Nonylphenol (NP), an environmental estrogen, is actually a complicated mixture of isomers, although it is commonly considered to be a single compound. There are many routes for crops to come into contact with NP; however, little is known about the plant uptake and metabolism of NP, especially at the isomer level. This study comparatively evaluated the uptake and in-planta metabolism of 4-n-NP and its 10 isomers using both carrot cells and intact plants. The rapid metabolism of 4-n-NP was observed in the callus tissues and intact plants with half-lives of 2 h and 4.72 d, respectively. Six conjugates of 4-n-NP were identified in the cell extracts using high resolution mass spectrometry. The primary transformation pathway was found to be the direct conjugation (Phase II metabolism) with the parent compound at the hydroxyl. Furthermore, 4-NP isomers with short side chains and/or bulky α-substituents were more resistant to plant metabolism and showed a greater tendency for accumulation. The influence of the side chains to the isomer selectivity was verified by the molecular docking between glycosyltransferase and 4-NP isomers. This study highlighted the necessity to consider isomer-specificity in the plant accumulation of NP and the environmental and human health implications of NP conjugates.

Azoxystrobin (AZ) and pyraclostrobin (PY) are strobilurin fungicides that inhibit fungal mitochondrial respiration. In this study, a representative model, zebrafish (Danio rerio), was used as a test species for acute and developmental toxicity. Survival and malformation rates were observed only PY-treated embryos, with an LC₅₀ value of 77.75 ppb accompanied by a dramatic decrease in hatching rate, while AZ did not show great mortality. Morphological changes were observed in PY-treated embryos with the occurrence of pericadial edema at 25 ppb. A delay in growth was observed after treatment with pyraclostrobin at 50 ppb. Use of genetically engineered Tg(cmlc:EGFP) allowed fluorescence observation during heart development. PY interfered with normal heart development via upregulation of the nppa gene responsible for the expression of natriuretic peptides. Heart function was dramatically reduced as indicated by reduced heart rates. Increased expression of the nppa gene was also seen in AZ-treated embryos. The expression level of cyp24a1 was also up-regulated, while ugt1a1 and sult1st6 were down-regulated after treatment of zebrafish embryos with AZ or PY. Overall, strobilurin fungicides might inhibit normal heart formation and function within the range of concentrations tested.

The high global consumption of ibuprofen and its limited elimination by wastewater treatment plants (WWTPs), has led to the contamination of aquatic systems by this common analgesic and its metabolites. The potentially negative environmental and public health effects of this emerging contaminant have raised concerns, driving the demand for treatment technologies. The implementation of bacteria which mineralize organic contaminants in biopurification systems used to decontaminate water or directly in processes in WWTPs, is a cheap and sustainable means for complete elimination before release into the environment. In this work, an ibuprofen-mineralizing bacterial strain isolated from sediments of the River Elbe was characterized and assayed to remediate different ibuprofen-polluted media. Strain RW412, which was identified as Sphingopyxis granuli, has a 4.48 Mb genome which includes plasmid sequences which harbor the ipf genes that encode the first steps of ibuprofen mineralization. Here, we confirm that these genes encode enzymes which initiate CoA ligation to ibuprofen, followed by aromatic ring activation by a dioxygenase and retroaldol cleavage to unequivocally produce 4-isobutylcatechol and propionyl-CoA which then undergo further degradation. In liquid mineral salts medium, the strain eliminated more than 2 mM ibuprofen within 74 h with a generation time of 16 h. Upon inoculation into biopurification systems, it eliminated repeated doses of ibuprofen within a few days. Furthermore, in these systems the presence of RW412 avoided the accumulation of ibuprofen metabolites. In ibuprofen-spiked effluent from a municipal WWTP, ibuprofen removal by this strain was 7 times faster than by the indigenous microbiota. These results suggest that this strain can persist and remain active under environmentally relevant conditions, and may be a useful innovation to eliminate this emerging contaminant from urban wastewater treatment systems.

Most legacy mines contributed to contamination of the environment before and after cessation of mining. Contamination from waste rock, slag and tailings can introduce large concentrations of metals and metalloids to the surface soil and downstream sediments. Since ants are able to accumulate metals in their bodies, we investigated the possibility of using the elemental compositions of ants as indicators of metals at legacy mines developed on ores rich in copper (Cu), zinc (Zn), arsenic (As), silver (Ag) and lead (Pb). Our results showed the concentrations of manganese (Mn) and Cu in ants were not significantly different between mine and reference samples and only Zn was significantly different between contaminated and reference areas. Crematogaster spp. and Notoncus spp. from reference areas accumulated larger concentrations of metals in their bodies compared to ants from the mine. Ants accumulated metals in different parts of their bodies. The abdomen was the main site for accumulation of Mn, iron (Fe) and Zn. Mandibles were only associated with accumulation of Zn. Copper and Pb showed no area of preferential accumulation and traces were detected in the whole body of the ants. Ants from five genera had similar regions for metal accumulation. The exoskeleton did not contribute to accumulation of metals; instead all metals were stored in internal organs. Not all genera were suitable for use as indicators; only Iridomyrmex spp. and Ochetellus spp. accumulated larger amount of metals in mine samples compared to reference samples.

