Overuse of antibiotics is accelerating the spread of resistance risk in the environment. In drinking water supply systems, the effect of antibiotics on the resistance of biofilm is unclear, and there have been few studies in disinfectant-containing systems. Here, we designed a series of drinking water supply reactors to investigate the effects of antibiotics on biofilm and bacteria in the water. At low concentrations, antibiotics could promote the growth of bacteria in biofilm; among the tested antibiotics (tetracycline, sulfadiazine and chloramphenicol), tetracycline had the strongest ability to promote this. And the antibiotic resistant bacteria (ARB) could inhibit the growth of bacteria in drinking water. Results have shown that antibiotics enhanced the bacterial chlorine resistance in the effluent, but reduced that in the biofilm. Furthermore, metagenomic analysis showed that antibiotics reduced the richness of biofilm communities. The dominant phyla in the biofilm were Proteobacteria, Planctomycetes, and Firmicutes. In tetracycline-treated biofilm, the dominant phylum was Planctomycetes. In sulfadiazine- and chloramphenicol-treated groups, bacteria with complex cell structures preferentially accumulated. The dominant class in biofilm in the ARB-added group was Gammaproteobacteria. The abundance of antibiotic resistant genes (ARGs) was correlated with biofilm community structure. This study shows that antibiotics make the biofilm community structure of drinking water more resistant to chlorine. ARGs may be selective for certain bacteria in the process, and there may ultimately be enhanced chlorine and antibiotic resistance of effluent bacteria in drinking water.

The sulfate pollution in water environment gains more and more concerns in recent years. The discharge of domestic, municipal, and industrial wastewaters increases the riverine sulfate concentrations, which may cause local health and ecological problems. To better understand the sources of sulfate, this study collected water samples in a typical agricultural watershed in East Thailand. The source apportionment of sulfide was conducted by using stable isotopes and receptor models. The δ³⁴SSO₄ value of river water varied from 1.2‰ to 16.4‰, with a median value of 8.9‰. The hydrochemical data indicated that the chemical compositions of Mun river water were affected by the anthropogenic inputs and natural processes such as halite dissolution, carbonate, and silicate weathering. The positive matrix factorization (PMF) model was not suitable to trace source of riverine sulfate, because the meaning of the extracted factors seems to be vague. Based on the elemental ratio and isotopic composition, the inverse model yielded the relative contribution of sulfide oxidation (approximately 46.5%), anthropogenic input (approximately 41.5%), and gypsum dissolution (approximately 12%) to sulfate in Mun river water. This study indicates that the selection of models for source apportionment should be careful. The large contribution of anthropogenic inputs calls an urgent concern of the Thai government to establish effective management strategies in the Mun River basin.

The sorption behavior of phthalate additives in plastic and microplastic litter is an important process controlling the exposure, net health risk and ecotoxicity of these co-occurring pollutants. Plastic crystallinity and particle morphology are hypothesized to be important variables for microplastics sorption behavior, but to date there have been few direct studies to explicitly test for the influence of these parameters. To address this, in this study we explored the sorption of dibutyl phthalate (DBP) as a probe molecule to diverse polyethylene microplastics including irregularly-shaped pure polyethylene microplastics (IPPM), black plastic film microplastics (BPFM), white plastic film microplastics (WPFM), and commercial microspheres (CM), which had crystallinities ranging from 17 to 99%. Sorption kinetics for all materials could be well represented with both a pseudo-first-order (R² = 0.87–0.93) and pseudo-second-order model (R² = 0.87–0.93). Further, sorption was highly linear in the concentration range of 0.5–10 mg L⁻¹, with no greater performance from a linear sorption model (R² = 0.96–0.99) than the non-linear Freundlich or Temkin sorption models. The partition coefficient (Kd) of DBP sorption onto IPPM, BPFM, WPFM and CMs were 1974.55 L kg⁻¹, 1483.85 L kg⁻¹, 1477.45 L kg⁻¹ and 509.37 L kg⁻¹, respectively, showing a significant decrease with increasing crystallinity (r² = 0.98). The particle size of microplastics (27–1000 μm) is, however, an indecisive factor affecting their sorption behavior for DBP in this study. This study provides new insight that crystallinity plays a governing role on the sorption of phthalate from microplastic. This should be considered in future exposure studies and assessments of phthalates from plastics and microplastics.

