Municipal waste incineration plants (MWIPs) are a source of emission of diverse pollutants that have been associated with environmental and health effects, mainly in relation to premises that are old and not well equipped or maintained. As a result, the public usually holds a negative view of such plants and tends to react adversely to construction of new plants. Understanding a population’s perceptions is key to ensuring the correct development of such infrastructure and adequately managing population health concerns and behaviours. In this study, we surveyed 173 residents living close (≤ 10 km) to an MWIP being built in San Sebastian (Gipuzkoa, Spain) and 164 living further away (>10 km). The questionnaire included sociodemographic and psycho-environmental measures. Answers to the questionnaire revealed a fairly low acceptance rate and the perception of a high risk for human health and the environment (average scores of 0.57, 3.07 and 2.89 respectively in a 0 to 4 scale), with no statistically significant differences between people living nearby and further afield. A hierarchical regression model built to explore the public’s acceptance of the MWIP explained 59% of the variance. Dominance and relative weight analyses revealed that the most important predictors of acceptance were trust in the information provided by the local government and perceived risk for human health, which accounted for 33.7% and 27.4% of the variance explained by the model respectively. Preference for landfilling and MWIP acceptance in a farther location made a less relevant contribution.

The short-term health effects of ozone (O₃) have highlighted the need for high-temporal-resolution O₃ observations to accurately assess human exposure to O₃. Here, we performed 20-s resolution observations of O₃ precursors and meteorological factors to train a random forest model capable of accurately predicting O₃ concentrations. Our model performed well with an average validated R² of 0.997. Unlike in typical linear model frameworks, variable dependencies are not clearly modelled by random forest model. Thus, we conducted additional studies to provide insight into the photochemical and atmospheric dynamic processes driving variations in O₃ concentrations. At nitrogen oxides (NOₓ) concentrations of 10–20 ppb, all the other O₃ precursors were in states that increased the production of O₃. Over a short timescale, nitrogen dioxide (NO₂) can almost track each high-frequency variation in O₃. Meteorological factors play a more important role than O₃ precursors do in predicting O₃ concentrations at a high temporal resolution; however, individual meteorological factors are not sufficient to track every high-frequency change in O₃. Nevertheless, the sharp variations in O₃ related to flow dynamics are often accompanied by steep temperature changes. Our results suggest that high-temporal-resolution observations, both ground-based and vertical profiles, are necessary for the accurate assessment of human exposure to O₃ and the success and accountability of the emission control strategies for improving air quality.

Airborne particulate matter (PM) has become a serious health issue causing pulmonary diseases such as asthma. Due to the side effects and non-specificity of conventional drugs, there is a need to develop natural-product-based alternative treatments. Sargassum horneri is a brown alga shown to have anti-oxidant, anti-inflammatory, and anti-allergic effects. Thus, we sought to determine whether ethanol extract of Sargassum horneri (SHE) mitigates the effect of PM exposure on asthma development. To establish a mouse model of asthma, BALB/c mice were sensitized with ovalbumin (OVA, 10 μg) and challenged with PM (5 mg/m³) for 7 days consecutively. SHE (200, 400 mg/kg), Prednisone (5 mg/kg), or PBS was daily administrated orally before PM exposure. SHE mitigated PM exacerbated dendritic cell activation. More importantly, SHE restrained Th2 polarization by attenuating transcription factors GATA3 and STAT5, which further mitigated the expression of Th2 cytokines interleukin (IL)-4, IL-5, and IL-13 in the lung homogenates of PM-exacerbated asthmatic mice. SHE further attenuated PM-exacerbated eosinophil infiltration in the lung, trachea, and BALF. In addition, SHE markedly mitigated the activation of mast cells and the IgE level in serum. Concomitantly, SHE further restrained the Th17 cell response in PM-exposed allergic mice through attenuating expression of transcription factors RORγT, STAT3 and expression of relevant effector cytokines IL-17a. This resulted in mitigated neutrophil infiltration in the lung. Taken together, SHE significantly suppressed PM-exacerbated hypersecretion of mucus in asthmatic mice. These results suggest that SHE has therapeutic potential for treating PM-exacerbated allergic asthma through concomitantly inhibiting Th2/Th17 responses.

