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.

Widespread nitrobenzene (NB) contamination in groundwater requires an economical and effective remediation technology. In situ microbial reactive zone enhanced by injecting emulsified vegetable oil (EVO) is an effective method for remediating NB-contaminated groundwater, which can be reduced to aniline (AN) effectively in the reactive zone. However, the bio-mechanism of NB remediation in a real contaminated site is still unclear. Thus, a 3-D tank was established to conduct a pilot-scale experiment and the bacterial communities in the tank were analyzed by 16S rDNA high-throughput sequencing. The results suggested that the injection of EVO can stimulate some certain microorganisms to grow, and reduce NB though biological and biochemical processes. There were three degradation pathways of NB: (1) direct oxidation by Pseudomonas; (2) direct mineralization by Clostridium sensu stricto; and (3) coupled reduction of NB through microbial dissimilatory iron reduction by Geobacter and Arthrobacter. Among these pathways, the coupled reduction process is the main degradation pathway.

Freshwater salinization is a rapidly emerging ecological issue and is correlated with significant declines in aquatic biodiversity. It remains unclear how changing salinity regimes affect the physiology of sensitive aquatic insects. We used the parthenogenetic mayfly, Neocloeon triangulifer, to ask how ionic exposure history alters physiological processes and responses to subsequent major ion exposures. Using radiotracers (²²Na, ³⁵SO₄, and ⁴⁵Ca), we observed that mayflies chronically reared in elevated sodium or sulfate (157 mg L⁻¹ Na or 667 mg L⁻¹ SO₄) had 2-fold (p < 0.0001) and 8-fold (p < 0.0001) lower ion uptake rates than mayflies reared in dilute control water (16 mg L⁻¹ Na and 23 mg L⁻¹ SO₄) and subsequently transferred to elevated salinities, respectively. These acclimatory ion transport changes provided protection in 96-h toxicity bioassays for sodium, but not sulfate. Interestingly, calcium uptake was uniformly much lower and minimally influenced by exposure history, but was poorly tolerated in the toxicity bioassays. With qRT-PCR, we observed that the expression of many ion transporter genes in mayflies was influenced by elevated salinity in an ion-specific manner (general upregulation in response to sulfate, downregulation in response to calcium). Elevated sodium exposure had minimal influence on the same genes. Finally, we provide novel light microscopic evidence of histomorphological changes within the epithelium of the Malpighian tubules (insect primary excretory system) that undergoes cellular degeneration and necrosis secondary to calcium toxicity. We conclude that physiological plasticity to salinity stress is ion-specific and provide evidence for ion-specific toxicity mechanisms in N. triangulifer.

Road traffic emissions are an increasingly important source of particulate matter in urban and non-road environments, where non-tailpipe emissions can contribute substantially to elevated levels of metals associated with adverse health effects. Thus, better characterization and quantification of traffic-emitted metals is warranted. In this study, real-world emission factors for fine particulate metals were determined from hourly x-ray fluorescence measurements over a three-year period (2015–2018) at an urban roadway and busy highway. Inter-site differences and temporal trends in real-world emission factors for metals were explored. The emission factors at both sites were within the range of past studies, and it was found that Ti, Fe, Cu, and Ba emissions were 2.2–3.0 times higher at the highway site, consistent with the higher proportion of heavy-duty vehicles. Weekday emission factors for some metals were also higher by 2.0–3.5 times relative to Sundays for Mn, Zn, Ca, and Fe, illustrating a dependence on fleet composition and roadway activity. Metal emission factors were also inversely related to relative humidity and precipitation, due to reduced road dust resuspension under wetter conditions. Correlation analysis revealed groups of metals that were co-emitted by different traffic activities and sources. Determining emission factors enabled the isolation of traffic-related metal emissions and also revealed that human exposure to metals in ambient air can vary substantially both temporally and spatially depending on fleet composition and traffic volume.

Hydrochar (HC) serves as a promising adsorbent to remove the cadmium from aqueous solution due to porous structure. The chemical aging method is an efficient and easy-operated approach to improve the adsorption capacity of HC. In this study, four chemical aging hydrochars (CAHCs) were obtained by using nitric acid (HNO₃) with mass fractions of 5% (N5-HC), 10% (N10-HC), and 15% (N15-HC) to age the pristine HC (N0-HC) and remove the Cd²⁺ from the aqueous solution. The results displayed that the N15-HC adsorption capacity was 19.99 mg g⁻¹ (initial Cd²⁺ concentration was 50 mg L⁻¹), which increased by 7.4 folds compared to N0-HC. After chemical aging, the specific surface area and oxygen-containing functional groups of CAHCs were increased, which contributed to combination with Cd²⁺ by physical adsorption and surface complexation. Moreover, ion exchange also occurred during the adsorption process of Cd²⁺. These findings have important implications for wastewater treatment to transform the forestry waste into a valuable adsorbent for Cd²⁺ removal from water.