Real-time river chloride prediction has received a lot of attention for its importance in chloride control and management. In this study, an artificial neural network model (i.e., multi-layer perceptron, MLP) and a statistical inference model (i.e., stepwise-cluster analysis, SCA) are developed for predicting chloride concentration in stream water. Then, an ensemble learning model based on MLP and SCA is proposed to further improve the modeling accuracy. A case study of hourly river chloride prediction in the Grand River, Canada is presented to demonstrate the model applicability. The results show that the proposed ensemble learning model, MLP-SCA, provides the best overall performance compared with its two ensemble members in terms of RMSE, MAPE, NSE, and R² with values of 11.58 mg/L, 27.55%, 0.90, and 0.90, respectively. Moreover, MLP-SCA is more competent for predicting extremely high chloride concentration. The prediction of observed concentrations above 150 mg/L has RMSE and MAPE values of 9.88 mg/L and 4.40%, respectively. The outstanding performance of the proposed MLP-SCA, particularly in extreme value prediction, indicates that it can provide reliable chloride prediction using commonly available data (i.e., conductivity, water temperature, river flow rate, and rainfall). The high-frequency prediction of chloride concentration in the Grand River can supplement the existing water quality monitoring programs, and further support the real-time control and management of chloride in the watershed. MLP-SCA is the first ensemble learning model for river chloride prediction and can be extended to other river systems for water quality prediction.

Indoor environment constitutes an important source of industrial additive chemicals to human exposure. We hypothesized that the influence of residential environment on human exposure varies among different types of additive chemicals and differs between children and mothers. This study determined a suite of additive chemicals in house dust from South China dwellings (n = 47) and urine from child-mother pairs. Concentrations of phthalates (PAEs; median 601 μg/g) were 2–3 orders of magnitude greater than those of parabens (0.82 μg/g), bisphenols (3.31 μg/g), and benzophenone-related chemicals (2.69 μg/g). Urinary concentrations differed between children and mothers, but the pattern of differences varied between chemical groups. Children exhibited greater urinary levels of mono-PAEs than mothers (510 versus 395 ng/mL, p = 0.152), while the latter population exhibited greater levels of parabens and benzophenones. Regression analyses indicate a lack of association between dust and urinary levels for most chemicals, suggesting that other exposure pathways can complicate human exposure scenarios. Indeed, we estimated that the daily intake via dust ingestion only constituted 0.002–0.81% of total daily intake estimated based on urine data for mothers and 0.04–5.61% for children. Future efforts are needed to better characterize source-specific exposure for different populations.

Fomesafen (FSA) is widely used in soybean fields for weed control. However, the persisting characteristics of FSA in the agricultural soil or water may become a hidden danger causing environmental pollution and phytotoxicity to succession crops. In this study, the growth and physiological responses of rice to FSA were investigated. It was found that the growth of rice seedlings was obviously inhibited by FSA exposure especially at over 0.1 mg L⁻¹. To gain an insight into the molecular mechanisms for the potential ecotoxicology, four libraries of rice roots and shoots exposed to FSA were created and subjected to the global RNA-sequencing (RNA-Seq) combined with HRLC-Q-TOF-MS/MS analytical technologies to comprehensively characterize the biochemical processes and catalytic reactions involved in FSA metabolism in rice. Compared with those without FSA, 499 and 450 up-regulated genes in roots and shoots with FSA were detected. Many of them were closely correlated with the tolerance to environmental stress, detoxification of xenobiotics and molecular metabolism process including cytochrome P450, glutathione S-transferases and acetyltransferase. A total of eight metabolites and fourteen conjugates in the reactive pathways of hydrolysis, substitution, reduction, methylation, glycosylation, acetylation, and malonylation were characterized by HRLC-Q-TOF-MS/MS. The relationship between the metabolized derivatives of FSA and enhanced expression the corresponding enzymatic regulators was established. This study will help understand the mechanisms and pathways of FSA metabolism and inspire the further research on FSA degradation in the paddy crops and environmental or health risks.

This is a research comment on the ochratoxin A (OTA) degradation mechanism by Lysobacter sp. CW239 regarding the previous publication in Environmental Pollution (Wei et al., 2020). Three possible degradation mechanisms were discussed in the referred publication, but without definite evidences, it was not clear which one worked actually. Here, the gene cp4 deficient mutant CW239Δᶜᵖ⁴ was successfully constructed, and the carboxypeptidase CP4 role on OTA degradation in strain CW239 was validated in vivo. As a result, the mutant CW239Δᶜᵖ⁴ without gene cp4 showed less than 10% reduction of 24 hrs degradation ratio compared to wide-type strain CW239. After the gene cp4 complemented to CW239Δᶜᵖ⁴, the complementary strain (+)cp4 recovered the degradation ability to wide-type. The validation result indicated that the third degradation mechanism (i.e., OTA is degraded by joint action of multiple enzymes in CW239) proposed previous (Wei et al., 2020) was correct route for the degradation strain. This commentary was significant to the following studies on the pollutant detoxify strains with similar degradation characters between identified enzyme and the host strain.

