Passive samplers are useful tools for monitoring hydrophobic, persistent, and potentially bioaccumulative contaminants in the environment. In this study, low density polyethylene passive samplers were deployed in urban-influenced and background nearshore freshwaters of northwestern Lake Ontario and analyzed for a broad range of both legacy halogenated organic contaminants (HOCs) and halogenated flame retardants (HFRs). Non-targeted analysis was conducted for screening additional halogenated substances. For most compounds, concentrations were greatest in the industrialized Hamilton Harbour and more generally at sites that have stronger influences of wastewater effluent discharges and stormwater run-off through rivers and creeks. Polychlorinated biphenyls (PCBs) remain the dominant class of HOCs in water, with dissolved-phase concentrations ranging from 10 to 4100 pg/L (ΣPCBs), followed by polybrominated diphenylethers (ΣPBDEs; 14–960 pg/L) and the organochlorine pesticides (OCPs; 22–290 pg/L). Several non-PBDE brominated flame retardants (nBFRs) and chlorinated Dechlorane-related compounds were detected, with hexabromocyclododecanes (ΣHBCDD; sum of 3 diastereoisomers) the most abundant (1.0–21 pg/L). Non-targeted screening of samples by high resolution mass spectrometry using Kendrick mass defect plots for data analysis indicated that several other halogenated compounds were present in waters at relatively high abundances compared to the flame retardants, based on semi-quantitative estimates. These included methyl-triclosan, four halogenated anisoles (2,4,6-tribromoanisole, dimethyl-trichloroanisole, pentachloroanisole, and pentachlorothioanisole), and pentachloro-aniline. Dissolved-phase methyl-triclosan was estimated to contribute up to approximately 40% of the summed target HOC concentrations. Polyethylene passive samplers provided an excellent medium for both non-targeted screening of HOCs not currently included in monitoring programs and tracking brominated and chlorinated chemicals slated for reductions in uses and emissions through international (Stockholm Convention) and binational (Great Lakes) agreements.

Wildfires may play a role in redistributing radionuclides in the environment in combination with hydrological processes such as surface runoff and soil erosion. We investigated plot-scale radionuclide wash-off at forest sites affected by wildfires in the Chernobyl Exclusion Zone (CEZ). We also compared speciation of the washed-off radionuclides with those in previous studies conducted just after the accident in 1986. We observed the surface runoff and the radionuclide wash-off with a soil erosion plot at forest and post-fire sites during May–September 2018. In the post-fire site, 2.81 mm of surface runoff was observed in at least three flow events resulting from 285.8 mm total rainfall. The fluxes of dissolved and particulate ¹³⁷Cs were estimated as 4.9 and 161 Bq m⁻², respectively. The dissolved phase ⁹⁰Sr flux was estimated as 214 Bq m⁻². At the forest site, a single surface runoff (0.67 mm) event was generated by rainfall of 182.2 mm. The fluxes of dissolved and particulate ¹³⁷Cs wash-off values were 6.2 and 8.6 Bq m⁻², respectively. The flux of dissolved ⁹⁰Sr wash-off from the forest was estimated as 45.1 Bq m⁻². The distribution coefficient, which indicates the dissolved-particulate form of radionuclides, in the post-fire site was 30 times higher than that in the forest site, indicating the importance of particulate ¹³⁷Cs wash-off after fire in the CEZ. The entrainment coefficients for dissolved and particulate ¹³⁷Cs concentrations were around 50 times lower than those obtained in the corresponding position within the CEZ immediately after the accident in 1987. The effect of downward migration of ¹³⁷Cs over 30 years led to decreased entrainment coefficients for dissolved and particulate ¹³⁷Cs. The effect of downward migration of radionuclides was considered sufficient to indicate changes in normalized liquid and solid radionuclides wash-off entrainment coefficient and the distribution coefficient in this study.

