Litter is omnipresent in the ocean where it can be ingested by marine biota. Although ingestion of microplastics (MPs) is abundantly reported, insights into how MP can influence predator-prey interactions currently limits our understanding of the ecological impact of MPs. Here we demonstrate trophic transfer of MPs from zooplankton to benthic filter feeders, through consumption of contaminated prey (i.e. prey with ingested MP). However, predation rates of contaminated prey were significantly lower as compared to predation rates of prey that had no MPs ingested. As filter feeder clearance rates were not affected by consumption of MPs, the lower predation rates of contaminated prey appear to be primarily explained by disruption in zooplankton swimming behaviour that reduces their filtration risk. This is the first study that shows how MPs can change predator-prey interactions that are involved in the coupling between the pelagic and seabed habitat.

The strict Clean Air Action Plan has been in place by central and local government in China since 2013 to alleviate haze pollution. In response to implementation of the Plan, daytime PM₂.₅ (particulate matter with aerodynamic diameter less than 2.5 μm) showed significant downward trends from 2015 to 2019, with the largest reduction during spring and winter in the North China Plain. Unlike PM₂.₅, O₃ (ozone) showed a general increasing trend, reaching 29.7 μg m⁻³ on summer afternoons. Increased O₃ and reduced PM₂.₅ simultaneously occurred in more than half of Chinese cities, increasing to approximately three-fourths in summer. Declining trends in both PM₂.₅ and O₃ occurred in only a few cities, varying from 19.1% of cities in summer to 33.7% in fall. Meteorological variables helped to decrease PM₂.₅ and O₃ in some cities and increase PM₂.₅ and O₃ in others, which is closely related to terrain. High wind speed and 24 h changing pressure favored PM₂.₅ dispersion and dilution, especially in winter in southern China. However, O₃ was mainly affected by 24 h maximum temperature over most cities. Soil temperature was found to be a key factor modulating air pollution. Its impact on PM₂.₅ concentrations depended largely on soil depth and seasons; spring and fall soil temperature at 80 cm below the surface had largely negative impacts. Compared with PM₂.₅, O₃ was more significantly affected by soil temperature, with the largest impact at 20 cm below the surface and with less seasonal variation.

Plants, that naturally inhabit arsenic-contaminated areas may be used for effective arsenic-uptake from soil. The efficiency of this process may be increased by the reducing arsenic phytotoxicity and stimulating the activity of indigenous soil microbiota. As we showed, it can be achieved by the bioaugmenting of soil with arsenite-oxidizing bacteria (AOB). This study aimed to investigate the influence of soil bioaugmentation with AOB on the structure, quantity, and activity of the indigenous soil microbiota as well as to estimate the effect of such changes on the morphology, growth rate, and arsenic-uptake efficiency of plants. Plants-microbes interactions were investigated using the effective arsenites oxidizer Ensifer sp. M14 and the native plant alfalfa. The experiments were performed both in potted garden soil enriched with arsenic and in highly arsenic polluted, natural soil. The presence of M14 strain in soil contributed to the increase both in plants growth intensity and arsenic-uptake efficiency with regard to the soil without M14. After 40 days of plants culture, their average biomass increased by about 60% compared to non-bioaugmented soil, while the arsenic accumulation increased more than two times. The soil bioaugmentation contributed also to the increase in the quantity and activity of soil microorganisms without disturbing the natural microbial community structure. In the bioaugmented soil, the noticable increase in the quantity of heterotrophic, denitrifying, nitrifying and cellulolytic bacteria as well as in the activity of dehydrogenases and cellulases were observed. Soil bioaugmentation with M14 enables the application of native and commonly occurring plant species for enhancing the treatment of arsenic-contaminated soil. This in situ strategy may constitute a valuable alternative both to the chemical and physical methods of arsenic removal from soil and to the biological ways based on the arsenic hyperaccumulating plants and/or the arsenic mobilizing bacteria.

The heating of edible oils during cooking activities promotes the emissions of pollutants that have adverse impacts on the health of humans. This study investigated the evaporative emissions of fifteen (15) commonly used cooking oils. Split-plot experimental design under the response surface methodology framework was used to study singular and interaction effects of influencing parameters (temperature, volume of cooking oil and time) on cooking oil evaporation rate and pollutants emissions (i.e. Particulate matter of aerodynamic diameter ≤1 μm (PM₁.₀); ≤2.5 μm (PM₂.₅); ≤10 μm (PM₁₀); Total Suspended Particulate (TSP); Total Volatile Organic Compounds -TVOCs, and Carbon Monoxide- CO) on a groundnut oil sample that served as a case study. Obtained values of density, viscosity, kinematic viscosity, smoke, flash and fire points were; 873–917 kg/m³; 1.12–9.7 kg/ms; 2.4–3.4 m²/s; 96 -100 °C; 124–179 °C and 142–186 °C, respectively. The role of temperature as the most significant parameter influencing the rate of evaporative emissions was established. Evaporation rate and pollutants emission from unrefined samples were the highest. The restricted maximum likelihood (REML) analysis results suggested a strong relationship between the actual values and the predicted values as R-squared values obtained were greater than 0.8 for all the responses. These results suggest that minimal rates of evaporation and pollutants emission from heating cooking oils can be achieved with a high volume of the cooking oil at moderate temperature levels.

