Plastic particles smaller than 1 μm are considered to be highly dangerous pollutants due to their ability to penetrate living cells. Model experiments on the toxicity of plastics should be correlated with actual concentrations of plastics in natural water. We simulated the natural destruction of polystyrene, polyvinyl chloride, and poly(methyl methacrylate) in experiments on the abrasion of plastics with small stones. The plastics were dyed in mass with a fluorescent dye, which made it possible to distinguish plastic particles from stone fragments. We found that less than 1% of polystyrene and polyvinyl chloride were converted to submicron size particles. In the case of more rigid poly(methyl methacrylate), the fraction of such particles reaches 11%. The concentration of particles with a diameter less than 1 μm in the model experiments was from 0.7 (polystyrene) to 13 mg/L (poly(methyl methacrylate)), and when transferring the obtained data to real reservoirs, these values should be reduced by several orders of magnitude. These data explain the difficulties associated with the search for nanoplastics in natural waters. The toxicity of such particles to hydrobionts in model experiments was detected for concentrations greater than 1 mg/L, which is unrealistic in nature. Detectable and toxic amounts of nano- and submicron plastic particles in living organisms can be expected only in the case of filter-feeding organisms, such as molluscs, krill, sponges, etc.

In this study, the influencing factors and sources of historical changes in polycyclic aromatic hydrocarbons (PAHs) in the sediment core of Fuxian Lake were analyzed. Before 1970, the Σ₁₆PAH concentration fluctuated widely, with one or more maximum values. During 1971–2004, the Σ₁₆PAH concentration showed a slow growth trend, while during 2005–2017, the concentration increased sharply, reaching a peak value of 821 ng g⁻¹. dw in 2017. The results of a positive matrix factorization (PMF) model demonstrated that before 1970, PAHs were mainly derived from biomass burning in the Fuxian Lake sediment core, with an overall contribution of 40 %. During 1971–2004, the source of PAHs was mainly coal combustion, with an overall contribution of 34 %. During 2005–2017, PAHs primarily originated from traffic, with an overall contribution of 33 %. Population, coal, GDP, motor, and petroleum had a significant influence on low molecular weight (LMW) PAHs in 1980–2004 and 2005–2017. Motor, coal, population, and GDP had a greater impact on high molecular weight (HMW) PAHs. Before 1970 and in 1971–2004, meteorological factors had little effect on PAHs in the sediment core in Fuxian Lake. During 2005–2017, day and rainfall were significantly negatively correlated with HMW PAHs, while temperature and wind were not correlated with PAH concentrations. During 2005–2017, total organic carbon (TOC) and total nitrogen (TN) had greater adsorption effects on HMW PAHs than on LMW PAHs. Before 1970 and in 1971–2004, the adsorption effects of TOC and TN on 3–4-ring PAHs were greater than those of 2-ring and 5–6-ring PAHs. Total phosphorus (TP) had no adsorption effect on PAHs in the entire sedimentary column.

Hybrid artificial intelligence (AI) models are developed for sediment lead (Pb) prediction in two Bays (i.e., Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) algorithm called extreme gradient boosting (XGBoost) is proposed to abstract the correlated input parameters for the Pb prediction and validated against principal component of analysis (PCA), recursive feature elimination (RFE), and the genetic algorithm (GA). XGBoost model is applied using a grid search strategy (Grid-XGBoost) for predicting Pb and validated against the commonly used AI models, artificial neural network (ANN) and support vector machine (SVM). The input parameter selection approaches redimensioned the 21 parameters into 9–5 parameters without losing their learned information over the models’ training phase. At the BB station, the mean absolute percentage error (MAPE) values (0.06, 0.32, 0.34, and 0.33) were achieved for the XGBoost–SVM, XGBoost–ANN, XGBoost–Grid-XGBoost, and Grid-XGBoost models, respectively. At the DB station, the lowest MAPE values, 0.25 and 0.24, were attained for the XGBoost–Grid-XGBoost and Grid-XGBoost models, respectively. Overall, the proposed hybrid AI models provided a reliable and robust computer aid technology for sediment Pb prediction that contribute to the best knowledge of environmental pollution monitoring and assessment.

