Although biochar supports were widely adopted to fabricate the biochar (BC) supported layered double hydroxides (LDHs) composites (LDH-BC) for efficient environmental remediation, few studies focus on the important role of biochar support in alleviating the stacking of LDHs and enhancing LDH-BC's performance. Through the analysis of the material structure-performance relationship, the “support effect” of fine biochar prepared by ball milling was carefully explored. Compared with the original LDHs on LDH-BC, the LDHs on ball milled biochar (LDH-BMBC) had smaller particle size (from 1123 nm to 586 nm), crystallite size (from 20.5 nm to 6.56 nm), more abundant O-containing functional groups, and larger surface area (370 m² g⁻¹) and porous structure. The Langmuir model revealed that the maximum theoretical phosphate adsorption capacity of LDH-BMBC (56.2 mg P g⁻¹) was significantly higher than that of LDH-BC (27.6 mg P g⁻¹). The leaching experiment proved that the addition of LDH-BMBC in calcareous soil could significantly reduce the release of soil total phosphate (46.1%) and molybdate reactive phosphate (40.4%), even though pristine BC and BMBC significantly enhanced the soil phosphate leaching. This work fabricated high-performance and eco-friendly LDH-BMBC for phosphate adsorption in solution and phosphate retention in soil and also provide valuable insights into fine biochar support effect on LDHs exfoliation, extending the practical use of the engineered ball milled biochars in environment remediation.

Endocrine-disrupting chemicals (EDCs) are ubiquitous in daily life, but their harmful effects on the human body have not been fully explored. Recent studies have shown that EDCs exposure could lead to infertility, menstrual disorder and menopause, resulting in subsequent effects on female health. Therefore, it is of great significance to clarify and summarize the impacts of EDCs on ovarian aging for explaining the etiology of ovarian aging and maintaining female reproductive health. Here in this review, we focused on the impacts of ten typical environmental contaminants on the progression of ovarian aging during adult exposure, including epidemiological data in humans and experimental models in rodents, with their clinical phenotypes and underlying mechanisms. We found that both persistent (polychlorinated biphenyls, perfluoroalkyl and polyfluoroalkyl substances) and non-persistent (phthalates) EDCs exposure could increase an overall risk of ovarian aging, leading to the diminish of ovarian reserve, decline of fertility or fecundity, irregularity of the menstrual cycle and an earlier age at menopause, and/or premature ovarian insufficiency/failure in epidemiological studies. Among these, the loss of follicles can also be validated in experimental studies of some EDCs, such as BPA, phthalates, parabens and PCBs. The underlying mechanisms may involve the impaired ovarian follicular development by altering receptor-mediated pro-apoptotic pathways, inducing signal transduction and cell cycle arrest and epigenetic modification. However, there were inconsistent results in the impacts on fertility/fecundity, menstrual/estrous cycle and hormone changes response to different EDCs, and differences between human and animal studies. Our review summarizes the current state of knowledge on ovarian disrupters, highlights their risks to ovarian aging and identifies knowledge gaps in humans and animals. We therefore propose that females adopt healthy lifestyle changes to minimize their exposure to both persistent and non-persistent chemicals, that have the potential damage to their reproductive function.

Assessments of antimony (Sb) and arsenic (As) contamination in sediments are reported on a wide range of different particle size fractions, including <63 μm, < 180 μm and <2 mm. Guidelines vary between jurisdictions which limits comparative assessment between contamination events and complicates ecotoxicity assessment, and almost no information exists on Sb size distribution in contaminated sediments. This study quantified and compared the size distribution of Sb and As in 11 sediments (and 2 floodplain soils) collected along 320 km of waterway contaminated by historic mining activity. Sediment particle size distribution was the primary determinant of total metalloid load in size fractions across the varying substrates of the waterway. Minerals and sorption complexes influenced metalloid particle distribution but relative importance depended on location. Arsenic concentrations were greatest in the fine <63 μm fraction across all the different river environments (7.3–189 mg kg⁻¹, or 1–26% of total sample As), attributed to fine-grained primary arsenopyrite and/or sorption of As(V) to fine solid-phases. The Sb particle size concentrations were greatest in mid-size fractions (205–903 mg kg⁻¹) in the upper catchment and up to 100 km downstream to the mid-catchment as a result of remnant Sb minerals. Antimony concentrations in the lower catchment were greatest in the <63 μm fraction (8.8–12.1 mg kg⁻¹), reflecting the increasing importance of sorption for Sb particle associations. This work demonstrates the importance of particle size analysed for assessment of sediment quality, and provides support for analysis of at least the <250 μm fraction for Sb and As when comparing pollutant distribution in events impacted by primary contamination. Analysis of the <63 μm fraction, however, provides good representation in well-dispersed contaminated sediments.

