In response to the growing worldwide plastic pollution problem, the field of nanoplastics research is attempting to determine the risk of exposure to nanoparticles amidst their ever-increasing presence in the environment. Since little is known about the attributes of environmental nanoplastics (concentration, composition, morphology, and size) due to fundamental limitations in detection and quantification of smaller plastic particles, researchers often improvise by engineering nanoplastic particles with various surface modifications as models for laboratory toxicological testing. Polystyrene and other commercially available or easily synthesized polymer materials functionalized with surfactants or fluorophores are typically used for these studies. How surfactants, additives, fluorophores, the addition of surface functional groups for conjugation, or other changes to surface attributes alter toxicological profiles remains unclear. Additionally, the limited polymers used in laboratory models do not mimic the vast range of polymer types comprising environmental pollutants. Nanomaterials are tricky materials to investigate due to their high surface area, high surface energies, and their propensity to interact with molecules, proteins, and biological probes. These unique properties can often invalidate common laboratory assays. Extreme care must be taken to ensure that results are not artefactual. We have gathered zeta potential values for various polystyrene nanoparticles with different functionalization, in different solvents, from the reported literature. We also discuss the effects of surface engineering and solvent properties on interparticle interactions, agglomeration, particle-protein interactions, corona formation, nano-bio interfaces, and contemplate how these parameters might confound results. Various toxicological exemplars are critically reviewed, and the relevance and shortfalls of the most popular models used in nanoplastics toxicity studies published in the current literature are considered.

Biological invasions and continued salinization of freshwater are two global issues with largely serious ecological consequences. Increasing salinity in freshwater systems, as an environmental stressor, may negatively affect normal life activities in fish. It has been documented that salinity limits the invasive success of alien species by mediating physiological and life-history performances, however, there are few studies on how salinity affects its invasive process via altered behaviors. Using wild-caught invasive western mosquitofish (Gambusia affinis) as animal model, in this study, we asked whether gradual increasing salinity affects behaviors (personality and mate choice decision here), life-history traits, as well as the correlation between them by exposing G. affinis to three levels salinity (freshwater, 10 and 20‰). Results showed that, with increased salinity, male tended to be shyer, less active, less sociable, and reduced desire to mate, and female tended to be shyer, less active and lost preferences for the larger male. Furthermore, across salinity treatments, male exhibited reduced body fat content and rising reproduction allocation, however, pregnant female revealed diametrically opposed trends. In addition, the correlation between life-history traits and behaviors was only identified in pregnant female. It seems that either salinity or life-history traits directly affects mosquitofish behaviors. In summary, our results partially emphasize the harmful consequences of salinity on both life-history traits and behavioral performances. These findings provide a novel perspective on how salinity potentially affect fish fitness via altering personalities, mate choice decisions, as well as body condition, and hence supports the idea that salinity could affect the spread of invasive mosquitofish.

Atmospheric nitrogen dioxide (NO₂) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO₂ monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO₂ from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO₂ with high accuracy, with a coefficient of determination (R²) of 0.89 and a root mean squared error of 5.8 μg/m³ for sample-based 10-fold cross-validation. Based on the surface NO₂ concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO₂ pollution in north China. We found substantial drops in surface NO₂ concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO₂ exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO₂ among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO₂ concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO₂ dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

Cyanobacterial blooms producing toxic metabolites occur frequently in freshwater, yet the environmental behaviors of complex cyanobacterial metabolites remain largely unknown. In this study, the seasonal and spatial variations of several classes of cyanotoxins (microcystins, cylindrospermopsins, saxitoxins) and taste-and-odor (T&O) compounds (β-cyclocitral, β-ionone, geosmin, 2-methylisoborneol) in Lake Taihu were simultaneously investigated for the first time. The total cyanotoxins were dominated by microcystins with concentrations highest in November (mean 2209 ng/L) and lowest in February (mean 48.7 ng/L). Cylindrospermopsins were abundant in May with the highest content of 622.8 ng/L. Saxitoxins only occurred in May (mean 19.2 ng/L) and November (mean 198.5 ng/L). Extracellular T&O compounds were most concentrated in August, the highest being extracellular β-cyclocitral (mean 240.6 ng/L) followed by 2-methylisoborneol (mean 146.6 ng/L). Environment variables play conflicting roles in modulating the dynamics of different groups of cyanotoxins and T&O compounds. Total phosphorus (TP), total nitrogen (TN), chlorophyll-a and cyanobacteria density were important factors affecting the variation of total microcystins, β-cyclocitral and β-ionone concentrations. In contrast, total cylindrospermopsins, 2-methylisoborneol and geosmin concentrations were significantly influenced by water temperature and TP. There was a significant and linear relationship between microcystins and β-cyclocitral/β-ionone, while cylindrospermopsins were positively correlated with 2-methylisoborneol and geosmin. The perceptible odors may be good indicators for the existence of cyanotoxins. Hazard quotients revealed that potential human health risks from microcystins were high in August and November. Meanwhile, the risks from cylindrospermopsins were at moderate levels. Cylindrospermopsins and saxitoxins were first identified in this lake, suggesting that diverse cyanotoxins might co-occur more commonly than previously thought. Hence, the risks from other cyanotoxins beyond microcystins shouldn't be ignored. This study also highlights that the necessity for further assessing the combination effects of these complex metabolites.