In this work, the novel technology was used to remove heavy metal from sludge. The coupled with biodegradable ethylenediamine disuccinic acid (EDDS) and approaching anode electrokinetic (AA-EK) technique was used to enhance heavy metal removing from sludge. Electric current, sludge and electrolyte characteristics, heavy metal removal efficiency and residual content distribution, and heavy metal fractions percentage of variation were evaluated during the electrokinetic remediation process. Results demonstrated that the coupled with EDDS and AA-EK technique obtain a predominant heavy metal removal efficiency, and promote electric current increasing during the enhanced electrokinetic remediation process. The catholyte electrical conductivity was higher than the anolyte, and electrical conductivity of near the cathode sludge achieved a higher value than anode sludge during the coupled with EDDS and AA-EK remediation process. AA-EK technique can produce a great number of H⁺, which caused the sludge acidification and pH decrease. Cu, Zn, Cr, Pb, Ni and Mn obtain the highest extraction efficiency after the coupled with EDDS and AA-EK remediation, which were 52.2 ± 2.57%, 56.8 ± 3.62%, 60.4 ± 3.62%, 47.2 ± 2.35%, 53.0 ± 3.48%, 54.2 ± 3.43%, respectively. Also, heavy metal fractions analysis demonstrated that the oxidizable fraction percentage decreased slowly after the coupled with EDDS and AA-EK remediation.

Hexafluoropropylene oxide dimer acid (HFPO-DA) is a perfluorooctanoic acid (PFOA) substitute. In the current study, potential developmental cardiotoxicity and hepatotoxicity following HFPO-DA exposure in chicken embryo has been investigated, focusing on the roles of peroxisome proliferator activated receptor alpha (PPARα), the major molecular target in PFOA-induced toxicities. HFPO-DA was exposed to fertile chicken eggs via air cell injection, morphology and function of the target organs (heart and liver) in hatchlings were investigated with histopathology and electrocardiography, and the serum levels of HFPO-DA had been measured with quadrupole-time of flight liquid chromatograph-mass spectrometer (Q-TOF LC/MS). Additionally, lentivirus-mediated in ovo PPARα silencing was used to assess the roles of PPARα in HFPO-DA induced developmental toxicities. The results indicated that developmental exposure to HFPO-DA induced developmental cardiotoxicity, including thinned right ventricular wall and elevated heart rates, similar to those observed with PFOA exposure, as well as developmental hepatotoxicity in the form of steatosis. Silencing of PPARα alleviated such effects, suggesting participation of PPARα in HFPO-DA induced developmental toxicities in chicken embryo. Moreover, enhanced expression of PPARα downstream genes, cluster of differentiation 36 (CD36) and enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase (EHHADH), were observed in HFPO-DA exposed animal heart tissues, which can be abolished by PPARα silencing. On the other hand, liver-type fatty acid binding protein (L-FABP) and CD36 expression were effectively enhanced in exposed liver tissues, but not EHHADH, suggesting differential mechanism of toxicity in heart and liver tissues. In summary, developmental exposure to HFPO-DA induced developmental cardiotoxicity and hepatotoxicity in hatchling chickens similar to PFOA, and PPARα still participates in such toxicities, with some differential downstream gene regulations in different organs. Further investigation on HFPO-DA-induced developmental toxicities is guaranteed.

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.

Precious metal mining activities have left complex environmental legacies in lakes around the world, including some sites in climatically sensitive regions of the Canadian sub-Arctic. Here, we examined the long-term impacts of past regional gold mining activities on sub-Arctic lakes near Con Mine (Yellowknife, Northwest Territories) based on sediment core analysis (paleolimnology). In addition to receiving metal(loid)s from roaster stack emissions, the study lakes were also influenced by salt-rich mine drainage from Con Mine tailings. Water samples from these lakes had some of the highest concentrations for salinity-related variables (e.g. Ca²⁺, Cl⁻, Na⁺) and metal(loid)s (e.g. As, Cu, Ni, Sb) in the Yellowknife area. Furthermore, the presence of halophilic diatom (Bacillariophyceae) taxa (Achnanthes thermalis and Navicula incertata) in the recent sediments of Keg and Peg lakes suggest that the extreme saline conditions are strongly influencing the present biota, more than 10 years after the cessation of gold mining activities at Con Mine. The sedimentary metal(loid) profiles (e.g. As, Cu, Ni) of Kam Lake tracked the influence of regional gold mining activities, particularly those at Con Mine, while the algal assemblages recorded the biological responses to salinization and metal(loid) pollution (e.g. marked decreases in diatom species richness, Hill’s N2 diversity, and chrysophyte cyst:diatom valve ratio). At Kam Lake, the algal assemblage changes in the post-mining era were indicative of climate-mediated changes to lake thermal properties (e.g. rise in planktonic diatoms), nutrient enrichment related to urbanization (e.g. increase in eutrophic Stephanodisucs taxa), and/or a combination of both stressors. The lack of biological recovery (i.e. return to pre-mining assemblages) is consistent with investigations of mine-impacted lakes in temperate regions where elevated contaminant levels and emerging stressors (e.g. climate warming, land-use changes) are influencing lake recovery.