The fate and behavior of radioactive cesium (Cs) in the water environment are of great concern. The involvement of bacteria regarding their accumulation capability for this element is the most fundamental factor that needs to be clarified even for exploring the interactions between many environmental factors that involve together in governing the transport and distribution of Cs. As the first systematical study that aimed to evaluate the accumulation capability of environmental bacteria for Cs, bacteria in the sediment of a freshwater reservoir and coastal water environment were isolated and multiplied for contact experiment with Cs under different temperature conditions (5, 25, and 35 °C). The accumulation concentration of Cs in bacteria from freshwater sediment varied in 3.95 × 10⁻⁶ to 5.68 × 10⁻⁴ng-Cs/cell, and that from coastal sediment in 1.52 × 10⁻⁶ to 7.41 × 10⁻⁴ng-Cs/cell, indicating obvious differences among bacterial species. Bacteria of coastal sediment possessed higher accumulation capability for Cs than bacteria from freshwater sediment, and temperature dependency was confirmed for bacteria from coastal sediment. The findings of this study have great reference value for better understanding and controlling the fate and behavior of radioactive Cs associated with bacteria in the water environment.

Catalytic pyrolysis is a promising chemical recycling technology to supplement mechanical recycling since plastics can be broken down into monomers or converted to the required fuels and chemicals. In this study, a microwave (MW) -responsive SiC foam@zeoltie core-shell structured catalyst was proposed for the catalytic pyrolysis of polyolefins. Under microwave irradiation, the SiC foam core works as both microwave adsorber and catalyst support, thus concentrating the generated heat energy on the ZSM-5 zeolite shell, where the catalytic reaction takes place. SiC foam with an open cellular structure can also improve the global transport of mass and heat during plastics pyrolysis. In this work, the effects of the SiO₂/Al₂O₃ ratio and alkaline treatment of ZSM-5 zeolite coated SiC foam under MW irradiation on the variations in product distribution from low-density polyethylene (LDPE) pyrolysis were investigated at 450 °C. The results indicated that the appropriate acidity and pore structure were crucial to upgrading gas and liquid products. Particularly, the creation of a mesoporous structure in ZSM-5 zeolite via alkaline treatment could improve the diffusion of large molecules and products, thus significantly increasing the selectivity of high-valued light olefins and aromatics while inhibiting the formation of unwanted alkanes, which are expected in the chemical industry. Concretely, the concentration of olefins in gas increased to 51.0 vol% for ZSM-5(50)-0.25AT, and 65.6 vol% for ZSM-5 (50)-0.50AT, compared with 45.2 vol% for the parent ZSM-5(50). The relative concentration of aromatics in liquid decreased from 96.6% for ZSM-5(50) to 75.9% for ZSM-5(50)-0.25AT, and 71.1% for ZSM-5(50)-0.50AT. Given the respective yield of gas and liquid, the total selectivity of C2–C4 olefins and aromatics for mesoporous ZSM-5 zeolites could reach 58.6–64.9% during LDPE pyrolysis, which were higher than that for the parent ZSM-5 zeolite.

The plasticizer di(2-ethylhexyl) phthalate (DEHP) is frequently detected in the environment due to the abundance of its use. These levels might be hazardous to human health and ecosystems. Phthalates have been associated with neurological disorders, yet whether chronic DEHP exposure plays a role in Parkinson's disease (PD) or its underlying mechanisms is unknown. We investigated the effects of chronic DEHP exposure less than an environmentally-relevant dose on PD hallmarks, using Caenorhabditis elegans as a model. We show that developmental stage and exposure timing influence DEHP-induced dopaminergic neuron degeneration. In addition, in response to chronic DEHP exposure at 5 mg/L, mitochondrial fragmentation became significantly elevated, reactive oxygen species (ROS) levels increased, and ATP levels decreased, suggesting that mitochondrial dysfunction occurs. Furthermore, the data show that mitochondrial complex I (nuo-1 and gas-1) and complex II (mev-1) are involved in DEHP-induced dopaminergic neuron toxicity. These results suggest that chronic exposure to DEHP at levels less than an environmentally-relevant dose causes dopaminergic neuron degeneration through mitochondrial dysfunction involving mitochondrial complex I and II. Considering the high level of genetic conservation between C. elegans and mammals, chronic DEHP exposure might elevate the risk of developing PD in humans.

