The contamination with antibiotic resistance genes (ARGs) in raw drinking water source may pose a direct threat to human health. In this study, metagenomics sequencing and analysis were applied to investigate the ARG pattern in 12 drinking water sources in upper and middle reach of Huaihe River Basin, China. Based on the redundant analysis and multi-linear regression model, location, specific microbial taxa, number of livestock and health facilities significantly influenced the ARG profile in drinking water sources. Besides the cluster effect of ARG in samples from plain and bedrock mountain areas, the samples from fracture aquifer areas also showed a distinctive biogeographic pattern with that from porous aquifer areas. Putative ARGs host Opitutus and Flavobacterium were the enriched biomarkers in plain and fracture aquifer area respectively, which mainly carried bacitracin, multidrug, beta-lactam and tetracycline ARGs. This result illuminated that both natural background and anthropogenic activities in the watershed influenced the ARG profile in natural freshwater system significantly. The low MGEs abundance and absence of pathogen revealed a low ARG dissemination risk in sampled drinking water sources, while Polynucleobacter was an abundant ARGs host and was significantly related to the ARG profile, which indicated that specific bacteria was responsible for ARGs propagation and accumulation in surface freshwater system. Further researches are needed to assess human exposure to raw drinking water source and the potential risk, as well as the species interaction in microbial community and its impact on ARG propagation under oligotrophic condition.

This study characterized spatio-temporal variations in the concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds in the vicinity of gas and compressed natural gas (CNG) stations in Tehran, Iran. Health risk assessment (HRA) was computed using Monte Carlo simulations (MCS) for evaluating inhalation lifetime cancer risk (LTCR), the hazard quotient (HQ), and sensitivity analysis (SA) for BTEX exposure in different age groups (birth to <81) and as a function of distance (0–250 m) from the center of the stations. For all monitoring stations, the average values of benzene, toluene, ethylbenzene, and xylene in winter were 466.09 ± 132.25, 873.13 ± 233.51, 493.05 ± 141.22, and 910.57 ± 145.40 μg m⁻³, respectively. The mean wintertime ratios of T/B for the 12 stations ranged from 1.69 to 2.04. Furthermore, there was no significant relationship between the concentration of BTEX with either the specific month or distance from the center of stations (p > 0.05). Factors promoting BTEX formation in the study region were fuel evaporation and gas/CNG station emissions. The LTCRs for the target compounds in the winter for different age groups and distances from the center of stations was limited to 2.11 × 10⁻⁴ to 1.82 × 10⁻³ and 2.30 × 10⁻⁴ to 2.01 × 10⁻³, respectively, which exceeded proposed values by U.S. EPA. Moreover, the HQs for BTEX for three age groups and distances were limited to between 2.89 × 10⁻⁵ and 9.33 × 10⁻², which were lower than the acceptable limit (HQs < 1). The results of this work are applicable to similar areas that are heavily populated with vehicular traffic. This study motivates a closer look at mitigation strategies to limit the health effects of carcinogenic emissions such as benzene and ethylbenzene from gas/CNG stations.

This study analyzes microplastic ingestion by three deep-water elasmobranch species (Galeus melastomus, Scyliorhinus canicula and Etmopterus spinax) from the Tyrrhenian Sea, discriminating between stomach and intestine contents. The absence of significant differences in frequency and abundance of plastic items into stomachs seems to suggest that ecological diversity among the three sharks does not strongly influence the probability of plastic ingestion in the study area. On the other hand, the detected differences in the microplastic content into the intestine might be due to a different retention time of microplastics, suggesting how feeding habits could influence metabolic features, and therefore affect the recovery of ingested plastic items. This information would improve the future development of marine micro-litter monitoring systems, following the MSFD requirements. Moreover, this study shows that all the three examined elasmobranch species can give important information even with relatively small sample sizes (N ≈ 30), and they could be used as target species for monitoring micro-litter ingestion in deep-water habitats.

