Chemical mixtures represent environmentally-realistic exposures of contaminants to aquatic biota. However, there remains a limited understanding of how toxicant mixtures may impact biological function, relative to their individual components. In the current study, oxidative stress responses of the freshwater galaxiid fish inanga (Galaxias maculatus) were examined following exposure to the pro-oxidant trace metal cadmium (2 or 9 μg L⁻¹), and the anti-oxidant pharmaceutical drug diclofenac (770 μg L⁻¹), individually or in simple binary mixtures. Cadmium exposure in the absence of diclofenac significantly decreased renal catalase activity, increased hepatic catalase activity, decreased renal superoxide dismutase (SOD) and decreased glutathione-S-transferase activity, effects that are suggestive of anti-oxidant defense inhibition and/or generation of increased reactive oxygen species. Diclofenac exposure in the absence of cadmium resulted in a decreased renal lipid peroxidation, consistent with its known anti-oxidant properties. The presence of waterborne diclofenac altered the effects of cadmium on catalase activity in the liver, SOD activity in the gill, and lipid peroxidation in the liver. Co-exposure with cadmium modulated diclofenac effects on lipid peroxidation in the kidney. These data indicate the capacity of each of these toxicants to offset biological effects of the other when both co-occur in urban waters at specific concentrations. This study also demonstrates the complexity of outcomes in contaminant mixtures, even when these stressors are presented as simple binary combinations.

From previous catastrophic fission nuclear accidents, such as the Chernobyl and Fukushima accidents, researchers learnt the lessons that external hazard beyond design basis or human errors could result in severe accidents and multi-failure of the confinements although they were considered as very-low-probability events and not requested to be paid much attention to according to the current nuclear safety regulations. Fusion energy is always regarded as a safe and clean energy. However, massive quantity of radioactivity still exists in the fusion reactor and is possible to be released into the environment. The environmental pollution and potential public consequences due to severe accidents of fusion reactor remain largely unexplored. In this contribution, we intended to investigate the hypothetical accident to envelop the worst but probable consequences of fusion reactor, and compare with historic Chernobyl and Fukushima accidents under assumed environmental conditions. It was demonstrated that, the radiation consequences of a hypothetical fusion accident would be much less severe than fission accidents, e.g. an INES 7 accident could not appear in a fusion reactor, as in the Chernobyl and Fukushima nuclear accidents. However, it would still be disastrous and the publics close to site might be exposed to “potentially lethal” radiation dose.

Silver nanoparticles (AgNPs) in aquatic ecosystems are toxic to aquatic organisms. In this study, we aimed to investigate the toxicities and molecular mechanisms of AgNPs with different surface coatings (sodium citrate and polyvinylpyrrolidone) and particle sizes (20 nm and 100 nm) in the gills, intestines, and muscles of zebrafish after 96 h of exposure. Our results indicated that the contribution of particle size to AgNP toxicity was greater than that of the surface coating. Citrate-coated AgNPs were more toxic than polyvinylpyrrolidone-coated AgNPs, and 20-nm AgNPs were more toxic than 100-nm AgNPs. The toxic effects of AgNPs to the tissues were in the order intestines > gills > muscles. Differential expression of genes with the different AgNPs confirmed that they had toxic effects in the zebrafish tissues at the molecular level. Our comprehensive comparison of the toxicities of different AgNPs to aquatic ecosystems will be helpful for further risk assessments of AgNPs.

In the era of big data, a variety of factors (particularly meteorological factors) have been applied to PM2.5 concentration prediction, revealing a clear discrepancy in timescale. To capture the complicated multi-scale relationship with PM2.5-related factors, a novel multi-factor & multi-scale method is proposed for PM2.5 forecasting. Three major steps are taken: (1) multi-factor analysis, to select predictive factors via statistical tests; (2) multi-scale analysis, to extract scale-aligned components via multivariate empirical mode decomposition; and (3) PM2.5 prediction, including individual prediction at each timescale and ensemble prediction across different timescales. The empirical study focuses on the PM2.5 of Cangzhou, which is one of the most air-polluted cities in China, and indicates that the proposed multi-factor & multi-scale learning paradigms statistically outperform their corresponding original techniques (without multi-factor and multi-scale analysis), semi-improved variants (with either multi-factor or multi-scale analysis), and similar counterparts (with other multi-scale analyses) in terms of prediction accuracy.

The comprehensive sources of particulate matter (PM) require air purification materials to possess both high filtration efficiencies and low air resistances in an effort to provide healthcare. However, the assembly of multiple-layered filters with different functions leads to high pressure drop and high operating cost. Therefore, a multifunctional air filter that can provide excellent air filtration capacity and healthcare is highly desired. Here, a novel bifunctional polyacrylonitrile/attapulgite hierarchical-structured filter with low air resistance and high adsorption capacity was designed and fabricated by embedding attapulgite nanorods during a facile electrospinning process. The hierarchical polyacrylonitrile/attapulgite membranes showed only a ∼64 Pa resistance for 0.1 μm PM. Another benefit of using the attapulgite nanorods is an adsorption effect for hazardous heavy metal ions that accompany airborne ultrafine PMs. Thereby this hierarchical membrane simultaneously exhibits an enhanced filtration performance and hazardous protection ability. Furthermore, due to the electret effect of the attapulgite nanorods, the surface potential of the membrane remains at above 2.2 kV after 600 min of continuous use, which could improve the air filtration efficiency and ensure the long-term service life of the filters. This work may provide a new approach for the design and development of multifunctional air filters for simultaneously capturing ultrafine PMs and any other accompanying hazardous chemicals.