Previous studies have developed a stable weather index (SWI) based on meteorological elements that adequately represent PM₂.₅ pollution over the North China Plain (NCP). However, the SWI performs poorly over the Yangtze River Delta (YRD) region because air pollution over this region is affected not only by stagnant weather (STAG) but also by transport (TRANS). For example, air pollutants can be transported from the NCP to the YRD by cold fronts. In this study, an obliquely rotated principal component analysis in the T-model is applied to classify the synoptic patterns of winter weather over the YRD region from 2013 to 2018. Among the four identified synoptic patterns, two of which cause TRANS, one pattern is most likely to cause STAG, and one pattern can lead to either STAG or TRANS depending on the location of high pressure around Shandong province. Due to the large contribution (63%) of TRANS to the total PM₂.₅ pollution events, a transport pollution index (TPI) is constructed to describe the transport features of PM₂.₅ pollution over the YRD region. Our results show that, when considering the SWI alone, the correlation coefficients between the SWI and ln(PM₂.₅) range from 0.50 to 0.57 in the main cities of the YRD. Excitingly, when considering both the TPI and SWI (TPI+SWI), the correlation coefficients increase significantly to 0.63–0.78, suggesting that TPI+SWI better reflects the wintertime PM₂.₅ pollution level over the YRD region. In addition, satisfactory performance in validation also suggests that TPI+SWI can increase the accuracy of evaluating and forecasting of PM₂.₅ pollution episodes over regions downstream of source emissions.

Due to the endocrine disrupting effects of bisphenol A (BPA) several governmental authorities have banned its use and the manufacturers had to find alternative substances with similar chemical properties. This led to the increase in the use of so-called BPA analogues, which however also turn out to possess mild estrogenic and ani-androgenic properties and thus, may cause fertility problems and sex-hormone dependent endocrinopathies. The aim of this study was to evaluate the potential association between the exposure to BPA and its two analogues: BPS and BPF, with the diagnosis of the polycystic ovary syndrome (PCOS), which remains the most common female endocrinopathy. Serum concentrations of BPA, BPS and BPF were measured using high performance liquid chromatography method with tandem mass spectrometry (HPLC-MS/MS) among 199 women with PCOS and 158 control subjects. In women with PCOS serum BPS concentrations were significantly higher compared to the control subjects (geometric mean [95% CI]: 0.14 ng/mL [0.10; 1.17] vs. 0.08 ng/mL [0.06; 0.09], P = 0.023). Serum BPA and BPF concentrations did not differ between the studied groups. There was however a negative correlation between serum BPA and HOMA-IR (r = − 0.233, P = 0.001) and TST (r = − 0.203, P = 0.006) in women with PCOS. No correlations were found between the serum BPs and other metabolic parameters such as serum lipids, insulin, DHEA-S, androstenedione and FAI. When studying the association between serum BPA analogues and PCOS it turned out that women whose serum BPS concentrations were in the first tertile were more likely to be diagnosed with this endocrinopathy (OR [95% CI]: 1.21 [1.04; 3.46], P = 0.017). This association was also statistically significant when adjusted for age, education, BMI, smoking, income, and alcohol consumption (adjusted OR [95% CI]: 1.12 [1.03; 3.71], P = 0.029). These results point to the potential association between the exposure to BPS and the diagnosis of PCOS. The role of BPA is not clear and warrants further studies.

Microplastics are emerging contaminants and widely distributed in the environment. They are considered as a vector of numerous organic pollutants including antibiotics in aquatic environments and thereby influence their distribution and transport behaviors. However, the effects of microplastics on the environmental behavior of antibiotics in soils remain largely unclear. In this paper, the influence of polyamide (PA) microplastics on sorption and transport of the selected antibiotic [oxytetracycline (OTC)] in a sandy loamy soil was studied by performing batch and column experiments. Results show that PA microplastics increase the pH of reaction systems, which contributes to OTC sorption onto the tested soils. However, altering pH is not the key influencing mechanism because the overall sorption capacity decreases slightly after adding PA microplastics, which can be attributed to the dilution effect. Reduction of OTC sorption by adding microplastics promotes the migration of OTC in the tested soil, which could be demonstrated by the results of column experiments that the breakthrough of OTC occurs earlier with an increasing content of PA microplastics. According to the fitting parameters of HYDRUS−1D model, PA microplastics can affect the transport of OTC by altering the soil pore structure and dispersion coefficient. These results provide new insight into the interaction between microplastics and organic pollutants in soil environments.