Waste plastics can be degraded to nanoplastics (NPs, diameter<1 μm) by natural forces. NPs not only directly affect aquatic organisms but also adsorb other pollutants, causing combined pollution. Glyphosate is one of the most widely used herbicides and is commonly monitored in freshwater systems. In this study, the effects of the combined toxicity of polystyrene cationic amino-modified nanoparticles (nPS-NH₂) and glyphosate on a blue-green alga, Microcystis aeruginosa, were investigated. Our results demonstrated that 5 mg/L glyphosate had a strong inhibitory effect on M. aeruginosa (the 96-h inhibitory rate was 27%), while 5 mg/L nPS-NH₂ had no apparent effect on the growth of M. aeruginosa. Interestingly, nPS-NH₂ combined with glyphosate showed antagonistic effects on the inhibition of algal growth because nPS-NH₂ displayed a strong adsorption capacity for glyphosate, which significantly alleviated the inhibitory effect of glyphosate on M. aeruginosa growth. However, the presence of glyphosate enhanced the stability of the dispersion system, which allowed more nPS-NH₂ to adsorb on the surface of M. aeruginosa and may result in greater enrichment of nPS-NH₂ in the food chain to show potential repercussions to human life. Our current study provides a new theoretical basis for the combined effects of NPs and pesticide pollution.

In this study, we investigated the in situ responses of Red Sea picophytoplankton, the dominant phytoplankton group in the oligotrophic ocean, to two toxic polycyclic aromatic hydrocarbons (PAHs), phenanthrene and pyrene. The experiments were conducted across a latitudinal gradient of the Saudi Arabian Red Sea, an area sensitive to oil pollution. We observed significant adverse effects on the growth and abundance of the picocyanobacteria Synechococcus and picoeukaryotes, at all stations sampled. Prochlorococcus, which was abundant only at one of the stations, also appeared to be affected. Pyrene was found to be more toxic to phytoplankton at all stations. In general, picoeukaryotes exhibited higher sensitivity to PAHs than Synechococcus. Populations in the highly oligotrophic Northern region of the Red Sea were more tolerant to PAHs, presumably influenced by the natural selection of more resistant strains of phytoplankton due to the prolonged exposure to PAHs. Toxicity threshold values estimated here are higher than those reported for picophytoplankton from other oligotrophic marine waters and exceed by far the natural levels of PAHs in many oceans. Our findings reveal a possible adaptation of picophytoplankton populations to oil-related contaminants, which may clearly influence their spatial distribution patterns in the Red Sea.

Groundwater is an essential public and drinking water supply and its protection is a goal for global policies. Here, we investigated the presence and prevalence of antibiotic residues, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and microbial contamination in groundwater environments at various distances from urban areas. Antibiotic concentrations ranged from below detection limit to 917 ng/L, being trimethoprim, macrolide, and sulfonamide the most abundant antibiotic classes. A total of eleven ARGs (aminoglycoside, β-lactam, chloramphenicol, Macrolide-Lincosamide-Streptogramin B - MLSB, sulfonamide, and tetracycline), one antiseptic resistance gene, and two MGEs were detected by qPCR with relative abundances ranging from 6.61 × 10−7 to 2.30 × 10−1 copies/16S rRNA gene copies. ARGs and MGEs were widespread in the investigated groundwater environments, with increased abundances not only in urban, but also in remote areas. Distinct bacterial community profiles were observed, with a higher prevalence of Betaproteobacteria and Bacteroidetes in the less-impacted areas, and that of Firmicutes in the contaminated groundwater. The combined characteristics of increased species diversity, distinct phylogenetic composition, and the possible presence of fecal and/or pathogenic bacteria could indicate different types of contamination. Significant correlations between ARGs, MGEs and specific taxa within the groundwater bacterial community were identified, revealing the potential hosts of resistance types. Although no universal marker gene could be determined, a co-selection of int1, qacEΔ1 and sulI genes, a proxy group for anthropogenic pollution, with the tetC, tetO, tetW resistance genes was identified. As the tet group was observed to follow the pattern of environmental contamination for the groundwater samples investigated in this study, our results strongly support the proposal of this group of genes as an environmental tracer of human impact. Overall, the present study investigated several emerging contaminants in groundwater habitats that may be included in monitoring programs to enable further regulatory and protection measures.

This study evaluated associations between the bioreactivity of PM2.5in vitro and emission sources in the vicinity of a petrochemical complex in Taiwan. The average PM2.5 was 30.2 μg/m3 from 9 February to 23 March 2016, and the PM2.5 was clustered in long-range transport (with major local source) (12.8 μg/m3), and major (17.3 μg/m3) and minor industrial emissions (4.7 μg/m3) using a k-means clustering model. A reduction in cell viability and increases in the cytotoxicity-related lactate dehydrogenase (LDH), oxidative stress-related 8-isoprostane, and inflammation-related interleukin (IL)-6 occurred due to PM2.5 in a dose-dependent manner. The PM2.5 from major industrial emissions was significantly correlated with increased 8-isoprostane and IL-6, but this was not observed for long-range transport or minor industrial emissions. The bulk metal concentration was 9.52 ng/m3 in PM2.5. We further observed that As, Ba, Cd, and Se were correlated with LDH in the long-range transport group. Pb in PM2.5 from the major industrial emissions was correlated with LDH, whereas Pb and Se were correlated with 8-isoprostane. Sr was correlated with cell viability in the minor industrial emissions group. We demonstrated a new approach to investigate particle bioreactivity, which suggested that petrochemical-emitted PM2.5 should be a concern for surrounding residents' health.