This study investigated the impact of different environmental particles at different concentrations (0.2% and 2%, w/w) on biodegradation of dibutyl phthalate (DBP) in sediments with and without Cylindrotheca closterium, a marine benthic diatom. The particles included biochar pyrolyzed at 400 °C, multi-walled carbon nanotube (MWNT), nanoscale zero-valent iron (nZVI) and polyethylene microplastic. In treatments without C. closterium, inhibition effect of the particles on degradation percentage of DBP (up to 15.7% decrement except 1.7% increment for 0.2% nZVI) increased with the increase of particle sorption ability to DBP and particle concentration in general. The results of 16s rDNA sequencing showed that C. closterium was probably the most abundant DBP-degrader, accounting for 20.0–49.3% of the total taxon read numbers. In treatments with C. closterium, inoculation of C. closterium increased the degradation percentage of DBP in all treatments with particle addition by 0.0–11.3%, which increased with the increase of chlorophyll a content in general but decreased with the increase of particle concentration from 0.2% to 2%. The increment was the highest for treatment with 0.2% nZVI addition due to its highest promotion effect on algal growth. In contrast, the increment was the lowest for treatments with MWNT addition due to its strong sorption to DBP and strong inhibition on the growth of C. closterium. Our findings suggested that the environmental particles could influence bioavailability of DBP by sorption and biomass of C. closterium, and thus degradation of DBP in sediments.

Artificial Light at Night (ALAN), which is the alteration of natural light levels as the result of anthropogenic light sources, has been acknowledged as an important factor that alters the functioning of marine ecosystems. Using LEDs light to mimic ALAN, we studied the effect on the physiology (symbiont and chlorophyll contents, photosynthesis, respiration, pigment profile, skeletal growth, and oxidative stress responses) of two scleractinian coral species originating from the Red Sea. ALAN induced the photoinhibition of symbiont photosynthesis, as well as an overproduction of reactive oxygen species (ROS) and an increase in oxidative damage to lipids in both coral species. The extent of the deleterious effects of ALAN on the symbiotic association and coral physiology was aligned with the severity of the oxidative stress condition experienced by the corals. The coral species Sylophora pistillata, which experienced a more severe oxidative stress condition than the other species tested, Turbinaria reniformis, also showed a more pronounced bleaching (loss of symbionts and chlorophyll content), enhanced photoinhibition and decreased photosynthetic rates. Findings of the present study further our knowledge on the biochemical mechanisms underpinning the deleterious impacts of ALAN on scleractinian corals, ultimately shedding light on the emerging threat of ALAN on coral reef ecology. Further, considering that global warming and light pollution will increase in the next few decades, future studies should be taken to elucidate the potential synergetic effects of ALAN and global climate change stressors.

A laboratory bioassay was conducted to investigate the ecotoxicity of a chromium-enriched superfood, Spirulina platensis, on the meiofauna collected from the Ghar El Melh lagoon, Tunisia. After 1 month of exposure, the abundances of meiobenthic taxa and the taxonomic and morpho-functional diversity of nematodes showed significant differences between the Spirulina and Spirulina + chromium groups. The nematodes were more tolerant of all types of stressors compared to harpacticoids, polychaetes, and oligochaetes, and the lowest taxonomic and morpho-functional diversity of nematodes was observed in the highest sedimentary concentration of S. platensis (50% DW). The mixed treatments may have been richer in micro-habitats and subject to low selective pressure, thereby hosting nematodes with a wide range of adaptations. The responses of the nematode species differed depending on their functional traits. Spirulina enriched with chromium induced two responses for the same feeding group: high toxicity for Daptonema fallax and low toxicity for two Theristus species (T. flevensis and T. modicus). The ecotoxicity of the Spirulina/chromium mixtures were lower than that of Spirulina alone, suggesting mutual neutralization between these two elements. The association between functional traits and taxonomic diversity showed that the effects of the mixtures were not additive and that one of the stressors camouflaged the effect of the other. Our findings should encourage the commercialization of chromium-enriched S. platensis owing to its lower ecotoxicity than Spirulina alone.

