The Fuyang River system (FRS) in north China, for a long time, is seriously polluted with organic compounds and heavy metals due to industrialization. However, the information on heavy metal pollution in this area is still limited, and health risks raised by trace elements are neglected up to now. To characterize the heavy metal pollutants and assess their potential ecological risks scientifically in FRS, surface sediments were collected from 66 sampling sites selected according to the hydrological and anthropogenic conditions along the river. A total of twelve metal pollutants (e.g., Cr, As, and Hg) in the sediments were detected among the distributaries. A combining application of geoaccumulation index (Igₑₒ), ratio of secondary phase and primary phase (RSP), and the ecological risk factor (Erⁱ) in this study gave systematic assessment results of single or combined pollution status raised by heavy metals in this area. The results show that Cr, Ni, Cu, As, Cd, Co, and Sn are mainly dispersed in the river reaches of Xingtai City and pose potential health risks in midstream, as per the geoaccumulation index and Pearson’s correlation analyses. In particular, Cd accumulates strongly in sediments of Ming River and Aixinzhuang dam from Xingtai City. In upstream and downstream of FRS, the potential ecological risk is low, except in Yongnian County where high ecological risk was caused by Cd and Hg. These findings provide new insights into the pollution characteristics and assessment of the potential ecological risks induced by heavy metals along FRS, which suggest new directions should strategically tend to typical pollutants control by policy formulation and taking effective measures to prevent and manage heavy metal pollution in North China.

Ballast water transport is considered as one of the major vectors for dispersal of microplastics around the global oceans. In this commentary, a simple, inexpensive solution has been proposed to reduce microplastic pollution and its mobility via ballast water. A screening chamber (with stainless steel three layered mesh) is proposed to be attached to the existing Ballast Water Treatment Systems (BWTSs) in cargo ships to filter back-flushed sea water from BWTSs. The three layered screens (500, 300 and 100 μm) will not only avoid clogging and easy separation of different size groups of microplastic particles but also help in smooth discharge of water to the sea. This technique is expected to remove a large number of microplastic particles (ranging from 0.0015 to 1020 million) from a single voyage. The proposed chamber may help to collect 0.0003–204 metric tons of particles/day, depending upon the geographical location of ballast intake in the global ocean. These estimations were made by considering a daily turnover of 0.033 billion tonnes of ballast water globally. This proposed screening chamber attached to the existing BWTSs in cargo ships, along with other region-specific ocean cleaning initiatives, will help in mitigating microplastic pollution in the global ocean.

Plastic mulching and straw incorporation are common agricultural practices in China. Plastic mulching is suspected to be a significant source of microplastics in terrestrial environments. Straw incorporation has many effects on the storage of soil organic carbon (SOC) and greenhouse gas emissions, but these effects have not been studied in the presence of microplastic pollution. In this study, 365-day soil incubation experiments were conducted to assess the effects of maize straw and polyethylene microplastics on SOC fractions and carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions in two different soils (fluvo-aquic and latosol). Against the background of straw incorporation, microplastics reduced the mineralization and decomposition of SOC, resulting in a microbially available SOC content decrease by 18.9%. In addition, microplastics were carbon-rich, but relatively stable and difficult to be used by microorganisms, thus increasing the mineral-associated SOC content by 52.5%. This indicated that microplastics had adverse effects on microbially available SOC and positive effects on mineral-associated SOC. Microplastics also decreased coarse particulate SOC (>250 μm), and increased non-aggregated silt and clay aggregated SOC (<53 μm). Furthermore, microplastics changed microbial community compositions, thereby reducing the CO₂ and N₂O emissions of straw incorporation by 26.5%–33.9% and 35.4%–39.7%, respectively. These results showed that microplastics partially offset the increase of CO₂ and N₂O emissions induced by straw incorporation. Additionally, the inhibitory effect of microplastics on CO₂ emissions in fluvo-aquic soil was lower than that in latosol soil, whereas the inhibitory effect on N₂O emissions had the opposite trend.