Many of the world's large coastal cities discharge partially treated wastewater effluents containing various endocrine disrupting chemicals (EDCs) to coastal environments. Nonylphenols (NP) and bisphenol A (BPA) were found to be the most abundant EDCs in sewage effluents in Hong Kong. The environmental fate and ecological risk of these two EDCs remains largely unknown, particular for coastal systems with complex hydrodynamic flows. Based on a validated three-dimensional (3D) multiple-scale hydrodynamic model, a field-based study was conducted to track the two EDCs from potential sources to the only marine reserve in Hong Kong. The two compounds were detected in all seawater, suspended particle, and sediment samples, with higher aqueous concentrations in wet season than in dry season. High concentrations in sediments suggest sediment is a sink, posing an ecological risk to the benthos. The fate and transport of the two EDCs was predicted using a 3D near-field Lagrangian jet model seamlessly coupled with a 3D shallow water circulation model. The results suggested the NP and BPA in the marine reserve cannot be solely attributed to the nearby submarine sewage outfall, but likely concurrently contributed by other sources. This study calls for more effective measures of reducing the use and release of these EDCs, and research to investigate their impacts on the marine benthos.

The transfer of antibiotic resistance genes (ARGs) in the environment is a threat to both human and animal health. However, the contribution of bacteriophages to the dissemination of resistance genes via transduction is rarely explored. In this study, we screened pig feces from three commercial farms in China for 32 clinically relevant ARG types to assess the presence of the ARG population in bacteria and bacteriophage and further to estimate the contribution of bacteriophages to the dissemination of antibiotic resistance. We found that bacteriophage DNA contained 35.5% of the target ARG types and sul1, blaTEM and ermB were found in 100% of the phage DNA samples. The most abundant genes in the bacterial population were ermB and fexA whereas ermB was the most abundant in bacteriophage. In contrast, floR was the least abundant ARG in both populations. Also, the ratio index of the abundance of ARGs in bacteriophage and bacteria was firstly used in this study as an estimator of bacteriophage ability to transmit ARGs. The ratio for qnrA was the greatest (about 10−1) and differed from the most abundant bacteriophage ARG ermB. In addition, fexA had the lowest ratio value (about 10−6) and not floR. These results illustrate that ARGs abundance and detection rates used alone probably be not suitable for comprehensively judging the contribution of bacteriophage to the dissemination of antibiotic resistance. A more suitable model is the application of three indices; occurrence rate, absolute abundance in bacteriophage and the ratio value as warning and monitoring tools for environmental ARG assessments in bacteriophages.

Hypermethylation of СpG islands in the promoter regions of several genes with basic protective function in blood leukocytes of individuals exposed to ionizing radiation long time ago (2–46 years), and differential effects of age and radiation exposure on hypermethylation was reported in our previous work. To validate these results, epigenetic modifications were assessed in an independent series of 49 nuclear industry workers from the “Mayak” facility (67–84 years old at sampling) with documented individual accumulated doses from the prolonged external γ-radiation exposure (95.9–409.5 cGy, end of work with radiation:0.3–39 years ago), and in 50 non-exposed persons matched by age. In addition to the genes analyzed before (RASSF1A, p16/INK4A, p14/ARF, GSTP1), four additional loci were analyzed: TP53, ATM, SOD3, ESR1. The frequency of individuals displaying promoter methylation of at least one of the 8 genes (71.4%) was significantly higher in exposed group as compared to the control group (40%), p = .002, OR = 3.75. A significantly elevated frequency of individuals with hypermethylated СpG islands in GSTP1, TP53, SOD3 promoters was revealed among exposed subjects as compared to the control group (p = .012, OR = 8.41; p = .041, OR = 4.02 and p = .009, OR = 3.42, respectively). A similar trend (p = .12, OR = 3.06) was observed for the p16/INK4A gene. As a whole, p16/INK4A and GSTP1 promoter hypermethylation in irradiated subjects from both previously and currently analyzed groups was pronounced. Thus, the direction of the effects was fully confirmed, suggesting the result reproducibility. No statistically significant correlation between promoter methylation and individual radiation dose was found. Further studies are required to create an array of blood epigenetic markers of radiation exposure associating with premature aging and age-related diseases and to accurately evaluate radiation-added effect across the range of doses.The results of studies of epigenetic changes in two independent samples of irradiated subjects indicated the significance of radiation factor in the induction of hypermethylation of CpG islands in gene promoters that is revealed in blood cells years and decades after exposure.