Growing applications of nanoagrichemicals have resulted in their increasing accumulation in agricultural soils, which could modify soil properties and affect soil health. A greenhouse pot trial was conducted to determine the effects of three metallic nanoagrichemicals on several fundamental chemical properties of a rice paddy soil, including zinc oxide nanoparticles (ZnO NPs) and copper oxide nanoparticles (CuO NPs) at 100 mg/kg, and silicon oxide nanoparticles (SiO₂ NPs) at 500 mg/kg, as well as their bulk and ionic counterparts. The investigated soil amendments displayed significant and distinctive impact on the examined soil chemical properties relevant to agricultural production, including soil pH, redox potential, soil organic carbon (SOC), cation exchange capacity (CEC), and plant available As. For example, all amendments increased the bulk soil pH at day 47 to some extent, but the increase was substantially higher for SiO₃²⁻ (37.7%) than other amendments (5.8%–13.7%). Soil Eh was elevated markedly at day 47 after the addition of soil amendments in both the bulk soil (45.9%–74.4%) and rice rhizosphere soil (20.3%–68.9%). CuO NPs and Cu²⁺ generally exhibited greater impact on soil chemical properties than other agrichemicals. Significantly different responses to soil amendments were observed between bulk and rhizosphere soils, suggesting the essential role of plants in affecting soil properties and their responses to environmental disturbance. Overall, our results confirmed that the tested amendments could have remarkable impacts on the fundamental chemical properties of rice paddy soils.

Heavy fuel oil (HFO) accounts for approximately 80% of the fuel consumption of ocean-going ships in the world. Multiple toxic species are found in HFO exhaust, however, carbonaceous substances emitted from low-speed marine engine exhaust at different operating loads have not been thoroughly addressed. Therefore, a bench test for a low-speed marine engine with HFO fuel under different operating modes was carried out in this study. Emission factors and characteristics of CO₂, CO, organic carbon (OC), elemental carbon (EC), as well as OC and EC fragments, organic matters of n-alkanes and polycyclic aromatic hydrocarbons (PAHs) are given and discussed. Combined with the correlation analysis results among the measured species and engine technical parameters, the formation processes and influence factors of carbonaceous components are also inferred in this study. Besides, together with OC to EC ratio, n-alkanes to PAHs ratio, etc., EC1 to soot-EC ratio in PM can be considered as tracer characteristic of high-sulfur-content HFO ship distinguished from diesel fuel ships. Profiles of n-alkanes and PAHs in PM can be used to distinguish shipping emission source from other combustion sources. Moreover, characteristics of carbonaceous components in size-segregated particles are also discussed, including OC, EC, OC and EC fragments, as well as organic matters. Results show that most of the particle mass, OC, EC, and organic matters are concentrated in fine particles with size of less than 1.1 μm, indicating the significance of ultrafine particles. Formation processes of OC and EC fragments, EC1 and soot-EC are also deduced and proved combined with the characteristics of OC and EC fragments, organic matters, and especially PAHs. Besides, the large variations of OC to EC ratios and speciated profiles of n-alkanes and PAHs in different particle size bins indicate that particle size should be considered when they are used as characteristic tracer in source apportionment studies.

Aquatic plant biomass like Iris pseudacorus can be used as electron donor to improve denitrification performance in subsurface constructed wetlands. However, the phenomenon that the nitrogen removal rate declined in the terminal stage restricted the utilization of litters. In terms of this problem, this study investigated the performance of the used biomass through alkali treatment on nitrogen removal and analyzed the effect of alkali treatment on the component and structure of biomass and microbial community. The results showed that the alkali-treated biomass could further enhance the nitrogen removal by nearly 15% compared with used ones. The significant damage of cell walls and compact fibers containing cellulose and lignin through alkali treatment mainly resulted in the improvement of carbon release and nitrogen removal. With the addition of alkali-treated biomass, the richness index of microbes was higher compared with other biomass materials. Furthermore, the abundance of denitrification related genera increased and the abundance of genera for nitrification was maintained. Based on these finds, a mode of a more efficient Iris pseudacorus self-consumed subsurface flow constructed wetlands was designed. In this mode, the effluent total nitrogen could be stabilized below 5 mg L⁻¹ for nine months and the weight of litters could be further cut down by 75%. These findings would contribute to efficient utilization of plant biomass for nitrogen removal enhancement and final residue reduction in the wetlands.

