Infectious diseases of humans and wildlife are increasing globally but the contribution of novel artificial anthropogenic entities such as nano-sized plastics to disease dynamics remains unknown. Despite mounting evidence for the adverse effects of nanoplastics (NPs) on single organisms, it is unclear whether and how they affect the interaction between species and thereby lead to ecological harm. In order to incorporate the impact of NP pollution into host-parasite-environment interactions captured in the “disease triangle”, we evaluated disease outcomes in the presence of polystyrene NP using an ecologically-relevant host-parasite system consisting of a common planktonic cyanobacterium and its fungal parasite. NP at high concentrations formed hetero-aggregates with phytoplankton and inhibited their growth. This coincided with a significant reduction in infection prevalence, highlighting the close interdependency of host and parasite fitness. Lower intensity of infection in the presence of NP indicates that reduced disease transmission results from the parasite’s diminished ability to establish new infections as NP formed aggregates around phytoplankton cells. We propose that NP aggregation on the host’s surface acts as a physical barrier to infection and, by reducing host light harvesting, may also hamper parasite chemotaxis. These results demonstrate that the consequences of NP pollution go well beyond toxic effects at the individual level and modulate the intensity of species interactions, thereby potentially eliciting diverse cascading effects on ecosystem functioning.

Japan receives nitrogenous air pollutants via long-range transport from China. However, emissions of nitrogenous air pollutants in China have stabilized or decreased in recent years. This study examined both the long-term trends in atmospheric nitrogen (N) deposition from the 1990s to the 2010s and the response of stream water nitrate (NO₃⁻) leaching from forested areas in western Japan. A long-term (1992–2018) temporal analysis of atmospheric N deposition in Fukuoka (western Japan) was conducted. Atmospheric bulk N deposition was collected at forested sites in a suburban forest (Swₑₛₜ) and a rural forest (Rwₑₛₜ) in western Japan during 2009–2018. Stream water samples were also collected from four locations at sites Swₑₛₜ and Rwₑₛₜ during the same period. Results showed that atmospheric N deposition in Fukuoka started to decrease from the mid-2000s at an annual rate of −2.5% yr⁻¹. The decrease in atmospheric N deposition was attributable mainly to decreased atmospheric ammonium (NH₄⁺) deposition, which caused greater contribution of NO₃⁻ deposition to atmospheric N deposition. Concentrations of NO₃⁻ in the stream water samples from three of the four locations decreased significantly at an annual rate of −3.7 to −0.7% yr⁻¹. However, stream water NO₃⁻ concentrations increased in one watershed where understory vegetation has been deteriorating owing to the increased deer population. This might weaken the recovery of N leaching from forested areas.

Source apportionment can be an effective tool in mitigating soil pollution but its efficacy is often limited by a lack of information on the factors that influence the accumulation of pollutants at a site. In response to this limitation and focusing on a suite of heavy metals identified as priorities for pollution control, the study established a comprehensive pollution control framework using factor identification coupled with spatial agglomeration for agricultural soils in an industrialized part of Zhejiang Province, China. In addition to elucidating the key role of industrial and traffic activities on heavy metal accumulation through implementing a receptor model, specific influencing factors were identified using a random forest model. The distance from the soil sample location to the nearest likely industrial source was the most important factor in determining cadmium and copper concentrations, while distance to the nearest road was more important for lead and zinc pollution. Soil parent materials, pH, organic matter, and clay particle size were the key factors influencing accumulation of arsenic, chromium, and nickel. Spatial auto-correlation between levels of soil metal pollution and industrial agglomeration can enable a more targeted approach to pollution control measures. Overall, the approach and results provide a basis for improved accuracy in source apportionment, and thus improved soil pollution control, at the regional scale.