Silver nanomaterials (AgNMs) are broadly used and among the most studied nanomaterials. The underlying molecular mechanisms (e.g. protein and metabolite response) that precede phenotypical effects have been assessed to a much lesser extent. In this paper, we assess differentially expressed proteins (DEPs) and metabolites (DEMs) by high-throughput (HTP) techniques (HPLC-MS/MS with tandem mass tags, reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC) with mass spectrometric detection). In a time series (0, 7, 14 days), the standard soil model Enchytraeus crypticus was exposed to AgNM300K and AgNO₃ at the reproduction EC20 and EC50. The impact on proteins/metabolites was clearly larger after 14 days. NM300K caused more upregulated DEPs/DEMs, more so at the EC20, whereas AgNO₃ caused a dose response increase of DEPs/DEMs. Similar pathways were activated, although often via opposite regulation (up vs down) of DEPs, hence, dissimilar mechanisms underlie the apical observed impact. Affected pathways included e.g. energy and lipid metabolism and oxidative stress. Uniquely affected by AgNO₃ was catalase, malate dehydrogenase and ATP-citrate synthase, and heat shock proteins (HSP70) and ferritin were affected by AgNM300K. The gene expression-based data in Adverse Outcome Pathway was confirmed and additional key events added, e.g. regulation of catalase and heat shock proteins were confirmed to be included. Finally, we observed (as we have seen before) that lower concentration of the NM caused higher biological impact. Data was deposited to ProteomeXchange, identifier PXD024444.

Pollutant emissions in ship exhaust have been continually increasing. SO₂ is one of the main gaseous pollutants in ship exhaust, resulting from the use of marine heavy fuel oil with high sulfur content. Therefore, it is necessary to detect the fuel sulfur content (FSC) to regulate ship exhaust emissions. Optical remote sensing methods, such as differential optical absorption spectroscopy (DOAS), light detection and ranging (LIDAR), and ultraviolet (UV) camera techniques, are regarded as simple and effective remote monitoring methods. One common technique is to estimate the SO₂ concentration in a ship plume using its local optical characteristics and use this to calculate FSC. One drawback of this technique is that there are always errors in the estimations of the SO₂ concentration despite the continuous improvement of such estimations. Another drawback is that calculating FSC from SO₂ often requires additional measurement methods. Here, a sulfur content prediction model based on a deep convolutional neural network using a UV camera is introduced. First, a ship benchmark test is performed. In the test, a large number of ultraviolet characteristic images of the ship exhaust plume are taken with a UV camera and the corresponding FSC data are collected. Next, a visual geometry group (VGG)-16 convolutional neural network model based on transfer learning is built. The model extracts all the features of the exhaust plume image as input data to the deep neural network and outputs the predicted FSC as a classification label. The results show that the model can predict the FSC value with high accuracy corresponding to the exhaust plume image. This study proves that it is theoretically feasible to apply a convolutional neural network to learn features of ultraviolet ship exhaust plume images for FSC predictions, which can provide guidance for the remote regulation of ship exhaust emissions.

Trace organic compounds (TOrCs) and microplastics (MPs) have been recognized as emerging pollutants that cause severe water pollution related problems due to their non-degradable and bio-accumulative nature. Many studies on oxidation processes such as ozone have been conducted to efficiently remove TOrCs in water treatment. However, there has been a lack of research on the removal efficiency of TOrCs in the oxidation process when they co-exist with MPs and form transformation byproducts (TBPs) during this process. This study evaluates the effects of MPs on TOrC removal during ozonation at various ozone concentrations and based on the mass of MP particles in distilled water. The adsorption of TBPs and TOrCs was also evaluated using the Freundlich and Langmuir isotherm equations. The toxicity of these compounds was evaluated to confirm the risk to aquatic ecosystems. The results show that triclosan (TCS) had the highest absorption capacity amongst the TOrCs and TBPs tested. Polyvinylchloride exhibited the highest adsorption efficiency compared with polyethylene and polyethyleneterephthalate (TCS 0.341 mg/g) due to its high adsorption capacity and hydrophobicity. In the toxicity test, 2,4-dichlorophenol and 4-chloroaniline as TBPs had a relatively higher toxicity to Vibrio fischeri (a marine bacterial species) than Daphnia magna (a freshwater plankton species).