Triclosan (TCS) and Triclocarbon (TCC) are chlorinated synthetic antimicrobial agents formaternal urinelated in quantities of consumer products. However, the biomonitoring of direct exposure reflection for fetuses are rare. In this study, we determine the concentrations of TCS and TCC in paired maternal serum, cord serum, maternal urine, and amniotic fluid samples collected from a cohort of 95 expecting mother-fetal pairs in Southern China. TCS and TCC are detected widely (detection rates: >76.9%) in maternal serum, cord serum, maternal urine, and amniotic fluid samples. TCS is found to be the predominant antimicrobial agent with median concentrations in maternal serum (1.5 ng/mL) and cord serum (1.8 ng/mL) that are one order of magnitude higher than those of tcc in maternal serum (0.085 ng/mL) and cord serum (0.052 ng/mL), respectively. Cord serum concentrations of tcs and tcc correlated well with the concentrations in maternal serum, which reflect the mothers’ contribution to fetal exposure. The higher median ratio of cord serum/maternal serumTCS (0.95) compared to that of cord serum/maternal serumTCC (0.53) indicates high placental transmission ability of TCS. Moreover, the facility to penetrate the placental barrier and hard to depurate characteristics lead to the long residence of TCS in the fetal environment, causing great concern over the prenatal exposure risks during the critical window of fetal development. This study provides a novel contribution by increasing existing knowledge on the exposure assessment of TCS and TCC during pregnancy through the exploration of matched maternal-fetal samples.

In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water, must satisfy certain preconditions (e.g., flat water surface and ideal radiation geometry). In this study, we hypothesized that drone-borne hyperspectral imagery of emergent plants could be better applied to retrieval total nitrogen (TN) concentration in water regardless of preconditions possibly due to the spectral responses of emergent plants on nitrogen removal and water purification. To test this hypothesis, a total of 200 groups of bootstrap samples were used to examine the relationship between the extracted TN concentrations from the drone-borne hyperspectral imagery of emergent plants and the experimentally measured TN concentrations in Ebinur Lake Oasis using four machine learning (ML) models (Partial Least Squares (PLS), Random Forest (RF), Extreme Learning Machine (ELM), and Gaussian Process (GP)). Through the introduction of the fractional order derivative (FOD), we build a decision-level fusion (DLF) model to minimize the regression results’ biases of individual ML models. For individual ML model, GP performed the best. Still, the amount of uncertainty in individual ML models renders their performance to be subpar. The introduction of the DLF model greatly minimizes the regression results’ biases. The DLF model allows to reduce potential uncertainties without sacrificing accuracy. In conclusion, the spectral response caused by nitrogen removal and water purification on emergent plants could be used to retrieve TN concentration in water with a DLF model framework. Our study offers a new perspective and a basic scientific support for water quality monitoring in arid regions.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

Monitoring studies have quantified microscopic plastic debris, so-called microplastics, in freshwater systems, including banks, surface waters and sediments. However, there is a lack of knowledge of freshwater and terrestrial environments.When microplastics are released in freshwater environments, they will be transported and will not remain stationary. Moreover, their transport from sink to source (land-based to river systems) may depend on several factors such as weather conditions and river hydrology.The present study aims to investigate the abundance and composition of microplastics in the most important river of Apulia Region (Southeast Italy) evaluating the main drivers and possible input sources of microplastic debris. The following work is the first study showing an Italian river context. For this research five sampling campaigns have been conducted west of the Ofanto river mouth. Microplastics were collected by three surface plankton nets fixed in the middle of the river in order to reduce the spatial and temporal variability. For each campaign, a total of six replicates were sampled during two time slots.Microplastic concentrations ranged from 0.9 ± 0.4 p/m³ to 13 ± 5 p/m³ showing comparable values to or greater than those ones reported in other studies. A statistically significant difference in the average microplastic concentrations in different campaigns of this study has been observed, suggesting thus a temporal variation in plastic abundances. These significant differences could be explained by the hydrology of the river that influences the particle concentration with its physical forces such as flow velocity, water level and seasonal variability. Microplastics were found at higher concentrations during wet periods indicating a land-based origin probably connected to waste produced by the surroundings agricultural areas. In fact, Spearman's correlation results show a strong positive statistically significant correlation between the concentration of microplastics and the water level (R = 0.8475, p < 0.0001).

