Plastic particles smaller than 1 μm are considered to be highly dangerous pollutants due to their ability to penetrate living cells. Model experiments on the toxicity of plastics should be correlated with actual concentrations of plastics in natural water. We simulated the natural destruction of polystyrene, polyvinyl chloride, and poly(methyl methacrylate) in experiments on the abrasion of plastics with small stones. The plastics were dyed in mass with a fluorescent dye, which made it possible to distinguish plastic particles from stone fragments. We found that less than 1% of polystyrene and polyvinyl chloride were converted to submicron size particles. In the case of more rigid poly(methyl methacrylate), the fraction of such particles reaches 11%. The concentration of particles with a diameter less than 1 μm in the model experiments was from 0.7 (polystyrene) to 13 mg/L (poly(methyl methacrylate)), and when transferring the obtained data to real reservoirs, these values should be reduced by several orders of magnitude. These data explain the difficulties associated with the search for nanoplastics in natural waters. The toxicity of such particles to hydrobionts in model experiments was detected for concentrations greater than 1 mg/L, which is unrealistic in nature. Detectable and toxic amounts of nano- and submicron plastic particles in living organisms can be expected only in the case of filter-feeding organisms, such as molluscs, krill, sponges, etc.

Pollen allergens, widely present in the atmosphere, are the main cause of seasonal respiratory diseases that affect millions of people worldwide. Although previous studies have reported that nitrogen dioxide (NO₂) and ozone (O₃) promote pollen allergy, the specific biological processes and underlying mechanisms remain less understood. In this study, Platanus pollen grains were exposed to gaseous pollutants (NO₂ and O₃). We employed environmental electron microscopy, flow cytometry, western blot assay, enzyme-linked immunoassay, ultraviolet absorption spectrometry, circular dichroism, and protein mass spectrometry to characterise the subpollen particles (SPPs) released from pollen grains. Furthermore, we determined the immunogenicity and pathogenicity induced by Platanus pollen allergen a 3 (Pla a 3). Our results demonstrated that NO₂ and O₃ could damage the pollen cell membranes in SPPs and increase the amount of Pla a 3 allergen released into the atmosphere. Additionally, NO₂ and O₃ altered the structure of Pla a3 protein through nitrification and oxidation, which not only enhanced the immunogenicity of allergens but also increased the stability of the protein. In vivo analysis using an animal model indicated that NO₂ and O₃ greatly aggravated pollen-induced pneumonia. Thus, our study provides guidance for the prevention of pollen allergic diseases.

The hazardous effects of herbicides are well known; however, their effects on the reproductive system remain unclear. In this study, we demonstrated the anti-proliferative effects of dinitramine (DN) on immature murine testicular cell lines (Leydig and Sertoli cells) mediated via endoplasmic reticulum (ER) stress-induced calcium dysregulation in the cytosol and mitochondria. The results demonstrated that the viability and proliferation of DN-treated TM3 and TM4 cells decreased significantly, even in the spheroid state. DN induced the apoptosis of TM3 and TM4 cells and decreased the expression of genes related to cell cycle progression. Treatment with DN increased the cytosolic and intramitochondrial levels of calcium by activating ER stress signals. DN activated the Erk/P38/Jnk Mapk pathway and inactivated the Pi3k/Akt pathway in murine testicular cells. Co-treatment with 2-aminoethoxydiphenyl borate (2-APB) mitigated DN-induced calcium upregulation in both testicular cell lines. Although 2-APB did not antagonize the anti-proliferative effect of DN in TM3 cells, treatment with 2-APB and 1,2-bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid restored the proliferation of DN-treated TM4 cells.

Recycling of waste glycerol derived from biodiesel production to high value-added chemicals is essential for sustainable development of Bio-Circular-Green Economy. This work studied the conversion of glycerol to 1,3-propanediol over Pt/WOₓ/Al₂O₃ catalysts, pointing out the impacts of catalyst pore sizes and operating conditions for maximizing the yield of 1,3-propanediol. The results suggested that both pore confinement effect and number of available reactive metals as well as operating conditions determined the glycerol conversion and 1,3-propanediol selectivity. The small-pore 5Pt/WOₓ/S–Al₂O₃ catalyst (6.1 nm) gave a higher Pt dispersion (32.0%), a smaller Pt crystallite size (3.5 nm) and a higher number of acidity (0.47 mmol NH₃ g⁻¹) compared to those of the large-pore 5Pt/WOₓ/L-Al₂O₃ catalyst (40.3 nm). However, glycerol conversion and 1,3-propanediol yield over the small-pore 5Pt/WOₓ/S–Al₂O₃ catalyst were significantly lower than those of the large-pore Pt/WOₓ/L-Al₂O₃ catalyst, suggesting that the diffusional restriction within the small-pore catalyst suppressed transportation of molecules to expose catalytic active sites, favoring the excessive hydrogenolysis of 1,3-propanediol, giving rise to undesirable products. The best 1,3-propanediol yield of 32.8% at 78% glycerol conversion were achieved over the 5Pt/WOₓ/L-Al₂O₃ under optimal reaction condition of 220 °C, 6 MPa, 5 h reaction time and amount of catalyst to glycerol ratio of 0.25 g mL⁻¹. However, the 1,3-propanediol yield and glycerol conversion decreased to 19.6% and 51% after the 4th reaction-regeneration which were attributed to the carbonaceous deposition and the agglomeration of Pt particles.

