about their environmental fate and health implications. More attention is needed for remote locations with source exposures. This study focuses on assessing PFAS exposure in Gustavus, a small Alaska community, located near a significant PFAS source from airport operations and fire training sites. Residential water (n = 25) and serum (n = 40) samples were collected from Gustavus residents and analyzed for 39 PFAS compounds. In addition, two water samples were collected from the previously identified PFAS source near the community. Fourteen distinct PFAS were detected in Gustavus water samples, including 6 perfluorinated carboxylic acids (PFCAs), 7 perfluorosulfonic acids (PFSAs), and 1 fluorotelomer sulfonate (FTS). ΣPFAS concentrations in residential drinking water ranged from not detected to 120 ng/L. High ΣPFAS levels were detected in two source samples collected from the Gustavus Department of Transportation (14,600 ng/L) and the Gustavus Airport (228 ng/L), confirming these two locations as a nearby major source of PFAS contamination. Seventeen PFAS were detected in serum and ΣPFAS concentrations ranged from 0.0170 to 13.1 ng/mL (median 0.0823 ng/mL). Perfluorooctanesulfonic acid (PFOS) and perfluorohexanesulfonic acid (PFHxS) were the most abundant PFAS in both water and serum samples and comprised up to 70% of ΣPFAS concentrations in these samples. Spearman's correlation analysis revealed PFAS concentrations in water and sera were significantly and positively correlated (r = 0.495; p = 0.0192). Our results confirm a presence of a significant PFAS source near Gustavus, Alaska and suggest that contaminated drinking water from private wells contributes to the overall PFAS body burden in Gustavus residents.

Although road traffic noise is the most important source of environmental noise emission in large cities, little is known about health burden. The present study was conducted to estimate the burden of diseases attributed to traffic noise in the metropolis of Tehran in 2017. Using noise maps provided by the municipality of Tehran, we calculated population exposure distribution in term of Ldₙ and Lₙᵢgₕₜ and the number of DALYs lost due to ischemic heart disease, hypertension, high sleep disturbance, annoyance and stroke endpoints based on the World Health Organization Environmental Noise Guidelines for the European Region. We applied published dose-response functions to estimate the traffic noise burden for high sleep disturbance and annoyance. We estimated 61,284 DALYs or 697 DALYs per 100,000 population attributed to traffic noise in Tehran for the reference year 2017. Highly sleep disturbance with a share of 58.74% of the DALYs was recognized as the most important contributor of disease burden, and noise annoyance with a share of 23.12% was ranked next. Ischemic heart disease (11.71%), stroke (5.12%), and hypertension (1.31%) were ranked third to fourth, respectively, in terms of the burden of disease caused by environmental noise. A considerable fraction of the population of Tehran lives in areas with an environmental noise higher than the standard level. The findings showed that traffic noise pollution is an important environmental risk factor in Tehran imposes the greatest burden on the community, mainly through highly sleep disturbance and noise annoyance endpoints.

Although the hazards of microplastics (MPs) have been quite well explored, the aberrant metabolism and the involvement of the autophagy pathway as an adverse response to environmental MPs in benthic organisms are still unclear. The present work aims to assess the impact of different environmental MPs collected from the south coast of the Mediterranean Sea, composed by polyethylene (PE), polyethylene vinyl acetate (PEVA), low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP) and polyamide (PA) on the metabolome and proteome of the marine polychaete Hediste diversicolor. As a result, all the microplastic types were detected with Raman microspectroscopy in polychaetes tissues, causing cytoskeleton damage and induced autophagy pathway manifested by immunohistochemical labeling of specific targeted proteins, through Tubulin (Tub), Microtubule-associated protein light chain 3 (LC3), and p62 (also named Sequestosome 1). Metabolomics was conducted to further investigate the metabolic alterations induced by the environmental MPs-mixture in polychaetes. A total of 28 metabolites were differentially expressed between control and MPs-treated polychaetes, which showed elevated levels of amino acids, glucose, ATP/ADP, osmolytes, glutathione, choline and phosphocholine, and reduced concentration of aspartate. These novel findings extend our understanding given the toxicity of environmental microplastics and unravel their underlying mechanisms.

Long-term change and shorter-term variability in the atmospheric deposition of pollutants and marine salts can have major effects on the biogeochemistry and ecology of soils and surface water ecosystems. In the 1980s, at the time of peak acid deposition in the UK, deposition loads were highly dependent on prevailing weather types, and it was postulated that future pollution recovery trajectories would be partly dependent on any climate change-driven shifts in weather systems. Following three decades of substantial acidic emission reductions, we used monitoring data collected between 1992 and 2015 from four UK Environmental Change Network (ECN) sites in contrasting parts of Great Britain to examine the trends in precipitation chemistry in relation to prevailing weather conditions. Weather systems were classified on the basis of Lamb weather type (LWT) groupings, while emissions inventories and clustering of air mass trajectories were used to interpret the observed patterns. Concentrations of ions showed clear differences between cyclonic-westerly-dominated periods and others, reflecting higher marine and lower anthropogenic contributions in Atlantic air masses. Westerlies were associated with higher rainfall, higher sea salt concentrations, and lower pollutant concentrations at all sites, while air mass paths exerted additional controls. Westerlies therefore have continued to favour higher sea salt fluxes, whereas emission reductions are increasingly leading to positive correlations between westerlies and pollutant fluxes. Our results also suggest a shift from the influence of anthropogenic emissions to natural emissions (e.g., sea salt) and climate forcing as they are transported under relatively cleaner conditions to the UK. Westerlies have been relatively frequent over the ECN monitoring period, but longer-term cyclicity in these weather types suggests that current contributions to precipitation may not be sustained over coming years.

Water quality forecasting can provide useful information for public health protection and support water resources management. In order to forecast water quality more accurately, this paper proposes a novel hybrid model by combining data decomposition, fuzzy C-means clustering and bidirectional gated recurrent unit. Firstly, the original water quality data is decomposed into several subseries by empirical wavelet transform, and then, the decomposed subseries are recombined by fuzzy C-means clustering. Next, for each clustered series, bidirectional gated recurrent unit is applied to develop prediction model. Finally, the forecast result is obtained by the summation of the predictions for the subseries. The proposed forecast model is evaluated by the water quality data of Poyang Lake, China. Results show that the proposed forecast model provides highly accurate forecast result for all of the six water quality data: the average of MAPE of the forecast results for the six water quality datasets is 4.59% for 7 day ahead prediction. Furthermore, our model shows better forecast performance than the other models. Particularly, compared with the single BiGRU model, MAPE decreased by 32.86% in average. Results demonstrate that the proposed forecast model can be used effectively for water quality forecasting.