Plastic marine debris hyper-concentrates hydrophobic contaminants such as polycyclic aromatic hydrocarbons (PAHs) and can transfer these sorbed contaminants to biota following ingestion. PAHs are known to induce cardiotoxicity and visual toxicity at sublethal doses. Juvenile White seabass (Atractoscion nobilis) fish were fed environmentally relevant concentrations of either virgin polystyrene or benzo(a)pyrene (BaP)-sorbed polystyrene for 5 days and were monitored for changes in phototactic response, swimming behavior, and hepatic cytochrome p450 1A (CYP1A) enzyme activity. No significant differences in the monitored endpoints were recorded in fish that ingested either polystyrene or BaP-sorbed polystyrene relative to control fish following the short-term exposure. However, fish exposed to 252 μg/L BaP alone as a positive control had significantly elevated CYP1A enzyme activity (p = 0.046) and impaired phototactic response (p = 0.020), though no altered swimming behavior was observed (p = 0.843) relative to control fish. These results demonstrate that pelagic fish ingesting environmentally relevant concentrations of BaP-sorbed polystyrene for a short, 5-day duration do not demonstrate measurable changes in vision, swimming activity, nor CYP1A activity. High variability within enzyme activity and behavioral responses suggest that lack of significant effects may be due to low sample size.

Bis(2-ethylhexyl) phthalate (DEHP) is the most common plasticizer. Previous studies have shown DEHP treatment accelerates neurological degeneration, suggesting that DEHP may impact retinal sensitivity to light, neurotransmission, and copulation behaviors. Although its neurotoxicity and antifertility properties have been studied, whether DEHP exposure disrupts vision and how DEHP influences neuromuscular junction (NMJ) have not been reported yet. Moreover, the impact of DEHP on insect courtship behavior is still elusive. Fruit flies (Drosophila melanogaster) were treated with series concentrations of DEHP and observed for lifespan, motor function, electroretinogram (ERG), electrophysiology of neuromuscular junction (NMJ), courtship behaviors, and relevant gene expression. Our results confirmed the DEHP toxicity on lifespan and capacity of motor function and updated its effect on copulation behaviors. Additionally, we report for the first time that DEHP exposure may harm vision by affecting the synaptic signaling between the photoreceptor and the laminar neurons. Further, DEHP treatment altered both spontaneous and evoked neurotransmission properties. Noteworthy, the effect of DEHP exposure on the copulation behavior is sex-dependent, and we proposed potential mechanisms for future investigation.

The development of the eye in vertebrates is dependent upon glucocorticoid signalling, however, specific components of the eye are sensitive to synthetic glucocorticoids. The presence of synthetic glucocorticoids within the aquatic environment may therefore have important consequences for fish, which are heavily reliant upon vision for mediating several key behaviours. The potential ethological impact of synthetic glucocorticoid oculotoxicity however has yet to be studied. Physiological and behavioural responses which are dependent upon vision were selected to investigate the possible toxicity of prednisolone, a commonly occurring synthetic glucocorticoid within the environment, during early life stages of zebrafish. Although exposure to prednisolone did not alter the morphology of the external eye, aggregation of melanin within the skin in response to increasing light levels was impeded and embryos exposed to prednisolone (10 μg/l) maintained a darkened phenotype. Exposure to prednisolone also increased the preference of embryos for a dark environment within a light dark box test in a concentration dependent manner. However the ability of embryos to detect motion appeared unaffected by prednisolone. Therefore, while significant effects were detected in several processes mediated by vision, changes occurred in a manner which suggest that vision was in itself unaffected by prednisolone. Neurological and endocrinological changes during early ontogeny are considered as likely candidates for future investigation.