In this work, we prepared nanocomposites of nickel-decorated manganese oxynitride on graphene nanosheets and demonstrated them as photocatalysts for degradation of acetylsalicylic acid (ASA). The catalyst exhibited a high degradation efficiency over ASA under visible light irradiation and an excellent structural stability after multiple uses. Compared to manganese oxide (MnO) and manganese oxynitride (MnON) nanoparticles, larger specific surface area and smaller band gap were observed for the nanocomposite accounting for the enhanced photocatalytic efficiency. Besides the compositional effect of the catalyst, we also examined the influence of various experimental parameters on the degradation of ASA such as initial concentration, catalyst dose, initial pH and additives. The best performance was obtained for the nanocomposite when the catalyst dose was 10 mg/mL and the initial pH 3. Detection of intermediates during photocatalysis showed that ASA undergoes hydroxylation, demethylation, aromatization, ring opening, and finally complete mineralization into CO₂ and H₂O by reactive species. For practical applications as a photocatalyst, cytotoxicity of the nanocomposite was also evaluated, which revealed its insignificant impact on the cell viability. These results suggest the nanocomposite of nickel-decorated manganese oxynitride on graphene nanosheets as a promising photocatalyst for the remediation of ASA-contaminated water.

Bioaccumulation of environmental contaminants in mammalian predators can serve as an indicator of ecosystem health. We examined mercury concentrations of raccoons (Procyon lotor; n = 37 individuals) and striped skunks (Mephitis mephitis; n = 87 individuals) in Suisun Marsh, California, a large brackish marsh that is characterized by contiguous tracts of tidal marsh and seasonally impounded wetlands. Mean (standard error; range) total mercury concentrations in adult hair grown from 2015 to 2018 were 28.50 μg/g dw (3.05 μg/g dw; range: 4.46–81.01 μg/g dw) in raccoons and 4.85 μg/g dw (0.54 μg/g dw; range: 1.53–27.02 μg/g dw) in striped skunks. We reviewed mammalian hair mercury concentrations in the literature and raccoon mercury concentrations in Suisun Marsh were among the highest observed for wild mammals. Although striped skunk hair mercury concentrations were 83% lower than raccoons, they were higher than proposed background levels for mercury in mesopredator hair (1–5 μg/g). Hair mercury concentrations in skunks and raccoons were not related to animal size, but mercury concentrations were higher in skunks in poorer body condition. Large inter-annual differences in hair mercury concentrations suggest that methylmercury exposure to mammalian predators varied among years. Mercury concentrations of raccoon hair grown in 2017 were 2.7 times greater than hair grown in 2015, 1.7 times greater than hair grown in 2016, and 1.6 times greater than hair grown in 2018. Annual mean raccoon and skunk hair mercury concentrations increased with wetland habitat area. Furthermore, during 2017, raccoon hair mercury concentrations increased with the proportion of raccoon home ranges that was wetted habitat, as quantified using global positioning system (GPS) collars. The elevated mercury concentrations we observed in raccoons and skunks suggest that other wildlife at similar or higher trophic positions may also be exposed to elevated methylmercury bioaccumulation in brackish marshes.

The solar ultraviolet radiation (UVR) at national, provincial and county levels in Iran during 2005–2019 were determined based on Ozone Monitoring Instrument (OMI) dataset. The temporal (annual and monthly) trends and spatial distributions of the UVR in terms of erythemally weighted daily dose (EDD), erythemally weighted irradiance at local solar noon time (EDR), and UV index and the major factors influencing the spatiotemporal trends were analyzed. The population-weighted average values of EDD, EDR, and UV index in Iran were respectively 3631 J/m², 176.3 mW/m², 7.1 in 2005 and rose by 0.22% per year to 3744 J/m², 181.7 mW/m², and 7.3, respectively in 2019, but the annual trend was not statistically significant. The EDD in Iran during the study period exhibited the highest monthly average value in June (6339 J/m²) and the lowest one in December (1263 J/m²). The solar UVA/UVB ratios at the national level during 2005–2019 were considerably lower in summer. The EDD provincial average values in the study period were in the range of 2717 (Gilan) to 4424 J/m² (Fars). The spatiotemporal variations of the solar UVR parameters were well described by the linear models as a function of cloud optical thickness (COT), ozone column amount, surface albedo, latitude, and altitude (R² > 0.961, p value < 0.001) and the temporal changes of the solar UVR parameters were mainly caused by the COT. The results indicated that non-burning exposure to solar UVR in summer can be more efficient for vitamin D synthesis due to higher contribution of UVB in the solar UVR. The spatial distributions and temporal trends should be considered to determine the optimal duration, time and condition of exposure to the solar UVR for the public and occupational training and public health measures.