Although recent epidemiologic studies have focused on some of the health effects of perfluoroalkyl substance (PFASs) exposure in humans, the associations between PFASs exposure and the lipidome in children are still unclear. The purpose of this study was to assess lipid changes in children to understand possible molecular events of environmental PFASs exposure and suggest potential health effects. A total of 290 Taiwanese children (8–10 years old) were included in this study. Thirteen PFASs were analyzed in their serum by high-performance liquid chromatography-tandem mass spectrometry (LC-MS). MS-based lipidomic approaches were applied to examine lipid patterns in the serum of children exposed to different levels of PFASs. LC coupling with triple quadrupole MS technology was conducted to analyze phosphorylcholine-containing lipids. Multivariate analyses, such as partial least squares analysis along with univariate analyses, including multiple linear regression, were used to analyze associations between s exposure and unique lipid patterns. Our results showed that different lipid patterns were discovered in children exposed to different levels of specific PFASs, such as PFTrDA, PFOS, and PFDA. These changes in lipid levels may be involved in hepatic lipid metabolism, metabolic disorders, and PFASs-membrane interactions. This study showed that lipidomics is a powerful approach to identify critical PFASs that cause metabolite perturbation in the serum of children and suggest possible adverse health effects of these chemicals in children.

Cuttings are the main solid residues which are generated from drilling operations. Due to the presence of heavy and radioactive elements, the environment risk posed by cuttings has attracted increasing attention. In this work, a short-term static immersion experiment was carried out to investigate the leaching of polycyclic aromatic hydrocarbons (PAHs) from oil-based residues of shale gas drilling cuttings. Furthermore, the effects of some relevant environmental factors controlling the leaching behavior were evaluated, including the different particle sizes, pH, extraction time, solid-to-liquid (S/L) ratio and dissolved organic matter (DOM) concentration. The results showed that (1) the concentrations of leached PAHs gradually increased with prolonged leaching time, but the cumulative amount of PAHs released during leaching was less than 3% of the total. (2) The Elovich, parabolic diffusion and power function models were found to fit the experimental data better than the first-order kinetic equation, indicating that the leaching of PAHs was controlled by the coupling of diffusion and chemical reactions at the source surface. (3) Different environmental factors had different impacts on the leaching of PAHs: the shaking time and presence of DOM increased leachability, the particle size and S/L ratio decreased leachability, and the pH did not affect the leachability of PAHs. Therefore, PAHs leaching was a complex process, and it is of scientific and environmental interest to conduct the leaching tests under the simulated environmental conditions.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Many estuaries have undergone severe saltwater intrusion in addition to simultaneously experiencing serious heavy metal pollution. To explore the effect of water density stratification associated with saltwater intrusion on the behaviour of heavy metals (Cr, Co, Ni, Cu, Zn, As, Pb, and Cd) in water and sediments, a field survey was conducted in a typical estuary (Modaomen). The content, distribution, and mobility of heavy metals were investigated, as well as the influence of environmental factors on their future. The results showed that Modaomen estuary was characterised by a notable variation in salinity along the estuary, presenting total freshwater upstream, high salinity stratification water in the mouth, and saltwater offshore. Dissolved metals presented a prominent gradient vertically, with 1.2–2.1 times higher in bottom water than in surface water and the highest contents in the highly–stratified bottom water. Elevated salinity and restricted mixing induced by water stratification were likely the causes of this outcome. The distribution of heavy metals in sediments was greatly governed by grain size, Fe/Mn (hydr)oxides, total organic carbon, salinity, and dissolved oxygen. Comprehensive evaluation, combined with total contents and chemical fractions of heavy metals, indicated that internal release from sediments contributed a considerable part to the higher levels of heavy metals in bottom water, particularly for Zn and Pb, which was fully consistent with their status in water body, and elevated salinity and lack of oxygen were likely the primary driving factors. During the phase-partition processes between bottom water and sediments, partitioning coefficients were markedly lower in the highly stratified zone, implying that saltwater intrusion facilitated the mobility and repartitioning processes of metals. Because of increased levels and toxicity of heavy metals in water and extended residence time during saltwater intrusion, the potential damage to the estuarine ecosystem should receive more attention.