Oxygenated volatile organic compounds (OVOCs) are critical atmospheric ozone and secondary organic aerosol (SOA) precursors and radical sources, while understanding of OVOC sources in the atmosphere, especially with large anthropogenic emissions, still has large uncertainties. A high-sensitivity proton transfer reaction mass spectrometer (PTR-MS) was deployed in vastly different atmospheres in southern China, including an urban site (SZ-U), a regional site (NA-R), and a background site (NL-B). Four critical OVOCs, i.e., methanol, acetone, methyl ethyl ketone (MEK) and acetaldehyde, five groups of aromatic hydrocarbons, isoprene and acetonitrile were measured with a high time resolution. The featured relative abundance and diurnal variations of the OVOCs indicated that methanol, acetone and MEK had prominent contributions from urban industrial activities, while acetaldehyde was closely related to the photochemical formation at all three sites. The photochemical age-based parameterization method was improved locally and then applied to quantify different sources of daytime OVOCs: anthropogenic secondary and biogenic sources (together 60–73%) were always the dominant source for acetaldehyde in various atmospheres; in addition to a significant background for methanol, acetone and MEK, anthropogenic primary emissions (mostly industrial) were their dominant source at SZ-U (38–73%), while biogenic sources played the key role for them at NL-B (30–43%); biomass burning contributed a small fraction of 5–17% for the four OVOCs at the three sites.

The cobalt ferrite-reduced oxidized graphene (CoFe2O4/rGO) catalyst was synthesized by hydrothermal method and characterized by Powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Scanning electron microscope (SEM), Brunauere Emmette Teller (BET) and Hysteresis loop. For developing a new method of removing elemental mercury (Hg0) from flue gas, the effects of catalyst dosage, PMS concentration, solution pH and reaction temperature on the removal efficiency were investigated experimentally by using peroxymonosulfate (PMS) catalyzed by CoFe2O4/rGO at a self-made bubbling reactor. The average removal efficiency of Hg0 in a 30-min period reached 95.56%, when CoFe2O4/rGO dosage was 0.288 g/L, PMS concentration was 3.5 mmol/L, solution pH was 5.5 and reaction temperature was 55 °C. Meanwhile, based on the free radical quenching experiments, in which, ethyl alcohol and tert butyl alcohol were used as quenchers to prove indirectly the presence of •OH and SO4•−, the characterizations of catalysts and reaction products, and the existing results from other scholars. The reaction mechanism was proposed.

Rare earth elements (REEs) have recently received particular attention due to their accumulation in the environment. Such heightened recognition prompted our evaluation of the possible occurrence of La-induced plant hormesis in the peer-reviewed literature. This study revealed 703 La-induced hormetic concentration/dose responses in plants, which were quantitatively and qualitatively assessed. The maximum (MAX) biological response to low La concentrations/doses is commonly below 150% of control response, with a geometric mean of 142% at 56 μM (geometric mean). The geometric mean concentration of the no-observed-adverse-effect-level (NOAEL) was 249 μM. The MAX:NOAEL distance was commonly below 5-fold, with a geometric mean of 4.5-fold. Hormetic concentration/dose responses varied as per the growth substrate pH, number of concentrations/doses below the NOAEL, and time window. These results provide a unique insight into the effects of low doses of La on plant growth, as well as offer means for improving experimental designs to assess low dose effects.

Burial in sediments is a crucial way to reduce mobilization and risks of hydrophobic organic contaminants (HOCs), but ability of sediments to bury HOCs may be altered if the environment is changed. Whether the ability of sediments to bury HOCs has been affected by climate change remains largely unclear. We excluded the impacts of anthropogenic emissions and eutrophication from that of climate change, and for the first time found that not only the rising surface air temperature but also the declining wind speed and the reducing days with precipitation had weakened the ability of Chinese lakes to bury 16 polycyclic aromatic hydrocarbon (PAHs) by 69.2% ± 9.4%–85.7% ± 3.6% from 1951 to 2017. The relative contributions of the climatic variables to the reduced burial ability depended on the properties of the PAHs, and lakes. Burial ability of the PAHs responded differently to climate change, and was correlated to their volatilization and aqueous solubility, and lake area, catchment area/lake area ratio, and water depth. Our study suggests that not only the rising surface air temperature but also the declining wind speed and the reducing days with precipitation can undermine global efforts to reduce environmental and human exposure to PAHs.

Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types is time-consuming, laborious, expensive and practically impossible. So, indirect methods for estimating the transport parameters by pedo-transfer functions are now advancing. This study developed and evaluated an Artificial Neural Network (ANN) model for estimating the transport velocity (V), dispersion coefficient (D) and retardation factor (R) of NaAsO₂, Pb(NO₃)₂, Cd(NO₃)₂, C₉H₉N₃O₂ and CaCl₂ from the basic soil properties. Breakthrough data of the solutes were measured in 14 agricultural soils of Bangladesh by time-domain reflectometry (TDR) in repacked soil columns under unsaturated steady-state water-flow conditions. The transport parameters of the chemicals were determined by analyzing the solute breakthrough data. Bulk density (γ), organic carbon (OC), clay (C) content, pH, median grain diameter (D₅₀) and uniformity coefficient (Cᵤ) of the soils were determined. An ANN model for V, D and R was developed by using data of eight soils, validated/tested with the data of five soils and verified with the data of one soil. Clay content and bulk density of the soils were the most sensitive input variables to the ANN model followed by other soil properties (OC, C, pH, D₅₀ and Cᵤ). The model reliably predicted V, D and R with relative root-mean-square error (RRMSE) of 0.028–0.363, mean error (ME) of – 0.00004 to 0.0005, bias error (BOE%) of 0–0.003 and modeling efficiency (EF) of >0.99. Thus, the ANN model can significantly enhance prediction of pollution transport through soils in terms of cost and effort.