Environmental quality data sets are typically imbalanced, because environmental pollution events are rarely observed in daily life. Prediction of imbalanced data sets is a major challenge in machine learning. Our recent work has shown deep cascade forest (DCF), as a base learning model, is promising to be recommended for environmental quality prediction. Although some traditional models were improved by introducing the cost matrix, little is known about whether cost matrix could enhance the prediction performance of DCF. Additionally, feature extraction is also an important way to potentially improve the model's ability to predict the imbalanced data. Here, we developed two novelty learning models based on DCF: cost-sensitive DCF (CS-DCF) and DCF that combines unsupervised learning models and greedy methods (USM-DCF-G). Subsequently, CS-DCF and USM-DCF-G were successfully verified by an imbalanced drinking water quality data set. Our data presented both CS-DCF and USM-DCF-G show better prediction performance than that of DCF alone did. In particular, USM-DCF-G shows the best performance with the highest F1-score (95.12 ± 2.56%), after feature extraction and selection by using unsupervised learning models and greedy methods. Thus, the two learning models, especially USM-DCF-G, were promising learning models to address environmental imbalanced issues and accurately predict environmental quality.

Fine particulate matter (PM₂.₅) is associated with various adverse health outcomes and poses serious concerns for public health. However, ground monitoring stations for PM₂.₅ measurements are mostly installed in population-dense or urban areas. Thus, satellite retrieved aerosol optical depth (AOD) data, which provide spatial and temporal surrogates of exposure, have become an important tool for PM₂.₅ estimates in a study area. In this study, we used AOD estimates of surface PM₂.₅ together with meteorological and land use variables to estimate monthly PM₂.₅ concentrations at a spatial resolution of 3 km² over Taiwan Island from 2015 to 2019. An ensemble two-stage estimation procedure was proposed, with a generalized additive model (GAM) for temporal-trend removal in the first stage and a random forest model used to assess residual spatiotemporal variations in the second stage. We obtained a model-fitting R² of 0.98 with a root mean square error (RMSE) of 1.40 μg/m3. The leave-one-out cross-validation (LOOCV) R² with seasonal stratification was 0.82, and the RMSE was 3.85 μg/m3, whereas the R² and RMSE obtained by using the pure random forest approach produced R² and RMSE values of 0.74 and 4.60 μg/m3, respectively. The results indicated that the ensemble modeling approach had a higher predictive ability than the pure machine learning method and could provide reliable PM₂.₅ estimates over the entire island, which has complex terrain in terms of land use and topography.

The trace element fluoride can be beneficial for oral health by preventing dental caries. However, fluoride is also known as an environmental pollutant. Fluoride pollution can lead to fluoride over-ingestion and can cause health issues, including dental fluorosis. Curcumin attenuated fluoride-induced toxicity in animal models, however the molecular mechanisms of how curcumin affects fluoride toxicity remain to be elucidated. We hypothesized that curcumin attenuates fluoride toxicity through modulation of Ac-p53. Here we investigated how curcumin affects the p53-p21 pathway in fluoride toxicity.LS8 cells were treated with NaF with/without curcumin. Curcumin significantly increased phosphorylation of Akt [Thr308] and attenuated fluoride-mediated caspase-3 cleavage and DNA damage marker γH2AX expression. Curcumin-mediated attenuation of caspase-3 activation was reversed by Akt inhibitor LY294002 (LY). However, LY did not alter curcumin-mediated γH2AX suppression. These results suggest that curcumin inhibited fluoride-mediated apoptosis via Akt activation, but DNA damage was suppressed by other pathways. Curcumin did not suppress/alter fluoride-mediated Ac-p53. However, curcumin itself significantly increased Ac-p53 and upregulated p21 protein levels to suppress cell proliferation in a dose-dependent manner. Curcumin suppressed fluoride-induced phosphorylation of p21 and increased p21 levels within the nuclear fraction. However, curcumin did not reverse fluoride-mediated cell growth inhibition. These results suggest that curcumin-induced Ac-p53 and p21 led to cell cycle arrest, while curcumin attenuated fluoride-mediated apoptosis via activation of Akt and suppressed fluoride-mediated DNA damage.By inhibiting DNA damage and apoptosis, curcumin may potentially alleviate health issues caused by fluoride pollution. Further studies are required to better understand the mechanism of curcumin-induced biological effects on fluoride toxicity.