Previous epidemiological and experimental studies have shown that legacy perfluoroalkyl acids (PFAAs) are immunotoxic. However, whether the immunosuppressive effects in PFAA alternatives which recently have been widely detected in the environment are unknown. To address this knowledge gap, we investigated the relationship of serum legacy PFAAs and PFAA alternatives with the antibody of hepatitis B virus in adults. We recruited 605 participants from a cross-sectional study, the Isomer of C8 Health Project in China. We measured two representative legacy PFAAs (perfluorooctane sulfonate, PFOS and perfluorooctanoic acid, PFOA), and three PFAA alternatives (two chlorinated polyfluorinated ether sulfonic acids, Cl-PFESAs and perfluorobutanoic acid, PFBA) in serum using ultra-performance liquid chromatograph-tandem mass spectrometry (UPLC-MS/MS). We applied linear and logistic regression models to analyze associations between serum PFAAs and hepatitis B surface antibody (HBsAb) with multivariable adjustments. We found negative associations between serum PFAAs concentrations and HBsAb. Lower serum HBsAb levels (log mIU/mL) were observed for each log-unit increase in linear PFOS (β = −0.31, 95% confidential interval: 0.84, −0.18), 6:2 PFESA (β = −0.81, 95% CI: 1.20, −0.42), 8:2 PFESA (β = −0.29, 95% CI: 0.43, −0.14) and PFBA (β = −0.18, 95% CI: 0.28, −0.08). The association between PFAAs and HBsAb seronegative seemed to be higher for 6:2 PFESA (odds ratio = 3.32, 95% CI: 2.16, 5.10) than its predecessors, linear PFOS (OR = 1.96, 95% CI: 1.37, 2.81) and branched PFOS isomers (OR = 1.64, 95% CI: 1.05, 2.56). We report new evidence that exposure to PFAA alternatives are associated with lower HBsAb in adults. This association seems to be stronger in 6:2 PFESA than PFOS. Our results suggest that more studies are needed to clarify the potential toxicity of PFAA alternatives in human which will facilitate better chemical regulations for PFAAs.

The surface organic horizons in forest soils have been affected by air and soil pollutants, including potentially toxic elements (PTEs). Monitoring of PTEs requires a large number of samples and adequate analysis. Visible–near infrared (vis–NIR: 350–2500 nm) spectroscopy provides an alternative method to conventional laboratory measurements, which are time-consuming and expensive. However, vis–NIR spectroscopy relies on an empirical calibration of the target attribute to the spectra. This study examined the capability of vis–NIR spectra coupled with machine learning (ML) techniques (partial least squares regression (PLSR), support vector machine regression (SVMR), and random forest (RF)) and a deep learning (DL) approach called fully connected neural network (FNN) to assess selected PTEs (Cr, Cu, Pb, Zn, and Al) in forest organic horizons. The dataset consists of 2160 samples from 1080 sites in the forests over all the Czech Republic. At each site, we collected two samples from the fragmented (F) and humus (H) organic layers. The content of all PTEs was higher in horizon H compared to F horizon. Our results indicate that the reflectance of samples tended to decrease with increased PTEs concentration. Cr was the most accurately predicted element, regardless of the algorithm used. SVMR provided the best results for assessing the H horizon (R² = 0.88 and RMSE = 3.01 mg/kg for Cr). FNN produced the best predictions of Cr in the combined F + H layers (R² = 0.89 and RMSE = 2.95 mg/kg) possibly due to the larger number of samples. In the F horizon, the PTEs were not predicted adequately. The study shows that PTEs in forest soils of the Czech Republic can be accurately estimated with vis–NIR spectra and ML approaches. Results hint in availability of a large sample size, FNN provides better results.