During their lifetime honey bees (Apis mellifera) rarely experience optimal conditions. Sometimes, a simultaneous action of multiple stressors, natural and chemical, results in even greater effect than of any stressor alone. Therefore, integrative investigations of different factors affecting honey bees have to be carried out. In this study, adult honey bees exposed to thiamethoxam in larval and/or adult stage and infected with Nosema ceranae were examined. Newly emerged bees from colonies, non-treated or treated with thiamethoxam, were organized in six groups and kept in cages. Thiamethoxam treated bees were further exposed to either thiamethoxam or Nosema (groups TT and TN), or simultaneously to both (group TTN). Newly emerged bees from non-treated colonies were exposed to Nosema (group CN). From both, treated and non-treated colonies two groups were organized and further fed only with sugar solution (groups C and TC). Here, we present the expression profile of 19 genes in adult worker honey bees comprising those involved in immune, detoxification, development and apoptosis response. Results showed that gene expression patterns changed with time and depended on the treatment. In group TC at the time of emergence the majority of tested genes were downregulated, among which nine were significantly altered. The same gene pattern was observed on day six, where the only significantly upregulated gene was defensin-1. On day nine most of analyzed genes in all experimental groups showed upregulation compared to control group, where upregulation of antimicrobial peptide genes abaecin, defensin-1 and defensin-2 was significant in groups TT and TTN. On day 15 we observed a similar pattern of expression in groups TC and TT exposed to thiamethoxam only, where most of the detoxification genes were downregulated. Additionally RNA loads of Nosema and honey bee viruses were recorded. We detected a synergistic interaction of thiamethoxam and Nosema, reflected in lowest honey bee survival.

The synergistic cooperation of microbial cells and their extracellular polymeric substances (EPS) in biofilms is critical for the biofilm’s resistance to heavy metals and the migration and transformation of heavy metals. However, the effects of different components of biofilms have not been fully understood. In this study, the spatial distribution and speciation of copper in the colloidal EPS, capsular EPS, cell walls and membranes, and intracellular fraction of unsaturated Pseudomonas putida (P. putida) CZ1 biofilms were fully determined at the subcellular level. It was found that 60–67% of copper was located in the extracellular fraction of biofilms, with 44.7–42.3% in the capsular EPS. In addition, there was 15.5–20.1% and 17.2–21.2% of copper found in the cell walls and membranes or the intracellular fraction, respectively. Moreover, an X-ray absorption fine structure spectra analysis revealed that copper was primarily bound by carboxyl-, phosphate-, and hydrosulfide-like ligands within the extracellular polymeric matrix, cell walls and membranes, and intracellular fraction, respectively. In addition, macromolecule quantification, fourier-transform infrared spectroscopy spectra and sulfur K-edge x-ray absorption near edge structure analysis further showed the carboxyl-rich acidic polysaccharides in EPS, phospholipids in cell walls and cell membranes, and thiol-rich intracellular proteins were involved in binding of copper in the different components of biofilm. The full understanding of the distribution and chemical species of heavy metals in biofilms not only promotes a deep understanding of the interaction mechanisms between biofilms and heavy metals, but also contributes to the development of effective biofilm-based heavy metal pollution remediation technologies.

Exposure to air pollutants has been associated with respiratory and cardiovascular mortality, but the underlying molecular mechanisms remain inadequately understood. We aimed to examine molecular-level inflammatory and oxidative stress responses to personal air pollutant exposure. Fifty-three healthy adults aged 22–52 were measured three times for their blood inflammatory cytokines and urinary malondialdehyde (MDA, an oxidative stress biomarker) within 2 consecutive months. Pollutant concentrations monitored indoors and outdoors were combined with the time-activity data to calculate personal O₃, PM₂.₅, NO₂, and SO₂ exposures averaged over 12 h, 24 h, 1 week, and 2 weeks, respectively, prior to biospecimen collection. Inflammatory cytokines and MDA were associated with pollutant exposures using linear mixed-effects models controlling for various covariates. After adjusting for a co-pollutant, we found that concentrations of proinflammatory cytokines were significantly and negatively associated with 12-h O₃ exposures and significantly but positively associated with 2-week O₃ exposures. We also found significant and positive associations of proinflammatory cytokines with 12-h and 24-h NO₂ exposures, respectively. However, we did not find clear associations of PM₂.₅ and SO₂ exposure with proinflammatory cytokines and with MDA. The removal of an O₃-generating electrostatic precipitator in the mechanical ventilation systems of the offices and residences of the subjects was associated with significant decreases in IL-1β, IL-2, IL-6, IL-8, IL-17A, and TNF-α. These findings suggest that exposure to O₃ for different time durations may affect systemic inflammatory responses in different ways.