Heavy metals (HMs) in soil and water bodies greatly threaten human health. The wide separation of HMs urges the necessity to develop an expert system for HMs prediction and detection. In the current perspective, several propositions are discussed to design an innovative intelligence system for HMs prediction and detection in soil and water bodies. The intelligence system incorporates the Edge Cloud Server (ECS) data center, an innovative deep learning predictive model and the Federated Learning (FL) technology. The ECS data center is based on satellite sensing sources under human expertise ruling and HMs in-situ measurement. The FL system comprises a machine learning (ML) technique that trains an algorithm across multiple decentralized edge servers holding local data samples without exchanging them or breaching data privacy. The expected outcomes of the intelligence system are to quantify the soil and water bodies' HMs, develop new modified HMs pollution contamination indices and provide decision-makers and environmental experts with an appropriate vision of soil, surface water, and crop health.

Artificial light at night (ALAN) alters circadian rhythms in animals and therefore can be a source of environmental stress affecting their physiology and behaviour. The impact of ALAN can be related to the increased light level, but also to the spectral composition of night lighting. Previous research showed that many species can be particularly sensitive to the LED light, but it is unclear if they respond to its broad spectrum or specifically to the blue light wavelength. In this study, we tested whether dim ALAN (2 lx) differing in the spectral quality (warm white LED, blue LED, high-pressure sodium HPS light) modifies behaviour and changes oxidative status in two nocturnal freshwater shredder species: Dikerogammarus villosus and Gammarus jazdzewskii (Gammaroidea, Amphipoda). Our experiment revealed that ALAN, irrespective of its spectral quality, did not affect the oxidative stress markers in cells (the level of reactive oxygen species and lipid peroxidation). However, ALAN changed the gammarid behaviour in a species-specific manner, which can potentially reduce the fitness of the shredders. Dikerogammarus villosus avoided all types of light compared to darkness. Therefore, confined to the shelter, D. villosus may have fewer opportunities to forage and/or mate. Gammarus jazdzewskii was sensitive only to the narrow-spectrum blue light, but did not respond to the HPS and white LED light. Avoidance is a typical response of gammarids to natural light, thus the disruption of this behaviour in the presence of common ALAN sources can increase the predation risk in this species. To summarize, behavioural modifications induced by ALAN seem more pronounced than changes in physiology and can constitute the main driver of disturbances in the processing of organic matter in freshwater ecosystems by invertebrate shredders.

The human eye is an excellent, general-purpose airborne sensor for detecting marine debris larger than 10cm on or near the surface of the water. Coupled with the human brain, it can adjust for light conditions and sea-surface roughness, track persistence, differentiate color and texture, detect change in movement, and combine all of the available information to detect and identify marine debris. Matching this performance with computers and sensors is difficult at best. However, there are distinct advantages over the human eye and brain that sensors and computers can offer such as the ability to use finer spectral resolution, to work outside the spectral range of human vision, to control the illumination, to process the information in ways unavailable to the human vision system, to provide a more objective and reproducible result, to operate from unmanned aircraft, and to provide a permanent record that can be used for later analysis.

Humanity could face the COVID-19 epidemic to crystallize a sustainable future for the water, hygiene, and food sectors. The epidemic has affected the sustainability of water, food, and health institutions in Egypt. Water consumption levels have increased in the agricultural sector to ensure food security. Regular handwashing is one of the most important measures to prevent the epidemic, and this has an impact on water consumption. The purpose of the research is to reshape sustainable development trajectory due to COVID-19 pandemic in Egypt through three interdependent phases: the first is devoted to forecast how the pandemic could be spreading in Egypt, the second is assigned to foresee implications and consequences of the pandemic on water, food, and human activities, and the third is dedicated to exploring how Egypt could utilize non-conventional water resources as a precious resource to fight the pandemic and explore sustainable recovery strategies. The results could be summarized as the diffusion of COVID-19 pandemic may be considered a group of evolutionary processes. The vision of growth to a limit may be applied; the number of cases of COVID-19 grows rapidly, but the growth will be reduced due to negative feedback signals from the environment. The paper concludes that the COVID-19 epidemic could be addressed by enhancing the water sector to better cope with future shocks. Water, food, health, and work opportunities could be provided and managed sustainably. The need to provide water to wash the hands of all citizens has been emphasized to fight the coronavirus. Non-conventional water resources could be an engine to ambitious plans to drive economic growth through megaprojects. Egypt would enable transforming this crisis into an opportunity to accelerate the pace of action towards achieving Sustainable Development Goals.