Despite being effective in controlling mosquito larvae and a few other target organisms, the application of insecticides into aquatic systems may cause unintended alterations to the physiology or behavioral responses of several aquatic non-target organisms, which can ultimately lead to their death. Here, we firstly evaluated whether the susceptibility of the giant water bug, Belostoma anurum (Hemiptera: Belostomatidae), a predator of mosquito larvae, to pyriproxyfen would be similar to that of its potential prey, larvae of Aedes aegypti (Diptera: Culicidae). Secondly, we recorded the nominal concentrations of pyriproxyfen in water and evaluated whether sublethal exposures would lead to physiological or behavioral alterations on the B. anurum nymphs. We characterized the activities of three major families of detoxification enzymes (i.e., cytochrome P450 monooxygenases, glutathione-S-transferase, and general esterases) and further evaluated the abilities of pyriproxyfen sublethally-exposed B. anurum to prey upon A. aegypti larvae at different prey densities. Our findings revealed that nominal pyriproxyfen concentration significantly decreased (approximately 50%) over the first 24 h. Furthermore, when applied at the concentration of 10 μg a.i./L, pyriproxyfen was approximately four times more toxic to A. aegypti larvae (LT₅₀ = 48 h) than to B. anurum nymphs (LT₅₀ = 192 h). Interestingly, the pyriproxyfen sublethally-exposed (2.5 μg a.i./L) B. anurum nymphs exhibited reduced enzyme activities (cytochrome P450 monooxygenases) involved in detoxication processes and preyed significantly less on A. aegypti larvae when compared to unexposed predators. Collectively, our findings demonstrate that mortality-based pyriproxyfen risk assessments are not always protective of aquatic non-target organisms.

The limited evidence available suggests that the interaction between chemical pollutants and biological particles may intensify respiratory diseases caused by air pollution in urban areas. Unlike air pollutants, which are routinely measured, records of biotic component are scarce. While pollen concentrations are daily surveyed in most cities, data related to airborne bacteria or fungi are not usually available. This work presents the first effort to understand atmospheric pollution integrating both biotic and abiotic agents, trying to identify relationships among the Proteobacteria, Actinobacteria and Ascomycota phyla with palynological, meteorological and air quality variables using all biological historical records available in the Madrid Greater Region. The tools employed involve statistical hypothesis contrast tests such as Kruskal-Wallis and machine learning algorithms. A cluster analysis was performed to analyse which abiotic variables were able to separate the biotic variables into groups. Significant relationships were found for temperature and relative humidity. In addition, the relative abundance of the biological phyla studied was affected by PM₁₀ and O₃ ambient concentration. Preliminary Generalized Additive Models (GAMs) to predict the biotic relative abundances based on these atmospheric variables were developed. The results (r = 0.70) were acceptable taking into account the scarcity of the available data. These models can be used as an indication of the biotic composition when no measurements are available. They are also a good starting point to continue working in the development of more accurate models and to investigate causal relationships.

Land use regression modeling is a common method for assessing exposure to ambient pollutants, yet it suffers from very coarse temporal resolution. Wireless distributed sensor networks (WDSN) is a promising technology that can provide extremely high spatiotemporal pollutant patterns but is known to suffer from several limitations that put into question its data reliability. This study examines the advantages of fusing data from these two methods and obtaining high spatiotemporally-resolved product that can be used for exposure assessment. We demonstrate this approach by estimating nitrogen dioxide (NO₂) concentrations at a sub-urban scale, with the study area limited by the deployment of the WDSN nodes. Specifically, hourly-resolved fused-data estimates were obtained by combining a stationary traffic-based land use regression (LUR) model with observations (15 min sampling frequency) made by an array of low-cost sensor nodes, with the sensors’ readings mapped over the whole study area. Data fusion was performed by merging the two independent information products using a fuzzy logic approach. The performance of the fused product was examined against reference hourly observations at four air quality monitoring (AQM) stations situated within the study area, with the AQM data not used for the development of any of the underlying information layers. The mean hourly RMSE between the fused data product and the AQM records was 9.3 ppb, smaller than the RMSE of the two base products independently (LUR: 14.87 ppb, WDSN: 10.45 ppb). The normalized Moran’s I of the fused product indicates that the data-fusion product reveals more realistic spatial patterns than those of the base products. The fused NO₂ concentration product shows considerable spatial variability relative to that evident by interpolation of both the WDSN records and the AQM stations data, with significant non-random patterns in 74% of the study period.