The Wiśniówka rock strip mining area (south-central Poland) with quartzite quarries, acid water bodies and tailings piles is one of the most unique acid mine drainage (AMD) sites throughout the world. This is due to the occurrence of enormous amounts of pyrite unknown in sedimentary formations worldwide. Of the two mineralization zones, one that is the most abundant in arsenical pyrite occurs in the lowermost Upper Cambrian formation of the Podwiśniówka quarry. The As-rich pyritiferous clastic rocks are exposed as a result of deep quartzite extraction during 2013–2014. In addition, the clayey-silty shale interbeds are enriched in rare earth element (REE) minerals. The mining operation left an acidic lake with a pH of about 2.4–2.6 and increased contents of sulfates, metal(loid)s and REE. The Podwiśniówka pyrite-rich waste material was stacked up in many places of the mining area giving rise to strongly acidic spills that jeopardized the neighboring environment. One of these unexplored tailings piles was a source of extremely sulfate- and metal(loid)-rich pools with unusual enrichments in As (up to 1548 mg L⁻¹) and REE (up to 24.84 mg L⁻¹). These distinctly exceeded those previously reported in the Wiśniówka area. A broad scope of geochemical, mineralogical and petrographic methods was used to document these specific textural and mineralogical properties of pyrite facilitating its rapid oxidation. The pyrite oxidation products reacted with REE-bearing minerals releasing these elements into acid water bodies. Statistical methods were employed to connect the obtained tailings pool hydrogeochemical data with those derived from this and the previous studies of the Podwiśniówka and Wiśniówka Duża acid pit lakes. In contrast to metal(loid) profiles, the characteristic shale-normalized REE concentration patterns turned out to be more suitable for solving different AMD issues including provenance of mine waste material in the tailings pile examined.

Plastic pollution is ubiquitous throughout the marine environment, with microplastic (i.e. <5 mm) contamination a global issue of emerging concern. The lack of universally accepted methods for quantifying microplastic contamination, including consistent application of microscopy, photography, an spectroscopy and photography, may result in unrealistic contamination estimates. Here, we present and apply an analysis workflow tailored to quantifying microplastic contamination in marine waters, incorporating stereomicroscopic visual sorting, microscopic photography and attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy. The workflow outlines step-by-step processing and associated decision making, thereby reducing bias in plastic identification and improving confidence in contamination estimates. Specific processing steps include (i) the use of a commercial algorithm-based comparison of particle spectra against an extensive commercially curated spectral library, followed by spectral interpretation to establish the chemical composition, (ii) a comparison against a customised contaminant spectral library to eliminate procedural contaminants, and (iii) final assignment of particles as either natural- or anthropogenic-derived materials, based on chemical type, a compare analysis of each particle against other particle spectra, and physical characteristics of particles. Applying this workflow to 54 tow samples collected in marine waters of North-Western Australia visually identified 248 potential anthropogenic particles. Subsequent ATR-FTIR spectroscopy, chemical assignment and visual re-inspection of photographs established 144 (58%) particles to be of anthropogenic origin. Of the original 248 particles, 97 (39%) were ultimately confirmed to be plastics, with 85 of these (34%) classified as microplastics, demonstrating that over 60% of particles may be misidentified as plastics if visual identification is not complemented by spectroscopy. Combined, this tailored analysis workflow outlines a consistent and sequential process to quantify contamination by microplastics and other anthropogenic microparticles in marine waters. Importantly, its application will contribute to more realistic estimates of microplastic contamination in marine waters, informing both ecological risk assessments and experimental concentrations in effect studies.