Antibiotic resistance genes (ARGs) are emerging contaminants in the environment and have been highlighted as a worldwide environmental and health concern. As important participants in the biogeochemical cycles, mangrove ecosystems are subject to various anthropogenic disturbances, and its microbiota may be affected by various contaminants such as ARGs. This study selected 13 transects of mangrove-covered areas in Hainan, China for sediment sample collection. The abundance and diversity of ARGs and mobile genetic elements (MGEs) were investigated using high-throughput quantitative polymerase chain reaction (HT-qPCR), and high-throughput sequencing was used to study microbial structure and diversity. A total of 179 ARGs belonging to 9 ARG types were detected in the study area, and the detection rates of vanXD and vatE-01 were 100%. The abundance of ARGs was 8.30 × 10⁷–6.88 × 10⁸ copies per g sediment (1.27 × 10⁻²–3.39 × 10⁻² copies per 16S rRNA gene), which was higher than similar studies, and there were differences in the abundance of ARGs in these sampling transects. The multidrug resistance genes (MRGs) accounted for the highest proportion (69.0%), which indicates that the contamination of ARGs in the study area was very complicated. The ARGs significantly positively correlated with MGEs, which showed that the high level of ARGs was related to its self-enhancement. The dominant bacteria at the genus level were Desulfococcus, Clostridium, Rhodoplanes, Bacillus, Vibrio, Enterococcus, Sedimentibacter, Pseudoalteromonas, Paracoccus, Oscillospira, Mariprofundus, Sulfurimonas, Aminobacterium, and Novosphingobium. There was a significant positive correlation between 133 bacterial genera and some ARGs. Chthoniobacter, Flavisolibacter, Formivibrio, Kaistia, Moryella, MSBL3, Perlucidibaca, and Zhouia were the main potential hosts of ARGs in the sediments of Hainan mangrove area, and many of these bacteria are important participants in biogeochemical cycles. The results contribute to our understanding of the distribution and potential hosts of ARGs and provide a scientific basis for the protection and management of Hainan mangrove ecosystem.

Understanding wetland water quality dynamics and associated influencing factors is important to assess the numerous ecosystem services they provide. We present a combined self-organizing map (SOM) and linear mixed-effects model (LMEM) to relate water quality variation of multipond systems (MPSs, a common type of non-floodplain wetlands in agricultural regions of southern China) to their extrinsic and intrinsic influences for the first time. Across the 6 test MPSs with environmental gradients, ammonium nitrogen (NH₄⁺-N), total nitrogen (TN), and total phosphate (TP) almost always exceeded the surface water quality standard (2.0, 2.0, and 0.4 mg/L, respectively) in the up- and midstream ponds, while chlorophyll-a (Chl-a) exhibited hypertrophic state (≥28 μg/L) in the midstream ponds during the wet season. Synergistic influences explained 69±12% and 73±10% of the water quality variations in the wet and dry season, respectively. The adverse, extrinsic influences were generally 1.4, 6.9, 3.2, and 4.3 times of the beneficial, intrinsic influences for NH₄⁺-N, nitrate nitrogen (NO₃⁻-N), TP, and potassium permanganate index (CODMₙ), respectively, although the influencing direction and degree of forest and water area proportion were spatiotemporally unstable. While CODMₙ was primarily linked with rural residential areas in the midstream, higher TN and TP concentrations in the up- and midstream were associated with agricultural land, and NH₄⁺-N reflected a small but non-negligible source of free-range poultry feeding. Pond surface sediments exhibited consistent, adverse effects with amplifications during rainfall, while macrophyte biomass can reflect the biological uptake of CODMₙ and Chl-a, especially in the mid- and downstream during the wet season. Our study advances nonpoint source pollution (NPSP) research for small water bodies, explores nutrient “source-sink” dynamics, and provides a timely guide for rural planning and pond management. The modelling procedures and analytical results can inform refined assessment of similar NFWs elsewhere, where restoration efforts are required.