In shallow eutrophic lakes, metal remobilization is closely related to the resuspension and eutrophication. An improved understanding of metal dynamics by biogeochemical processes is essential for effective management strategies. We measured concentrations of nine metals (Cr, Cu, Zn, Ni, Pb, Fe, Al, Mg, and Mn) in water and sediments during seven periods from 2014 to 2018 in northern Lake Taihu, to investigate the metal pollution status, spatial distributions, mineral constituents, and their interactions with P. Moreover, an automatic weather station and online multi-sensor systems were used to measure meteorological and physicochemical parameters. Combining these measurements, we analyzed the controlling factors of metal dynamics. Shallow and eutrophic northern Lake Taihu presents more serious metal pollution in sediments than the average of lakes in Jiangsu Province. We found chronic and acute toxicity levels of dissolved Pb and Zn (respectively), compared with US-EPA “National Recommended Water Quality Criteria”. Suspended particles and sediment have been polluted in different degrees from uncontaminated to extremely contaminated according to German pollution grade by LAWA (Bund/Länder-Arbeitsgemeinschaft Wasser). Polluted particles might pose a risk due to high resuspension rate and intense algal activity in shallow eutrophic lakes. Suspended particles have similar mineral constituents to sediments and increased with increasing wind velocity. Al, Fe, Mg, and Mn in the sediment were rarely affected by anthropogenic pollution according to the geoaccumulation index. Among them, Mn dynamics is very likely associated with algae. Micronutrient uptake by algal will affect the migration of metals and intensifies their remobilization. Intensive pollution of most particulate metals were in the industrialized and down-wind area, where algae form mats and decompose. Moreover, algal decomposition induced low-oxygen might stimulate the release of metals from sediment. Improving the eutrophication status, dredging sediment, and salvaging cyanobacteria biomass are possible ways to remove or reduce metal contaminations.

The insufficient removal of pollutants and bioelectricity production have become a bottleneck for high-concentration saline wastewater treatment through microbial fuel cell (MFC) technology. Herein, a novel supercapacitor MFC (SC-MFC) was constructed with carbon nanofibers composite electrodes to investigate pollutant removal ability, power generation, and electrochemical properties using real landfill leachate. The possible extracellular electron transfer and nitrogen element conversion pathways in the bioanode were also analyzed. Results showed that the SC-MFC had higher pollutant removal rates (COD: 59.4 ± 1.2%; NH₄⁺-N: 78.2 ± 1.6%; and TN: 77.8 ± 1.2%), smaller internal impedance Rₜ (∼6 Ω), higher exchange current density i₀ (2.1 × 10⁻⁴ A cm⁻²), and a larger catalytic current j₀ (704 μA cm⁻²) with 60% leachate than those with 10% and 20% leachate, resulting in a power output of 298 ± 22 mW m⁻². Ammonium could be incorporated by chemoautotrophic bacteria to produce organic compounds that could be further utilized by heterotrophs to generate power when biodegradable organic matters are depleted. Three conversion pathways of nitrogen might be involved, including NH₄⁺ diffusion from anode to cathode chamber, nitrification, and the denitrification process. Additionally, cyclic voltammetry tests showed that both the direct electron transfer (DET) and the mediator electron transfer in bioanode were involved and dominated by DET. The microbial analysis revealed that the bioanode was dominated by salt-tolerant denitrifying bacteria (38.5%), which was deduced to be the key functional microorganism. The electrochemically active bacteria decreased significantly from 61.7% to 4% over three stages of leachate treatment. Overall, the SC-MFC has demonstrated the potential for wastewater treatment along with energy harvesting and provides a new avenue toward sustainable leachate management.

In the present paper, a scenario-based many-objective optimization model is developed for the spatio-temporal optimal design of reservoir water quality monitoring systems considering uncertainties. The proposed methodology is based on the concept of nonlinear interval number programming and information theory, while handling uncertainties of temperature, reservoir inflow, and inflow constituent concentration. A reference-point-based non-dominated sorting genetic algorithm (NSGA-III) is used to deal with the many-objective optimization problem. The proposed model is developed for the Karkheh reservoir system in Iran as a real-world problem. The results show excellent performance of the optimized water quality sampling locations instead of all potential ones in providing adequate information about the reservoir water quality status. The presented uncertainty-based model leads to a 55.73% reduction in the radius of the uncertain interval caused by different scenarios. Handling uncertainties in a spatio-temporal many-objective optimization problem is the main contribution of this study, yielding a reliable and robust design of a reservoir monitoring system that is less sensitive to various scenarios.