Tin oxide (SnO₂) with versatile properties is of substantial standing for practical application, and improved features of the material are demonstrated in the current issue through the integration of nanotechnology with bio-resources leading to what is termed as biosynthesis of SnO₂ nanoparticles (NPs). This review reveals the recent advances in biosynthesis of SnO₂ NPs by chemical precipitation method focused on distinct methodologies, characterization, and reaction mechanism along with a photocatalytic application for dye degradation. According to available literature reviews, numerous bio-based precursors selectively extracted from biological substrates have effectively been applied as capping or reducing agents to achieve the metal oxide NPs. The major precursor obtained from the aqueous extract of root barks of Catunaregam spinosa is found to be 7-hydroxy-6-methoxy-2H-chromen-2-one that has been proposed as a model compound for the reduction of metal ions into nanoparticles due to having highly active functional groups, being abundant in plants (67.475 wt%), easy to extract, and eco benign. In addition, the photocatalytic activity of SnO₂ NPs for the degradation of organic dyes, pharmaceuticals, and agricultural contaminants has been discussed in the context of a promising bio-reduction mechanism of the synthesis. The final properties are supposed to depend exclusively upon a number of factors, e.g., particle size (< 50 nm), bandgap (< 3.6 eV), crystal defects, and catalysts dosage. With this contribution, it has been perceived not only to provide an overview of recent advances in the biosynthesis of SnO₂ NPs but also to indicate the main issues in need aiming to show vision towards innovative outcomes.

Excessive release of methylene blue (MB) in the environment and its potential infusion to human body may cause several health issues such as blurred vision, confusion, hallucinations and seizures. Based on experimental results on MB removal efficiency through adsorption using activated carbon of Parthenium hysterophorus, a simple mathematical model is developed for the prediction of MB removal efficiency for any combination of input conditions. Based on earlier experimental results, four independent variables such as pH, contact time, initial MB concentration and dose concentration were considered for the model. Based on individual experimental results, a factor is proposed for each independent variable. Eventually, all the factors are multiplied with maximum achievable removal efficiency to predict a removal efficiency under specific conditions. It is found that the developed model can accurately predict the higher range of efficiency while underestimates during lower range of efficiency. To overcome this drawback, the developed model was further fine-tuned with an adjustment factor, through which model predictions were turned out to be much better. Standard errors of the original model’s estimations are RMSE = 10.09, MAE = 7.08 and RAE = 0.12. After the mentioned adjustment, the same errors were lowered by 60%, 57% and 83%, respectively. Such modelling approach is very useful for the decision-makers on deciding input variables for industry-scale implementations. Similar mathematical modelling can be adopted for other pollutants and for other adsorbents.

The dynamics of global emissions and the increasing focus on market-based policy instruments have prompted this research to examine the extent to which such instruments are successful in emission control. The study explores the influence of carbon taxes, eco-friendly innovations, and ecological policy in attaining sustainable development goals and fulfilling the mitigation targets of climate change for 2030. The article selected 15 EU countries from southern and western regions and tested the empirical relationship between 2000 and 2018. This work used second-generation testing approaches and error correction-based modeling approaches to analyze the relationship between the variables. The results show that eco-friendly innovations and environmental policies help reduce emissions in the long and short run. On the other hand, carbon taxes have a more prominent effect on mitigation efforts, specifically in the short run. Factors such as urbanization, economic growth, and energy consumption are the most prominent polluting elements, the results being consistent in all models. The results further show a unidirectional and bidirectional causality relationship between the variables, and outcomes are more country-specific. Given these arguments, carbon taxes are a short-term instrument in combating carbon emissions. However, the sustainable development vision 2030 relies on eco-innovations linked with research and development and the transition from gray to green energy.