By identifying the main sources of nitrate (NO3−) can obtain useful information to support the management of NO3− pollution, particularly in subtropical catchments with shallow drinking water wells. This study used water chemistry and dual stable isotopes δ15N and δ18O methods to assess seasonal and spatial variations of NO3− in precipitation, surface water, and groundwater in an agricultural and forest subtropical catchment in Jiangxi Province, China. The maximum concentrations of nitrate-nitrogen (NO3−-N) and ammonium-nitrogen (NH4+-N) were 10.4 and 10.8 mg L−1in samples collected from 221 rainfall events from 2011 to 2013. About 4.4% and 12.3% NH4+-N concentrations of surface water and groundwater exceeded the thresholds of 1.0 and 0.2 mg L−1. The NO3−-N concentrations in surface water were closely correlated with NH4+-N concentrations in surface water and groundwater (r = −0.71 and r = −0.71, P < 0.05). The concentrations of NH4+-N and NO3−-N were significantly higher in a fishery pond and nearby drinking wells than in other monitoring points. Annual exports of NO3−-N and NH4+-N were 4.06 × 104 and 8.14 × 103 kg yr−1, respectively and NO3−-N is the main form of N loss. The δ15N values ranged from 0‰ to 20‰ in surface water and groundwater, and the δ18O values ranged from 0‰ to 15‰ and 1‰–13‰, respectively. Dual stable isotope natural abundance distribution and water chemistry [NO3−]/[Cl−] molar ratio information suggested that manure and sewage and soil N were the main sources of NO3− in surface water and manure and sewage in groundwater in summer and winter. In spring, water occurred denitrification and ammonium fertilizer, manure and sewage were the main sources of NO3− in surface water and groundwater which sampling points were closer residential area and fish ponds than paddy field and local farmers used more Manure. Manure applications should be reasonable around drinking water wells to protect the drinking water quality.

Propranolol (PRO), a human β-AR (β-adrenergic receptor) antagonist, is considered to result in specific effects in a non-target species, D. magna, based on our previous studies. The present study investigated the effects of β-AR agents, including an antagonist and agonist using pharmacologically relevant endpoints as well as a more holistic gene expression approach to reveal the impacts and potential mode of actions (MOAs) in the model non-target species. Results show that the responses in cardiac endpoints and gene expression in D. magna are partially similar but distinguishable from the observations in different organisms. No effect was observed on heart size growth in PRO and isoprenaline (ISO) exposure. The contraction capacity of the heart was decreased in ISO exposure, and the heart rate was decreased in PRO exposure. Time-series exposures showed different magnitudes of effect on heart rate and gene expression dependent on the type of chemical exposure. Significant enrichment of gene families involved in protein metabolism and biotransformation was observed within the differentially expressed genes, and we also observed differential expression in juvenile hormone-inducible proteins in ISO and PRO exposure, which is suspected of having endocrine disruption potential. Taken together, deviation between the effects of PRO and ISO in D. magna and other organisms suggests dissimilarity in MOAs or attributes of target bio-molecules between species. Additionally, PRO and ISO may act as endocrine disruptors based on the gene expression observation. Results in the present study confirm that it is challenging to predict ecological impact of active pharmaceutical ingredients (APIs) based on the available data acquired through human-focused studies. Furthermore, the present study provided unique data and a case study on the impact of APIs in a non-target organism.

Long- and short-term exposure to PM2.5 is of great concern in China due to its adverse population health effects. Characteristic of the severity of the situation in China is that in the Jing-Jin-Ji region considered in this work a total of 2725 excess deaths have been attributed to short-term PM2.5 exposure during the period January 10–31, 2013. Technically, the processing of large space-time PM2.5 datasets and the mapping of the space-time distribution of PM2.5 concentrations often constitute high-cost projects. To address this situation, we propose a synthetic modeling framework based on the integration of (a) the Bayesian maximum entropy method that assimilates auxiliary information from land-use regression and artificial neural network (ANN) model outputs based on PM2.5 monitoring, satellite remote sensing data, land use and geographical records, with (b) a space-time projection technique that transforms the PM2.5 concentration values from the original spatiotemporal domain onto a spatial domain that moves along the direction of the PM2.5 velocity spread. An interesting methodological feature of the synthetic approach is that its components (methods or models) are complementary, i.e., one component can compensate for the occasional limitations of another component. Insight is gained in terms of a PM2.5 case study covering the severe haze Jing-Jin-Ji region during October 1–31, 2015. The proposed synthetic approach explicitly accounted for physical space-time dependencies of the PM2.5 distribution. Moreover, the assimilation of auxiliary information and the dimensionality reduction achieved by the synthetic approach produced rather impressive results: It generated PM2.5 concentration maps with low estimation uncertainty (even at counties and villages far away from the monitoring stations, whereas during the haze periods the uncertainty reduction was over 50% compared to standard PM2.5 mapping techniques); and it also proved to be computationally very efficient (the reduction in computational time was over 20% compared to standard mapping techniques).