Environmentally persistent free radicals (EPFRs) have aroused widespread concern due to their potential adverse health effects. Research on EPFRs in road dust is still very limited. In this study, 86 road dust samples were collected using vacuum sampling in a rapidly developing city in central China. The pollution characterization and health risk of EPFRs in the urban road dust were then systematically analyzed. The results showed the average concentrations of EPFRs in urban road dust and fraction of particle with aerodynamic diameters lower than 10 μm (PM₁₀) were 2.24 × 10¹⁷ to 3.72 × 10¹⁹ spins·g⁻¹ and 6.02 × 10¹⁷ to 1.41 × 10²⁰ spins g⁻¹, respectively. The concentrations of EPFRs in dust from expressways, arterial roads, and secondary trunk roads were significantly higher than those found in the remaining road types. The g-factors of 2.0032–2.0039 indicated that the EPFRs have consisted of oxygen-centered and carbon-centered radicals or carbon-centered radicals with nearby oxygen or halogen atoms. Moreover, three decay patterns of EPFRs were observed: a fast decay followed by a slow decay, a single slow decay, and the slowest decay. In addition, a comparative evaluation was made for probabilistic risk assessments of exposure to the EPFRs in road dust and the PM₁₀ fraction. Compared with road dust, the probability of the number of equivalent cigarettes to exceed the 100 and 200 cigarettes for inhaling EPFRs in the PM₁₀ fraction increased by 27.0% and 25.0%, respectively. The simulation results showed the PM₁₀ fraction were primarily deposited in the upper respiratory tract regions (57.1%) and pulmonary regions (28.8%). The findings of this study suggest a potential risk of EPFRs in inhalable particles and provide a new insight for further exploration of the EPFRs in fine particles of road dust.

Soil contamination with multiple heavy metals poses threats to human health and ecosystem functioning. Using the Nemerow pollution index, which considers the effects of multiple heavy metals, we compared the diversity and composition of bacteria, fungi and protists and their potential interactions in response to a multi-metal contamination gradient. Multi-metal contamination significantly altered the community composition of bacteria, fungi and protists, and the degree of alteration increased with increasing severity of contamination. The alpha-diversity of bacteria, fungi and protists significantly decreased with increasing contamination level. The dominant generalists, found in all soil samples, were Gammaproteobacteria, Chloroflexi and Bacillus sp, whereas the dominant specialists were Anaerolineaceae, Entoloma sp. and Sandonidae_X sp. The relative abundances of generalists were positively correlated, whereas those of specialists were negatively correlated, with the Nemerow pollution index. In addition, the complexity of the microbial co-occurrence network increased with increasing contamination level. Generalists, rather than specialists, were the keystones in the microbial co-occurrence network and played a crucial role in adaptation to multi-metal contamination through enhanced potential interactions within the entire microbiome. Our results provide insights into the ecological effects of multi-metal contamination on the soil microbiome and will help to develop bio-remediation technologies for contaminated soils.

Organic ultraviolet absorbents (UVAs) are increasingly reported in environmental matrices and organisms. However, available information on the bioaccumulation of UVAs in freshwater species is insufficient and their trophodynamics in lake food webs remain unknown. We measured the concentrations of twelve UVAs in the wild species from Lake Chaohu. Except for UV-320 not detected, the other UVAs were prevalent in the study species and their total concentrations were in the range of 5.44–131 ng/g dry weight, which were comparable to the concentrations reported in other waters. Compound and species-specific accumulations of UVAs in the organisms were observed. In the lake, the log-transformed concentrations of 4-methyl benzylidene camphor, octyl p-dimethylaminobenzoate, UV-326, and UV-327 related significantly to the trophic levels of species separately. The calculated trophic magnification factors (TMFs) of the four UVAs were 3.79, implying trophic magnification, and 0.18, 0.40 and 0.58, suggesting trophic dilution, respectively. These suggested that the magnification potential and the associated risks of individual UVAs in freshwater lake differed. To our knowledge, this is the first report of these TMFs in lake food webs. However, more investigation is needed to characterize their trophodynamic behaviors in lakes because food web characteristics likely affect trophic transfer of these chemicals.

