Integrated spatial health assessment of yellow perch (<Emphasis Type="Italic">Perca flavescens</Emphasis>) populations from the St. Lawrence River,Quebec, Canada) part A: physiological parameters and pathogen assessment

A multi-disciplinary approach was used to evaluate the health of yellow perch (Perca flavescens) in the St. Lawrence River (Quebec, Canada), which is experiencing a severe population decline in the downstream portion of the river. Physiological parameters, liver alterations, trace metal concentrations, parasite prevalence and abundance, stable isotope composition, and the presence/absence of the viral hemorragic septicemia virus (VHSV) were evaluated in perch collected at six sites along the river: Lake St. François, Lake St. Louis (north and south), Beauregard Island, and Lake St. Pierre (north and south). Trace metal concentrations in surface water were higher in Lake St. Louis and downstream of a major urban wastewater treatment plant discharge, indicating that this effluent was a significant source of Cu, As, Ag, Zn, and Cd. Levels of Pb in surface water exceeded thresholds for the protection of aquatic life in Lake St. Louis and were negatively correlated with body condition index in this lake. In Lake St. Pierre, Cu, Ag, and Cd bioaccumulated significantly in perch liver and lower body condition index and greater liver damage were observed compared to upstream sites. Parasite analyses indicated a higher abundance of metacercariae of the trematodes Apophallus brevis and Diplostomum spp. in Lake St. Louis, and VHSV was not detected in the liver of yellow perch for all studied sites. Overall, results suggested that the global health of yellow perch from Lake St. Pierre is lower compared to upstream studied sites, which could contribute to the documented population collapse at this site.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Hexabromocyclododecanes in soils and plants from a plastic waste treatment area in North China: occurrence,diastereomer- and enantiomer-specific profiles,and metabolization

Plastic waste is a source of organic contaminants such as hexabromocyclododecanes (HBCDs). HBCDs have been found to cause developmental and reproductive toxicity; it is important to investigate the occurrence and metabolization of HBCDs in the soil environments with plastic waste contamination. This work analyzed HBCDs and their metabolites in soil and plant samples collected from Xinle and Dingzhou—the major plastic waste recycling centers in North China. Results showed that total HBCD concentrations in soils followed the order: plastic waste treatment site (11.0–624 ng/g) > roadside (2.96–85.4 ng/g) ≥ farmland (8.69–55.5 ng/g). HBCDs were detected in all the plant samples with total concentrations ranging from 3.47 to 23.4 ng/g. γ-HBCD was the dominant congener in soils, while α-HBCD was preferentially accumulated in plants. Compositions of HBCD isomers in soils and plants were significantly different (P < 0.05) among sampling sites and among plant species. HBCDs in farmland soil and all plant samples exhibited high enantio-selectivity based on the enantiomeric fractions (EFs). Furthermore, metabolites of pentabromocyclododecenes (PBCDEs) were frequently identified in soils, and mono-OH-HBCDs were the most common ones in plants. This study for the first time provides evidences of HBCD contamination in the soil-plant system caused by plastic waste, their stereo-selectivity, and metabolization behavior, improving our understanding of the environmental behavior and fate of HBCDs.     

Carbon dioxide emissions,output, and energy consumption categories in Algeria

This study examines the relation between CO₂ emissions, income, non-renewable, and renewable energy consumption in Algeria during the period extending from 1980 to 2011. Our work gives particular attention to the validity of environmental Kuznets curve (EKC) hypothesis. The autoregressive distributed lag (ARDL) with break point method outcome demonstrates the positive effect of non-renewable type of energy on CO₂ emissions consumption. On the contrary, the results reveal an insignificant effect of renewable energy on environment improvement. Moreover, the results accept the existence of EKC hypothesis but the highest gross domestic product value in logarithm scale of our data is inferior to the estimated turning point. Consequently, policy-makers in Algeria should expand the ratio of renewable energy and should decrease the quota of non-renewable energy consumption.     

Development of the hybrid cells in series model to simulate ammonia nutrient pollutant transport along the Umgeni River

Discharge of organic waste results in high nutrient pollution of the water bodies which is a major menace to the environment. A high quantity of nutrients such as ammonia causes a reduction in the dissolved oxygen level and induces algal growth in the water bodies. Water quality models have been the tools to evaluate the rate at which streams can disperse the pollutants they receive. Many water quality models are flawed either because of their inadequacy to completely simulate the advection component of the pollutant transport, or because of the limited application of the models, due to inaccurate estimation of model parameters. The hybrid cell in series (HCIS) developed by Ghosh et al. (2004) has been able to overcome such difficulties associated with the mixing cell-based models. Thus, the current study focuses on developing an analytical solution for the pollutant transport of the ammonia concentration through the plug flow, the first and second well-mixed cells of the HCIS model. The HCIS model coupled with the first order kinetic equation for ammonia nutrient was developed to simulate the ammonia pollutant concentration in the water column. The ammonia concentration at various points along the river system was assessed by considering the effects of the transformation of ammonia to nitrite, the uptake of ammonia by the algae, the respiration rate of the algae and the input of benthic source to the ammonia concentration in the water column. The proposed model was tested using synthetic data, and the HCIS-NH₃ model simulations for spatial and temporal variation of ammonia pollutant transport were analysed. The simulated results of the HCIS-NH₃ model agreed with the Fickian-based advection-dispersion equation (ADE) for simulating ammonia concentration solved using an explicit finite difference scheme. The HCIS-NH₃ model also showed a good agreement with the observed data from the Umgeni River, except during rainy periods.     

