2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) was difficult to degrade in sediments. In this study, the environmental behavior of BDE-47 with/without the effect of benthos (Tubificidae Limnodrilus) and electron acceptors in sediments was investigated using C-14 tracer. Generally, extractable residues of BDE-47 were dominant in sediment and posed high environment risk. The amount of non-extractable residues (NERs) accounted for 39.0% of initial radioactivity in oxic sediments was significantly higher than those in anoxic sediments (17.6%). Most of NERs were localized in the humin fraction and presented as sequestrated forms. Under oxic conditions, the present of Limnodrilus significantly increased the proportion of NERs in sediment. Limnodrilus accumulated 34.2% of initial radioactivity. Under anoxic conditions, the addition of iron (Ⅲ) [Fe(III)], sulfate and nitrate reduced the environmental risk of BDE-47 with the increase of NERs formation, while manganese (IV) [Mn(IV)] addition had no effect on the formation of NERs. The present of Limnodrilus and electron acceptors promoted the production of metabolites. Meanwhile, BDE-47 changed the microbial community structure of sediments. These findings indicated that the environmental behavior and risk of BDE-47 was affected by benthos and electron acceptors, and the high proportion of sequestrated NERs posed high bioactivity and toxic threat to ecological environment.

Mapping soil contamination enables the delineation of areas where protection measures are needed. Traditional soil sampling on a grid pattern followed by chemical analysis and geostatistical interpolation methods (GIMs), such as Kriging interpolation, can be costly, slow and not well-suited to highly heterogeneous soil environments. Here we propose a novel method to map soil contamination by combining high-resolution aerial imaging (HRAI) with machine learning algorithms. To support model establishment and validation, 1068 soil samples were collected from an arsenic (As) contaminated area in Zhongxiang, Hubei province, China. The average arsenic concentration was 39.88 mg/kg (SD = 213.70 mg/kg), with individual sample points determined as low risk (66.9%), medium risk (29.4%), or high risk (3.7%), respectively. Then, identified features were extracted from a HRAI image of the study area. Four machine learning algorithms were developed to predict As risk levels, including (i) support vector machine (SVM), (ii) multi-layer perceptron (MLP), (iii) random forest (RF), and (iii) extreme random forest (ERF). Among these, we found that the ERF algorithm performed best overall and that its prediction performance was generally better than that of traditional Kriging interpolation. The accuracy of ERF in test area 1 reached 0.87, performing better than RF (0.81), MLP (0.78) and SVM (0.77). The F1-score of ERF for discerning high-risk points in test area 1 was as high as 0.8. The complexity of the distribution of points with different risk levels was a decisive factor in model prediction ability. Identified features in the study area associated with fertilizer factories had the most important contribution to the ERF model. This study demonstrates that HRAI combined with machine learning has good potential to predict As soil risk levels.

Nitrous acid (HONO) production from the heterogeneous photochemical reaction of NO₂ on several Chinese soils was performed in a cylindrical reactor at atmospheric pressure. The NO₂ uptake coefficient (γ) and HONO yield (YHONO) on different soils were (0.42–5.16) × 10⁻⁵ and 6.3%–69.6%, respectively. Although the photo-enhanced uptake of NO₂ on different soils was observed, light could either enhance or inhibit the conversion efficiency of NO₂ to HONO, depending on the properties of the soils. Soils with lower pH generally had larger γ and YHONO. Soil organics played a key role in HONO formation through the photochemical uptake of NO₂ on soil surfaces. The γ showed a positive correlation with irradiation and temperature, while it exhibited a negative relationship with relative humidity (RH). YHONO inversely depended on the soil mass (0.32–3.25 mg cm⁻²), and it positively relied on the irradiance and RH (7%–22%). There was a maximum value for YHONO at 298 K. Based on the experimental results, HONO source strengths from heterogeneous photochemical reaction of NO₂ on the soil surfaces were estimated to be 0.2–2.7 ppb h⁻¹ for a mixing layer height of 100 m, which could account for the missing daytime HONO sources in most areas.

Polyethylene terephthalate (PET) is a possible key component of nanoplastics in water environments, which can migrate pollutants through co-transport. In this regard, the co-transport of endocrine disruptors (such as bisphenol A, BPA) by nanoplastics is of emergent concern because of its cytotoxicity/bioaccumulation effects in aquatic organisms. In this work, a computational study is performed to reveal the BPA adsorption mechanism onto PET nanoplastics (nanoPET). It is found that the outer surface of nanoPET has a nucleophilic nature, allowing to increase the mass transfer and intraparticle diffusion into the nanoplastic to form stable complexes by inner and outer surface adsorption. The maximum adsorption energy is similar (even higher) in magnitude with respect to nanostructured adsorbents such as graphene, carbon nanotubes, activated carbon, and inorganic surfaces, indicating the worrying adsorption properties of nanoPET. The adsorption mechanism is driven by the interplay of dispersion (38–49%) and electrostatics effects (43–50%); specifically, dispersion effects dominate the inner surface adsorption, while electrostatics energies dominate the outer surface adsorption. It is also determined that π–π stacking is not a reliable interaction mechanism for aromatics on nanoPET. The formed complexes are also highly soluble, and water molecules behave as non-competitive factors, establishing the high risk of nanoPET to adsorb and migrate pollutants in water ecosystems. Furthermore, the adsorption performance is decreased (but not inhibited) at high ionic strength in salt-containing waters. Finally, these results give relevant information for environmental risk assessment, such as quantitative data and interaction mechanisms for non-biodegradable nanoplastics that establish strong interactions with pollutants in water.