Natural photic regime has been drastically altered by the artificial night sky luminance. Despite evidence of sufficient light brightness inducing plant physiology and affecting phenology, generalization regarding effects of light pollution on plant phenology across species and locations is less clear. Meanwhile, the relative contributions and joint effects of artificial light pollution and climate change or other anthropic stressors still remain unknown. To fill this knowledge gap, we utilized in situ plant phenological observations of seven tree species during 1991–2015 in Europe, night-time light dataset and gridded temperature dataset to investigate the impacts of the artificial light pollution on spatial-temporal shifts of plant phenological phases under climatic warming. We found 70% of the observation sites were exposed to increased light pollution during 1992–2015. Among them, plant phenological phases substantially delayed at 12–39% observation sites of leaf-out, and 6–53% of flowering. We also found plant species appeared to be more sensitive to artificial light pollution, and phenology advancement was hindered more prominently and even delay phenomenon exhibited when the color level showed stronger sky brightness. Linear mixed models indicate that although temperature plays a dominant role in shifts of plant phenological phases at the spatial scale, the inhibitory effect of artificial light pollution is evident considering the interactions. To our knowledge, this study is the first to quantitatively establish the relationship between artificial light pollution and plant phenology across species and locations. Meanwhile, these findings provide a new insight into the ecological responses of plant phenology to the potential but poorly understood environmental stressors under this warmer world and call for light pollution to be accorded the equal status as other global change phenomena.

Atmospheric size-classified particles in sizes ranging from small to nanoparticles (PM₀.₁) are reported for Rangsit City in the Bangkok Metropolitan Region (BMR) of Thailand, for October 2019 (wet season) and January–February 2020 (dry season). The sampling involved the use of a PM₀.₁ cascade air sampler to determine the mass concentration. The PMs consisted of six stages including TSP–PM₁₀, PM₂.₅₋₁₀, PM₁.₀₋₂.₅, PM₀.₅₋₁.₀, PM₀.₅₋₁.₀ and PM₀.₁. Elemental carbon (EC) and organic carbon (OC) were evaluated by a carbon analyzer following the IMPROVE_TOR protocol. The average PM₀.₁ mass concentrations were found to be 13.47 ± 0.79 (wet season) and 18.88 ± 3.99 (dry season) μg/m³, respectively. The average OC/EC ratio for the rainy season was lower than that in the dry season. The char-EC/soot-EC ratios were consistently below 1 for the PM₀.₁ fraction in both seasons indicating that vehicular traffic appeared to be the main emission source. However, the influence of open biomass burning on fine and coarse PM particles on local air pollution was found to be an important issue during the wet season. In addition, long-range transport from other countries may also contribute to the carbon content in the Bangkok Metropolitan Region (BMR) atmosphere during the dry season. The higher secondary organic carbon to organic carbon (SOC/OC) ratio in the dry season is indicative of the contribution of secondary sources to the formation of PM, especially finer particles. A strong correlation between OC and EC in nanoparticles was found, indicating that they are derived from sources of constant emission, likely the diesel engines. Conversely, the OC and EC correlation for other size-specific PMs decreased during the dry season, indicating that these emission sources were more varied.

During March 2020, most European countries implemented lockdowns to restrict the transmission of SARS-CoV-2, the virus which causes COVID-19 through their populations. These restrictions had positive impacts for air quality due to a dramatic reduction of economic activity and atmospheric emissions. In this work, a machine learning approach was designed and implemented to analyze local air quality improvements during the COVID-19 lockdown in Graz, Austria. The machine learning approach was used as a robust alternative to simple, historical measurement comparisons for various individual pollutants. Concentrations of NO₂ (nitrogen dioxide), PM₁₀ (particulate matter), O₃ (ozone) and Oₓ (total oxidant) were selected from five measurement sites in Graz and were set as target variables for random forest regression models to predict their expected values during the city’s lockdown period. The true vs. expected difference is presented here as an indicator of true pollution during the lockdown. The machine learning models showed a high level of generalization for predicting the concentrations. Therefore, the approach was suitable for analyzing reductions in pollution concentrations. The analysis indicated that the city’s average concentration reductions for the lockdown period were: -36.9 to −41.6%, and −6.6 to −14.2% for NO₂ and PM₁₀, respectively. However, an increase of 11.6–33.8% for O₃ was estimated. The reduction in pollutant concentration, especially NO₂ can be explained by significant drops in traffic-flows during the lockdown period (−51.6 to −43.9%). The results presented give a real-world example of what pollutant concentration reductions can be achieved by reducing traffic-flows and other economic activities.