Immobilization of fungal laccase onto a nonionic surfactant-modified clay material: application to PAH degradation

Nonionic surfactant-modified clay is a useful absorbent material that effectively removes hydrophobic organic compounds from soil/groundwater. We developed a novel material by applying an immobilized fungal laccase onto nonionic surfactant-modified clay. Low-water-solubility polycyclic aromatic hydrocarbons (PAHs) (naphthalene/phenanthrene) were degraded in the presence of this bioactive material. PAH degradation by free laccase was higher than degradation by immobilized laccase when the surfactant concentration was allowed to form micelles. PAH degradation by immobilized laccase on TX-100-modified clay was higher than on Brij35-modified clay. Strong laccase degradation of PAH can be maintained by adding surfactant monomers or micelles. The physical adsorption of nonionic surfactants onto clay plays an important role in PAH degradation by laccase, which can be explained by the structure and molecular interactions of the surfactant with the clay and enzyme. A system where laccase is immobilized onto TX-100-monomer-modified clay is a good candidate bioactive material for in situ PAHs bioremediation.     

Sediment pollution and dynamic in the Mar Piccolo of Taranto (southern Italy): insights from bottom sediment traps and surficial sediments

Major and trace element, PAH, and PCB concentrations were measured in surface sediments and particles from sediment traps collected in the First and Second Basin of the Mar Piccolo (Gulf of Taranto) in two periods (June–July and August–September, 2013). The aim of the study was to evaluate pollution degree, sediment transport and particle redistribution dynamic within the area. Results confirm the higher contamination of sediments from the First Basin observed by previous researches, particularly for Cu, Hg, Pb, total PAHs, and total PCBs. Advective transport from the First to the Second Basin appears to be the leading transfer mechanism of particles and adsorbed contaminants, as evidenced by measured fluxes and statistical analyses of contaminant concentrations in surficial sediments and particles from sediment traps. Long-range selective transports of PAHs and microbial anaerobic degradation processes for PCBs have been also observed. These results are limited to a restricted time window but are consistent with the presence of transport fluxes at the bottom of the water column. This mechanism deserves further investigation and monitoring activities, potentially being the main responsible of pollutant delivering to the less contaminated sectors of the Mar Piccolo.     

Investigation of low-level <Superscript>242</Superscript>Pu contamination on nutrition disturbance and oxidative stress in <Emphasis Type="Italic">Solanum tuberosum</Emphasis> L.

Plutonium associated with higher molecular weight molecules is presumed to be poorly mobile and hardly plant available. In our present study, we investigate the uptake and effects of Pu treatments on Solanum tuberosum plants in amended Hoagland medium at concentrations of [²⁴²Pu] = 100 and 500 nm, respectively. We found a direct proof of oxidative stress in the plants caused by these rather low concentrations. For the confirmation of oxidative stress, we explored the production of nitric oxide (NO) and hydrogen peroxide (H₂O₂) by epifluorescence microscopy. Oxidative stress markers like lipid peroxidation and superoxide radicals (O₂ ^??) are monitored through histochemical analysis. The biochemical parameters i.e. chlorophyll and carotenoids are measured as an indicator of cellular damage in the tested plants including the enzymatic parameters such as catalase and glutathione reductase. From our work, we conclude that Pu in low concentration has no significant effects on the uptake of many trace and macroelements. In contrast, the content of O₂ ^?? , malondialdehyde (MDA), and H₂O₂ increases with increasing Pu concentration in the solution, while the opposite effects was found for NO, catalase, and glutathione reductase. These findings prove that even low concentration of Pu regulates ROS production and generate oxidative stress in S. tuberosum L.     

Interaction webs in arctic ecosystems: Determinants of arctic change?

How species interact modulate their dynamics, their response to environmental change, and ultimately the functioning and stability of entire communities. Work conducted at Zackenberg, Northeast Greenland, has changed our view on how networks of arctic biotic interactions are structured, how they vary in time, and how they are changing with current environmental change: firstly, the high arctic interaction webs are much more complex than previously envisaged, and with a structure mainly dictated by its arthropod component. Secondly, the dynamics of species within these webs reflect changes in environmental conditions. Thirdly, biotic interactions within a trophic level may affect other trophic levels, in some cases ultimately affecting land–atmosphere feedbacks. Finally, differential responses to environmental change may decouple interacting species. These insights form Zackenberg emphasize that the combination of long-term, ecosystem-based monitoring, and targeted research projects offers the most fruitful basis for understanding and predicting the future of arctic ecosystems.