Insect gut microbiotas have a variety of physiological functions for host growth, development, and immunity. Bacillus thuringiensis (Bt) is known to kill insect pests by releasing insecticidal protoxins, which are activated in the insect midgut. However, the interplay among Bt infection, host immunity, and gut microbiota are still unclear. Here we show that Bt Cry1Ac protoxin interacts with the gut microbiota to accelerate the mortality of P. xylostella larvae. Cry1Ac protoxin was found to cause a dynamic change in the midgut and hemocoel microbiota of P. xylostella, with a significant increase in bacterial load and a significant reduction in bacterial diversity. In turn, loss of gut microbiota significantly decreased the Bt susceptibility of P. xylostella larvae. The introduction of three gut bacterial isolates Enterococcus mundtii (PxG1), Carnobacterium maltaromaticum (PxCG2), and Acinetobacter guillouiae (PxCG3) restored sensitivity to Bt Cry1Ac protoxin. We also found that Cry1Ac protoxin and native gut microbiota can trigger host midgut immune response, which involves the up-regulation of expression of Toll and IMD pathway genes and most antimicrobial peptide genes, respectively. Our findings further shed light on the interplay between insect gut microbiota and host immunity under the Bt toxin killing pressure, and this may provide insights for improving the management of Bt resistance and lead to new strategies for biological control of insect pests.

Fine particulate matter (PM₂.₅) has attracted extensive attention because of its baneful influence on human health and the environment. However, the sparse distribution of PM₂.₅ measuring stations limits its application to public utility and scientific research, which can be remedied by satellite observations. Therefore, we developed a Geo-intelligent long short-term network (Geoi-LSTM) to estimate hourly ground-level PM₂.₅ concentrations in 2017 in Wuhan Urban Agglomeration (WUA). We conducted contrast experiments to verify the effectiveness of our model and explored the optimal modeling strategy. It turned out that Geoi-LSTM with TOA reflectance, meteorological conditions, and NDVI as inputs performs best. The station-based cross-validation R², root mean squared error and mean absolute error are 0.82, 15.44 μg/m³, 10.63 μg/m³, respectively. Based on model results, we revealed spatiotemporal characteristics of PM₂.₅ in WUA. Generally speaking, during the day, PM₂.₅ concentration remained stable at a relatively high level in the morning and decreased continuously in the afternoon. While during the year, PM₂.₅ concentrations were highest in winter, lowest in summer, and in-between in spring and autumn. Combined with meteorological conditions, we further analyzed the whole process of a PM₂.₅ pollution event. Finally, we discussed the loss in removing clouds-covered pixels and compared our model with several popular models. Overall, our results can reflect hourly PM₂.₅ concentrations seamlessly and accurately with a spatial resolution of 5 km, which benefits PM₂.₅ exposure evaluations and policy regulations.

We investigated the roles of rootstocks in Cu accumulation and tolerance in Malus plants by grafting ‘Hanfu’ (HF) scions onto M. baccata (Mb) and M. prunifolia (Mp) rootstocks, which have different Cu tolerances. The grafts were exposed to basal or excess Cu for 20 d. Excess Cu-treated HF/Mb had less biomass, and pronounced root architecture deformation and leaf ultrastructure damage than excess Cu-challenged HF/Mp. Root Cu concentrations and bio-concentration factor (BCF) were higher in HF/Mp than HF/Mb, whereas HF/Mb had higher stem and leaf Cu concentrations than HF/Mp. Excess Cu lowered root and aerial tissue BCF and translocation factor (Tf) in all plants; however, Tf was markedly higher in HF/Mb than in HF/Mp. The subcellular distribution of Cu in the roots and leaves indicated that excess Cu treatments increased Cu fixation in the root cell walls, which decreased Cu mobility. Compared to HF/Mb, HF/Mp sequestered more Cu in its root cell walls and less Cu in leaf plastids, nuclei, and mitochondria. Moreover, HF/Mp roots and leaves had higher concentrations of water-insoluble Cu compounds than HF/Mb, which reduced Cu mobility and toxicity. Fourier transform infrared spectroscopy analysis showed that the carboxyl, hydroxyl and acylamino groups of the cellulose, hemicellulose, pectin and proteins were the main Cu binding sites in the root cell walls. Excess Cu-induced superoxide anion and malondialdehyde were 28.6% and 5.1% lower, but soluble phenolics, ascorbate and glutathione were 10.5%, 41.9% and 17.7% higher in HF/Mp than HF/Mb leaves. Compared with HF/Mb, certain genes involved in Cu transport were downregulated, while other genes involved in detoxification were upregulated in HF/Mp roots and leaves. Our results show that Mp inhibited Cu translocation and mitigated Cu toxicity in Malus scions by regulating Cu mobility, antioxidant defense mechanisms, and transcription of key genes involved in Cu translocation and detoxification.