Environmental pollution is a widespread problem, which has seriously threatened human health and led to an increase of human diseases. Therefore, it is critical to evaluate environmental pollutants quickly and efficiently. Because of obvious inter-species differences between animals and humans, and lack of physiologically-relevant microenvironment, animal models and in vitro two-dimensional (2D) models can not accurately describe toxicological effects and predicting actual in vivo responses. To make up the limitations of conventional environmental toxicology screening, organ-on-a-chip (OOC) systems are increasingly developing. OOC systems can provide a well-organized architecture with comparable to the complex microenvironment in vivo and generate realistic responses to environmental pollutants. The feasibility, adjustability and reliability of OCC systems make it possible to offer new opportunities for environmental pollutants screening, which can study their metabolism, collective response, and fate in vivo. Further progress can address the challenges to make OCC systems better investigate and evaluate environmental pollutants with high predictive power.

Piscivorous avian species may be affected by mercury (Hg) which tends to accumulate in aquatic environments and biomagnifies across the food webs. One of such species is the black stork, whose population increase recently slowed down due to unknown reasons. At the same time Hg contamination and its effects were almost unaudited for this species, so it may have exerted deleterious effects on the population and an evaluation is necessary. This is the first study of this species concerning Hg contamination. Thus, Hg concentrations were investigated in the down of black stork chicks (N = 90) from breeding locations in central and southern Poland (Europe) between 2015 and 2017. As well as Hg levels, morphometric parameters and age were evaluated. Mean Hg concentrations reached 0.7 μg/g d.w. and differed significantly between years, from the lowest value noted in 2017 (mean 0.5 μg/g), through 2016 (0.7 μg/g), to the highest one in 2015 (0.9 μg/g), and between nest locations where higher Hg levels were generally found in northern parts of the study area. Hg concentrations were also unrelated to morphometric parameters. Contrarily, morphometric parameters revealed high correlations between themselves, which was confirmed by the cluster analysis (revealing only two clusters) and principal component analysis (the first PC explained 96.8% of the variance). Hg levels in the down of black storks were rather low with the fluctuation between years and nest locations probably caused by parental exposure during wintering, migration, pre-breeding season and recent exposure through food provided by parents. Such low Hg concentrations seemed not to affect the population from the region studied.

Individuals with metabolic disorders exhibit enhanced susceptibility to the cardiovascular health effects of particulate air pollution, but the underlying mechanisms are not yet understood. We aim to assess whether changes in proinflammatory lipid signals are associated with fine particulate matter (PM₂.₅) exposure in individuals with and without prediabetes. A longitudinal panel study was conducted in Beijing, China, and included 120 participants followed up over 589 clinical visits from August 2013 to February 2015. We measured 12 lipids derived from arachidonic acid pathways in blood samples of the participants via targeted lipidomic analyses. Ambient PM₂.₅ concentrations were continuously monitored at a station for associations with the lipids. Among the 120 participants, 110 (mean [SD] age at recruitment, 56.5 [4.2] years; 31 prediabetics) who visited the clinic at least twice over the follow-up period were assigned exposure values of the outdoor residential PM₂.₅ concentrations during the 1–14 days preceding each clinical visit. With an interquartile range increase in the 1-day-lag PM₂.₅ exposure (64.0 μg/m³), the prediabetic group had consistently greater increases in the concentration of arachidonate metabolites derived from the cytochrome P450 (CYP450) pathway (5,6-DHET, 15.8% [95% CI, 3.5–29.7%]; 8,9-DHET, 9.7% [95% CI, 0.6–19.6%]; 11,12-DHET, 8.3% [95% CI, 1.9–15.1%]; 14,15-DHET, 7.4% [95% CI, 0.9–14.4%]; and 20-HETE, 8.9% [95% CI, 1.0–17.5%]), compared with the healthy group. Among CYP450-derived lipids, 14,15-DHET and 20-HETE significantly mediated 8% and 8% of the PM₂.₅-associated increase in white blood cells, 10% and 13% of that in neutrophils, and 20% and 23% of that in monocytes, respectively, in the prediabetic group. In conclusion, proinflammatory lipid signals from CYP450 pathways triggered the health effects of particulate air pollution in individuals with prediabetes, suggesting that targeting lipid metabolism has therapeutic potential to attenuate or prevent the cardiovascular effects of air pollution in susceptible populations.