Water diversion has been increasingly applied to improve water quality in many water bodies. However, little is known regarding pollution by organic micropollutants (OMPs) in water diversion projects, especially at the supplier, and this pollution may threaten the quality of transferred water. In the present study, a total of 110 OMPs belonging to seven classes were investigated in water and sediment collected from a supplier of the Yangtze River within four water diversion projects. A total of 69 and 58 target OMPs were detected in water and sediment, respectively, at total concentrations reaching 1041.78 ng/L and 5942.24 ng/g dry weight (dw). Polycyclic aromatic hydrocarbons (PAHs) and pharmaceuticals were the predominant pollutants identified. When preliminarily compared with the pollution in the receiving water, the Yangtze River generally exhibited mild OMPs pollution and good water quality parameters, implying a clean water source in the water diversion project. However, in Zongyang and Fenghuangjing, PAHs pollution was more abundant than that in the corresponding receiving water in Chaohu Lake. Ammonia nitrogen pollution in the Wangyu River was comparable to that in Taihu Lake. These findings imply that water diversion may threaten receiving waters in some cases. In addition, the risks of all detected pollutants in both water and sediment were assessed. PAHs in water, especially phenanthrene and high-molecular-weight PAHs, posed high risks to invertebrates, followed by the risks to fish and algae. Pharmaceuticals, such as antibiotics and antidepressants, may also pose risks to algae and fish at a number of locations. To the best of our knowledge, this report is the first to describe OMPs pollution in water diversion projects, and the results provide a new perspective regarding the security of water diversion projects.

The environment is one of the main reservoirs of antibiotic resistance genes (ARGs) but multidrug resistant (MDR) environmental isolates are barely characterised. As suggested by the name, Pedobacter species have been predominantly isolated from soils, but are also recovered from water (including drinking water), chilled food, fish, compost, sludge, glaciers and other extreme environments. The susceptibility phenotype of Pedobacter lusitanus NL19 (isolated from a deactivated uranium mine), its closely related species and the genus type strain were investigated. All strains are MDR bacteria, resistant to β-lactams, colistin, aminoglycosides and ciprofloxacin. Therefore, Pedobacter spp. are likely intrinsically resistant to β-lactams (including ertapenem) and to other three classes of antibiotics. 6%–8% of their total protein-encoding genes encode a diverse collection of putative ARGs, including β-lactamases. These enzymes are highly abundant in all the other Pedobacter strains with sequenced genomes, especially class C, class B3 and class A. LUS-1 and PLN-1 were further characterised in E. coli. LUS-1 is a class A β-lactamase and it conferred an increase in the MIC of cefotaxime, albeit very low. PLN-1 is a class B3 β-lactamase with carbapenemase activity, conferring resistance to ertapenem and a 66x and 16x increase in the MIC of imipenem and meropenem, respectively. PLN-1 also hydrolyses ampicillin, 1st and 3rd generation cephalosporins, and at a lower extent cephamycins and 4th generation cephalosporins. Therefore, Pedobacter spp. encode a large and diverse arsenal of resistance mechanisms that make them environmental superbugs.