Hydraulic fracturing flowback and produced water (HF-FPW), which contains polyaromatic hydrocarbons (PAHs) and numerous other potential contaminants, is a complex wastewater produced during the recovery of tight hydrocarbon resources. Previous studies on HF-FPW have demonstrated various toxicological responses of aquatic organisms as consequences of combined exposure to high salinity, dissolved organic compounds and particle/suspended solids-bound pollutants. Noteworthy is the lack of studies illustrating the potentially toxic effects of the FPW suspended solids (FPW-SS). In this study, we investigated the acute and sublethal toxicity of suspended solids filtered from six authentic FPW sample collected from two fracturing wells, using a sediment contact assay based on early-life stages of zebrafish (Danio rerio). PAHs profiles and acute toxicity tests provided initial information on the toxic potency of the six samples. Upon exposure to sediment mixture at two selected doses (1.6 and 3.1 mg/mL), results showed adverse effects in larval zebrafish, as revealed by increased Ethoxyresorufin-O-deethylase (EROD) activity. Transcriptional alterations were also observed in xenobiotic biotransformation (ahr, pxr, cyp1a, cyp1b1, cyp1c1, cyp1c2, cyp3a65, udpgt1a1, udpgt5g1), antioxidant response (sod1, sod2, gpx1a, gpx1b) and hormone receptor signaling (esr1, esr2a, cyp19a1a, vtg1) genes. The results demonstrated that even separated from the complex aqueous FPW mixture, FPW-SS can induce toxicological responses in aquatic organisms' early life stages. Since FPW-SS could sediment to the bottom of natural wetland acting as a continuous source of contaminants, the current findings imply the likelihood of long-term environmental risks of polluted sediments on aquatic ecosystems due to FPW spills.

Sediment serves as a sink for metals, thus it is critical to assess its contamination and associated risk. A typical riparian wetland close to a Zn-smelting operation in karst areas in southwest China was investigated. Sediment and reed plant (Phragmites australis) samples from wet and dry seasons were analyzed for total As, Cu, and Zn concentrations. Metal pollution in the sediment was assessed based on geoaccumulation index (Igₑₒ). Further, metals in the sediment were fractionated into exchangeable, water and acid-soluble, reducible, oxidizable, and residual fractions based on the BCR sequential extraction. The results showed that the As, Cu, and Zn concentrations in the sediment were significantly higher than the background values (740–4081, 96–228, and 869–3331 vs. 10, 22, and 70 mg kg⁻¹). With the Igₑₒ being 10–17, the data indicate that the sediment was highly-polluted. While total As, Cu and Zn in the sediment increased from dry to wet season, their available concentrations decreased except Cu. With 62–94% of As, Cu, and Zn being in the residual fraction, metal availability in the sediment was low based on fractionation data. The data are consistent with low metal uptake by reed as their concentration ratios in plant roots to the sediment were 0.01–0.32. The results suggest that the riparian sediment was highly-polluted with As, Cu and Zn, but showing low metal availability and limited plant uptake.

Ingestion of food or cereal products contaminated by deoxynivalenol (DON) and related derivatives poses a threat to the health of humans and animals. However, the toxicity and underlying mechanisms of 3-acetyldeoxynivalenol (3-Ac-DON), an acetylated form of deoxynivalenol, have not been fully elucidated. In the present study, we showed that 3-Ac-DON caused significant oxidative damage, as shown by elevated aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactic dehydrogenase (LDH) in serum, increased lipid peroxidation products, such as hydrogen peroxide (H₂O₂) and malondialdehyde (MDA), decreased activities of antioxidant enzymes catalase (CAT) and superoxide dismutase (SOD). In addition, 3-Ac-DON exposure led to elevated infiltrations of immune cell, increased apoptosis and autophagy in the liver. Interestingly, 3-Ac-DON-resulted apoptosis and liver injury were partially reduced by autophagy inhibitors. Further study showed that 3-Ac-DON-treated mice had altered ultrastructural changes of endoplasmic reticulum (ER), as well as enhanced protein levels of p-IRE1α, p-PERK, and downstream targets, indicating activation of unfolded protein response (UPR) in the liver. Importantly, 3-Ac-DON induced ER stress, oxidative damage, cell death, infiltration of immune cells, and increased mRNA levels of inflammatory cytokines were significantly abolished by 4-phenylbutyric acid (4-PBA), an ER stress inhibitor, indicating a critical role of UPR signaling for the cellular damage of the liver in response to 3-Ac-DON exposure. In conclusion, using mice as an animal model, we showed that 3-Ac-DON exposure impaired the function of liver, as shown by oxidative damage, cell death, and infiltration of immune cell, in which ER stress played an important role. Restoration of the ER function might be a preventive strategy to reduce the deleterious effect of 3-Ac-DON on the liver of animals.