Phytoextraction using hyperaccumulator, Pteris vittata, to extract arsenic (As) from soil has been applied to large areas to achieve an As removal rate of 18% per year. However, remarkable difference among different studies and field practices has led to difficulties in the standardization of phytoextraction technology. In this study, data on As concentration in P. vittata and related environmental conditions were collected through literature search. A conceptual framework was proposed to guide the improvement of phytoextraction efficiency in the field. The following influencing factors of As concentration in this hyperaccumulator were identified: total As concentration in soil, soil available As, organic matter in soil, total potassium (K) concentration in soil, and annual rainfall. The geodetection results show that the main factors that affect As concentration in P. vittata include soil organic matter (q = 0.75), soil available As (q = 0.67), total K (q = 0.54), and rainfall (q = 0.42). The predictive models of As concentration in P. vittata were established separately for greenhouse and field conditions through multivariate linear stepwise regression method. Under greenhouse condition, soil available As was the most important influencing factor and could explain 41.4% of As concentration in P. vittata. Two dominant factors were detected in the field: soil available As concentration and average annual rainfall. The combination of these two factors gave better prediction results with R² = 0.762. The establishment of the model might help predict phytoextraction efficiency and contribute to technological standardization. The strategies that were used to promote As removal from soil by P. vittata were summarized and analyzed. Intercropping with suitable plants or a combination of different measures (e.g., phosphate fertilizer and water retention) was recommended in practice to increase As concentration in P. vittata.

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013–2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.

Exposure of Bisphenol A (BPA) is closely associated with an increased prevalence of obesity-related metabolic syndrome. However, the potential mechanism of BPA-induced adipogenesis remains to be fully elucidated. Herein, potential mechanisms of BPA-induced adipogenesis in 3T3-L1 preadipocytes were evaluated using RNA-Seq. Then, using an early-life BPA exposure model, we further evaluated the effects of BPA exposure on lipid and glucose homeostasis. The results showed that lipid content in 3T3-L1 adipocytes was significantly increased after BPA exposure (p < 0.01) and male C57BL/6 mice with the dose of 500 μg/kg/day BPA by once-a-day oral administration for 8 weeks displayed a NAFLD-like phenotype. RNA-Seq analysis of preadipocytes showed that BPA exposure affected multiple biological processes including glycosphingolipid biosynthesis, regulation of lipolysis in adipocytes, PPAR signaling pathway and fatty acid metabolism. The dysregulation in a series of genes of mice was associated to de novo lipogenesis and lipid transport, which was linked to obesity. Importantly, we also found a significant expression increase of stearoyl-CoA desaturase 1 (SCD1) and a significant decrease of apolipoprotein D (APOD) in both fat (p < 0.01) and livers (p < 0.01) of male mice. Besides, the dysregulation of pro-inflammatory genes (TNF-α,IL-6 and SAA3) showed that BPA exposure promoted progression of hepatic inflammation. In conclusion, this study elucidated a novel mechanism in which obesity associated with BPA exposure by targeting SCD1. Exposure to BPA should be carefully examined in the chronic liver metabolic diseases.

Aquifer vulnerability mapping to pollution is topical research activity, and common frameworks such as the basic DRASTIC framework (BDF) suffer from the inherent subjectivity. This paper formulates an artificial intelligence modeling strategy based on Convolutional Neural Network (CNN) to decrease subjectivity. This formulation considers three definitions of intrinsic, specific, and total vulnerabilities. Accordingly, three CNN models are trained and tested to calculate IVI, SVI, and TVI, respectively referring to the intrinsic, specific, and total vulnerability indices. The formulation is applied in an unconfined aquifer northwest of Iran and delineates hotspots within the aquifer. The area under curve (AUC) values derived by the receiver operating curves evaluate the vulnerability indices versus nitrate concentrations. The AUC values for BDF, IVI, SVI, and TVI are 0.81, 0.91, 0.95, and 0.95, respectively. Therefore, CNNs significantly improve the results compared to BDF, but IVI, SVI, and TVI have approximately identical performances. However, the visual comparison between their results provides evidence that significant differences exist between the spatial patterns despite identical AUC values.