The increasing demand for fresh water coupled with the need to recycle water and nutrients has witnessed a global increase in wastewater irrigation. However, the development of antibiotic resistance hotspots in different environmental compartments, as a result of wastewater reuse is becoming a global health concern. The effect of irrigation water sources (wastewater, surface water, fresh water) on the presence and abundance of antibiotic resistance genes (ARGs) (blaCTX₋ₘ₋₃₂, tet-W, sul1, cml-A, and erm-B) and class 1 integrons (intI1) were investigated in the irrigation water-soil-crop continuum using quantitative real-time PCR (qPCR). Sul1 and blaCTX₋ₘ₋₃₂ were the most and least abundant ARGs in three environments, respectively. The abundance of ARGs and intI1 significantly decreased from wastewater to surface water and then fresh water. However, irrigation water sources had no significant effect on the abundance of ARGs and intI1 in soil and crop samples. Principal component analysis (PCA) showed that UV index and air temperature attenuate the abundance of ARGs and intI1 in crop samples whereas the air humidity and soil electrical conductivity (EC) promotes the ARGs and intI1. So that the climate condition of semi-arid regions significantly affects the abundance of ARGs and intI1 in crop samples. The results suggest that treated wastewater might be safely reused in agricultural practice in semi-arid regions without a significant increase of potential health risks associated with ARGs transfer to the food chain. However, further research is needed for understanding and managing ARGs transfer from the agricultural ecosystem to humans through the food chain.

The reduction of NOₓ emissions in a VOC-limited region can lead to an increase of the local O₃ concentration. An evaluation of the net health effects of such pollutant changes is therefore important to ascertain whether the emission control measures effectively improve the overall protection of public health. In this study, we use a short-term health risk (added health risk or AR) model developed for the multi-pollutant air quality health index (AQHI) in Hong Kong to examine the overall health impacts of these pollutant changes. We first investigate AR changes associated with NO₂ and O₃ changes, followed by those associated with changes in all four AQHI pollutants (NO₂, O₃, SO₂, and particulate matter (PM)). Our results show that for the combined health effects of NO₂ and O₃ changes, there is a significant reduction in AR in urban areas with dense traffic, but no statistically significant changes in other less urbanized areas. The increase in estimated AR for higher O₃ concentrations is offset by a decrease in the estimated AR for lower NO₂ concentrations. In areas with dense traffic, the reduction in AR as a result of decreased NO₂ is substantially larger than the increase in AR associated with increased O₃. When additionally accounting for the change in ambient SO₂ and PM, we found a statistically significant reduction in total AR everywhere in Hong Kong. Our results show that the emission control measures resulting in NO₂, SO₂, and PM reductions over the past decade have effectively reduced the AR over Hong Kong, even though these control measures may have partially contributed to an increase in O₃ concentrations. Hence, efforts to reduce NOx, SO₂, and PM should be continued.

Owing to its physicochemical similarity to strontium (Sr), calcium (Ca) was tested as a key component of a soil washing solution for Sr-contaminated soil collected near a nuclear power plant. A four-factor, three-level Box–Behnken experimental design combined with response surface modeling was employed to determine the optimal Sr washing condition for Ca-based solution. The Ca concentration (0.1–1 M), liquid-to-soil ratio (5–20), washing time (0.5–2 h), and pH (2.0–7.0) were tested as the independent variables. From the Box–Behnken design, 27 sets of experimental conditions were selected, and a second-order polynomial regression equation was derived. The significance of the independent parameters and interactions was tested by analysis of variance. Ca concentration was found to be the most influential factor. To determine whether the four variables were independent, three-dimensional (3D) response surface plots were established. The optimal washing condition was determined to be as follows: 1 M Ca, L/S ratio of 20, 1 h washing, and pH = 2. Under this condition, the highest Sr removal efficiency (68.2%) was achieved on a soil contaminated with 90.1 mg/kg of Sr. Results from five-step sequential extraction before and after washing showed that 84.0% and 82.9% of exchangeable and carbonate-bound Sr were released, respectively. In addition, more tightly bound Sr, such as Fe/Mn oxides-bound and organic matter-bound Sr, were also removed (86.2% and 64.5% removal, respectively).