In order to improve the prediction accuracy and real-time of the air pollutant concentration prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning machine (ANFIS-WELM) based on the weighted extreme learning machine (WELM) and the adaptive neuro-fuzzy inference system (ANFIS) combined air pollutant concentration prediction method. Firstly, Gaussian membership function parameters are selected to fuzzify the input values and calculate the membership degree of each input variable. Secondly, corresponding fuzzy rules are activated, and the firing strength is normalized to calculate the output matrix of hidden nodes. Then, the optimal parameters (C, M), weights are assigned to weighted ELM by using locally weighted linear regression, and the regularized WELM target formula with equality constraint is optimized by the Karush–Kuhn–Tucker (KKT) conditions, the output weight matrix is calculated, and finally the prediction output matrix is calculated. Based on the air pollutant concentration data collected in Datong, Taiwan, the data on the pollutants containing carbon monoxide (CO), nitric oxide (NO), PM2.5 (particulate matter) and PM10, are selected by different historical time series lengths, using genetic algorithm-backpropagation neural network (GA-BPNN), support vector regression (SVR), extreme learning machine (ELM), WELM, ANFIS, regularized extreme learning adaptive neuro-fuzzy inference system (R-ELANFIS) and ANFIS-WELM are built for predict the concentration of each pollutant collected by single monitoring point in single-step time series. The experimental results show that the ANFIS-WELM presented in this paper has better prediction accuracy and real-time performance, realizes the prediction of multi-step time series on the basis of the ANFIS-WELM, and realizes the engineering application of the ANFIS-WELM algorithm package on the self-developed mobile source emissions online monitoring data center software system.

Selenium (Se) is an essential micronutrient for animals and humans with a relatively narrow margin between nutritional essentiality and potential toxicity. Even though our previous studies have demonstrated algae could efficiently remove Se, mainly through volatilization, concern is raised about eco-risks posed by the remaining Se in algae. Here, Sinanodonta woodiana was investigated as a biofilter for the removal of Se-containing Chlorella vulgaris and for its potential risk to human health. Our results suggest filtration rates of S. woodiana were independent of Se levels in algal biomass, with a removal efficiency of between 60 and 78%. However, Se concentrations accumulated in mussels were significantly correlated with algal-borne Se levels, with a dietary assimilation efficiency ranging from 12% to 46%. Thus, a pilot biofiltration system was set up to assess uptake and depuration processes. The system was found to efficiently remove Se laden algae through the uptake by mussels, while 21% of Se in mussels could be depurated in 6 days. Among tissues, gills accumulated the highest Se concentration after assimilating algal-borne Se but shed Se compounds in the fastest pace during depuration. Health risks posed by consumption of mussels exposed to different sources of Se were further assessed. S. woodiana accumulated the highest Se concentration after exposure to waterborne SeMet, followed by dietary Se, selenite and control. The relatively higher Se levels were found in gills for all the treatments. After boiling, the most common method of cooking mussels, the greatest reduction in Se concentration occurred in mantle for the control and dietary Se groups and in muscle for the SeMet and selenite treatments. Therefore, within the safe limits, Se-containing mussels can be consumed as a dietary supplement. Overall, our research suggests incorporation of mussels into an algal treatment system can improve Se removal efficiency and also provide financial incentives for practitioners.

Multi-stage constructed wetlands (CWs) have been proved to be a cost-effective alternative in the treatment of various wastewaters for improving the treatment performance as compared with the conventional single-stage CWs. However, few long-term full-scale multi-stage CWs have been performed and evaluated for polishing effluents from domestic wastewater treatment plants (WWTP). This study investigated the seasonal and spatial dynamics of carbon and the effects of the key factors (input loading and temperature) in the large-scale seven-stage Wu River CW polishing domestic WWTP effluents in northern China. The results indicated a significant improvement in water quality. Significant seasonal and spatial variations of organics removal were observed in the Wu River CW with a higher COD removal efficiency of 64–66% in summer and fall. Obvious seasonal and spatial variations of CH₄ and CO₂ emissions were also found with the average CH₄ and CO₂ emission rates of 3.78–35.54 mg m⁻² d⁻¹ and 610.78–8992.71 mg m⁻² d⁻¹, respectively, while the higher CH₄ and CO₂ emission flux was obtained in spring and summer. Seasonal air temperatures and inflow COD loading rates significantly affected organics removal and CH₄ emission, but they appeared to have a weak influence on CO₂ emission. Overall, this study suggested that large-scale Wu River CW might be a potential source of GHG, but considering the sustainability of the multi-stage CW, the inflow COD loading rate of 1.8–2.0 g m⁻² d⁻¹ and temperature of 15–20 °C may be the suitable condition for achieving the higher organics removal efficiency and lower greenhouse gases (GHG) emission in polishing the domestic WWTP effluent. The obtained knowledge of the carbon dynamics in large-scale Wu River CW will be helpful for understanding the carbon cycles, but also can provide useful field experience for the design, operation and management of multi-stage CW treatments.