Plume chasing is cost-effective, measuring individual, on-road vehicular emissions. Whereas, wake-flow-generated turbulence results in intermittent, rapid pollutant dilution and substantial fluctuating concentrations right behind the vehicle being chased. The sampling duration is therefore one of the important factors for acquiring representative (average) concentrations, which, however, has been seldom addressed. This paper, which is based on the detailed spatio-temporal dispersion data after a heavy-duty truck calculated by large-eddy simulation (LES), examines how sampling duration affects the uncertainty of the measured concentrations in plume chasing. The tailpipe dispersion is largely driven by the jet-like flows through the vehicle underbody with approximate Gaussian concentration distribution for x ≤ 0.6h, where x is the distance after the vehicle and h the characteristic vehicle size. Thereafter for x ≥ 0.6h, the major recirculation plays an important role in near-wake pollutant transport whose concentrations are highly fluctuating and positively shewed. Plume chasing for a longer sampling duration is more favourable but is logistically impractical in busy traffic. Sampling duration, also known as averaging time in the statistical analysis, thus has a crucial role in sampling accuracy. With a longer sampling (averaging) duration, the sample mean concentration converges to the population mean, improving the sample reliability. However, this effect is less pronounced in long sampling duration. The sampling accuracy is also influenced by the locations of sampling points. For the region x > 0.6h, the sampling accuracy is degraded to a large extent. As a result, acceptable sample mean is hardly achievable. Finally, frequency analysis unveils the mechanism leading to the variance in concentration measurements which is attributed to sampling duration. Those data with frequency higher than the sampling frequency are filtered out by moving average in the statistical analyses.

The popular paradigm in trophic dynamic theory is that contemporary autochthonous organic matter (e.g., phytoplankton) sustains consumer growth, whereas aged allochthonous organic matter is conceptually considered recalcitrant resources that may only be used to support consumer respiration but suppress consumer growth. This resource-age paradigm has been challenged by a growing body of recent evidence that ancient (radiocarbon depleted) organic carbon (OC) released from glaciers and permafrost can be incorporated by consumers in aquatic systems. However, little information is available regarding the food quality of ancient terrestrial OC and how it impacts the growth of consumers in lakes. Here, ancient dissolved organic carbon (DOC) was extracted from frozen soils in an alpine lake catchment. The contents of polyunsaturated fatty acids (PUFAs) in soil DOC increased significantly after bioconversion by heterotrophic bacteria. The utilization of soil DOC by heterotrophic bacteria also increased the total phosphorus concentration in the systems. Gammaproteobacteria and Betaproteobacteria showed a strong negative correlation with the percentage contents of fluorescent components, including humic-like and tyrosine-like components. Daphnia magna were fed Auxenochlorella vulgaris and ancient DOC plus heterotrophic bacteria. The contents of PUFAs and the growth of zooplankton were influenced by the pre-conversion time of ancient DOC by bacteria. When ancient DOC was pre-converted by bacteria for 27 days, D. magna fed on the mixed diets showed the highest body length (3.40 mm) and intrinsic rate of increase in population (0.49 d⁻¹). Our findings provide direct evidence that ancient terrestrial OC can be an important subsidy for lake secondary production, which have important implications for food webs in high-altitude and polar lakes.

Developing efficient catalysts for oxytetracycline (OTC) degradation is an ideal strategy to tackle environmental pollution, and advanced oxidation processes (AOPs) have been widely used for its degradation. However, the studies on the activation of periodate (PI) by biochar and its composites in recent years have been scarcely reported. In this study, we focused on the degradation of OTC by PI activation with manganese oxide/biochar composites (MnₓOy@BC). Experimental results showed that the OTC degradation rate of MnₓOy@BC/PI system reached almost 98%, and the TOC removal efficiency reached 75%. Various characteristic analysis proved that PI could be activated efficiently by surface functional groups and manganese-active species (Mn(II), Mn(III), and Mn(IV)) on biochar, and various reactive species such as singlet oxygen (¹O₂), hydroxyl radical (∙OH), and superoxide radical (O₂∙⁻) can be observed via radical quenching experiments. Based on this, three degradation pathways were proposed. Furthermore, MnₓOy@BC and PI were combined to degrade environmental pollutants, which achieved excellent practical benefits and had great practical application potential. We hope that it can provide new ideas for advanced oxidation processes (AOPs) applying for wastewater treatment in the future.