Ochratoxin A (OTA) is a potent mycotoxin that frequently contaminates agro-products and threatens food safety. A highly efficient OTA degrading strain Lysobacter sp. CW239 was isolated, and the OTA degradation characteristics were investigated. A novel OTA degrading gene carboxypeptidase cp4 was successfully cloned and characterized from CW239. The heterologous recombinant was constructed by gene cp4 and expression vector pET-32a⁽⁺⁾ and overexpressed by E. coli BL21 CodonPlus™ (DE3). The recombinant protein rCP4 was purified, and the OTA-degrading activity was evaluated. Although OTA was efficiently degraded by CW239 (24-h degradation ratio of 86.2%), the 24-h OTA degradation ratio for rCP4 was only 36.8% at fairly high concentration (0.25 mg/mL) protein. The degraded product was obtained by immune affinity column (IAC) and determined by mass spectrometry (MS), and the degraded product was the less toxic ochratoxin α (OTα). Based on the serial investigations of this study, OTA might be simultaneously co-degraded by CP4 and another unknown degrading agent in that degrading strain.

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To characterise the mass concentration, size-distribution, and respiratory deposition of selected trace metals (Cr, Mn, Fe, Ni, Cu, Zn, Ba, and Pb) in size-segregated PM₂.₅, a long-term monitoring campaign was undertaken at an urban background site in Como (Northern Italy). 96-h aerosol samples were collected weekly, from May 2015 to March 2016, using a 13-stage low pressure impactor and analysed via laser ablation-inductively coupled plasma-mass spectrometry. Significantly higher levels of trace metals were generally found during the heating season (two to more than four times) compared to the non-heating period at all size ranges, especially for concentrations in PM₀.₁–₁. Distinct distribution profiles characterised the different elements, even though the corresponding heating and non-heating shapes always exhibited similar features, with negligible seasonal shifts in the average mass median aerodynamic diameters. Fe, Ba, and Cu had >70% of their mass in PM₁–₂.₅, whereas Pb, Zn, and Ni showed higher contributions in the accumulation mode (>60%). Finally, broad size-distributions were found for Cr and Mn. The multiple-path particle dosimetry model estimated the overall deposition fractions in human airways varying between 27% (Pb) and 48% (Ba). The greatest deposition variability was always registered in the head region of the respiratory system, with the highest contributions for those metals predominantly accumulated in the PM₂.₅ coarse modes. In contrast, the deposition in the deepest respiratory tract maintained nearly constant proportions over time, becoming notably important for Pb, Ni, and Zn (∼13%) with respect to their total deposition. The comparison with national limits established for Pb and Ni suggested the absence of significant risks for the local population, as expected, with average concentrations two orders of magnitude lower than the corresponding annual limit and objective value. Similar findings were reported for all the other metals, for which the estimated hazard quotients were always well <1.

Trichlorfon is an organic phosphorus pesticide used to control different parasitic infections in aquaculture. The repeated, excessive use of trichlorfon can result in environmental pollution, thus affecting human health. This study aimed to determine the effects of different concentrations of trichlorfon (0, 0.1, 0.5 and 1.0 mg/L) on the intestinal barrier, oxidative stress, inflammatory response and intestinal microbiome of common carp. Trichlorfon exposure significantly reduced the height of intestinal villus and decreased the expression levels of tight junction genes, such as claudin-2, occludin and ZO-1, in common carp. Moreover, the activities of antioxidant enzymes, such as CAT, SOD and GSH-Px, exhibited a decreasing trend with increasing trichlorfon concentrations, while the contents of MDA and ROS elevated in the intestinal tissues of common carp. The mRNA and protein levels of pro-inflammatory cytokines TNF-α and IL-1β were significantly upregulated by trichlorfon exposure. The level of anti-inflammatory cytokine TGF-β was remarkably higher in 1.0 mg/L trichlorfon treatment group compared to control group. In addition, the results demonstrated that trichlorfon exposure could affect the microbiota community composition and decreased the community diversity in the gut of common carp. Notably, the proportions of some probiotic bacteria, namely, Lactobacillus, Bifidobacterium and Akkermansia, were observed to be reduced after trichlorfon exposure. In summary, the findings of this study indicate that exposure to different concentrations of trichlorfon can damage intestinal barrier, induce intestinal oxidative damage, trigger inflammatory reaction and alter gut microbiota structure in common carp.