This work is a first part of the study in development on the mapping of soiling losses in the region of Rabat-Sale-Kenitra in Morocco. To perform the work, two holders of glass samples have been constructed and installed in two different sites of Sale City for three successive periods (from April to June 2019). At the end of each period, the transmittance losses of the glass samples as well as the mass of deposited soils are systematically measured. SEM (scanning electronic microscopy) analyses are also performed for more investigation and deep understanding. The obtained results show that the relationship between soil mass density and glass transmittance loss is not always linear as could be expected. They also show that soiling losses are strongly depending on the environment and nature of the surrounding installation spaces. The SEM analysis results of the 1st period and the inclined surfaces have shown that particles are greater in the range of 2–11 μm and the majority tends to have a regular shape in the two sites. Nevertheless, the frequencies are different. From this study, it can be concluded that it is highly recommended characterizing the site where soiling measurements are conducted not only by its location/city but also by its environment characteristics.

With the growing interest among researchers in analyzing the ecological footprint of any country, this study focuses on new dimensions to analyze the long-run and short-run asymmetric impact of tourism, financial development, and globalization on ecological footprint in Turkey by using Quantile Autoregressive Distributed Lag model for the period from 1986 to 2018. Further, the EKC hypothesis was also tested. The results show that tourism, globalization, and financial development are positively and significantly associated with the EFP. This means that the increase in these variables will further increase the ecological footprint in Turkey. The U-shaped EKC curve was found to be valid in Turkey. The results also depict nonlinear and asymmetric association among most of the variables. Hence, based on the results, further research directions and practical implications can be suggested.

Cobalt (Co) is widely used in many industrial fields such as batteries and paints. Cobalt, a dangerous heavy metal, can be found in high concentrations in natural and human habitats. Although cobalt is an important micronutrient, it is toxic to living organisms when exposed to high amounts. Carob (Ceratonia siliqua L.) is a tree native to The Mediterranean region. Carob bean, which has high nutritional and economic value, is used against cardiovascular and gastrointestinal diseases. In addition, the antioxidant properties of carob are gaining importance in recent years. In this study, the protective effects of carob extract against the toxicity of cobalt on Allium cepa L. were investigated. For this purpose, 150 mg/L and 300 mg/L carob extract solutions and 5.5 mg/kg cobalt solutions were applied to A. cepa L. bulbs. Root emergence, weight gain, root elongation, and mitotic index (MI) decreased, while the frequency of chromosomal abnormalities (CAs) and micronucleus (MN) increased as a result of Co application. Furthermore, Co treatment triggered a noticeable rise in the activities of superoxide dismutase (SOD) and catalase (CAT) enzymes as well as the malondialdehyde (MDA) amount and the abnormalities in the meristematic cells. On the other hand, applications of carob extracts mitigated cobalt-induced damages in a dose-dependent manner in all parameters. Therefore, the current study showed that the strong preventive potential of carob extract against phytotoxicity and genotoxicity is caused by Co in a model plant. The protective effects of carob extract on Co-induced toxicity were demonstrated for the first time in terms of reducing genotoxicity and oxidative stress response.

Animal-Vehicle Collision (AVC) is a predominant problem in both urban and rural roads and highways. Detecting animals on the road is challenging due to factors like the fast movement of both animals and vehicles, highly cluttered environmental settings, noisy images, and occluded animals. Deep learning has been widely used for animal applications. However, they require large training data; henceforth, the dimensionality increases, leading to a complex model. In this paper, we present an animal detection system for mitigating AVC. The proposed system integrates sparse representation and deep features optimized with FixResNeXt. The deep features extracted from candidate parts of the animals are represented in a sparse form using a feature-efficient learning algorithm called Sparse Network of Winnows (SNoW). The experimental results prove that the proposed system is invariant to the viewpoint, partial occlusion, and illumination. On the benchmark datasets, the proposed system has achieved an average accuracy of 98.5%.

Studies from our group and others have reported that 30 mW/cm² microwave could damage the structures of rat hippocampus, as well as impair the neuronal functions. The neuroprotective effects of astragaloside, purified from Astragalus membranaceus, have been demonstrated in animal models of neurodegenerative diseases. In this study, we found that 30 mW/cm² microwave impaired spatial learning and memory ability in rats, while astragaloside could significantly alleviate the injuries. The pathological analysis also showed that astragaloside protected neurons from microwave-induced damages, such as mitochondrial swelling and cavitation, rough endoplasmic reticulum swelling and dilation, synaptic gap disappearing, and vesicle aggregation. Moreover, microwave-induced structural damage of synapse resulted in downregulation of acetylcholine, an important neurotransmitter for information transmission, while astragaloside could protect the structure of synapse, as well as restore the acetylcholine level in rat hippocampus. Furthermore, astragaloside also accelerated the recovery of brain electroencephalogram (EEG) after microwave exposure, indicating that astragaloside could promote the normalization of neuronal functions. In conclusion, astragaloside protected the morphological structures and restored acetylcholine level in rat hippocampus, which could improve brain functions via normalizing brain EEG. Therefore, astragaloside might be a promising candidate to treat microwave-induced injuries of central nervous system (CNS).

In the process of identifying groundwater pollution sources, in order to solve the problem that the monitoring data of monitoring wells was insufficient or the correlation between monitoring data and model parameters was weak, a monitoring well optimization method based on Bayesian formula and information entropy was proposed. Two-dimensional phreatic groundwater solute transport model was built and solved by using GMS software. To reduce the computational load of calling the numerical model repeatedly in the optimization design of the monitoring schemes and the identification process of the pollution sources, the Kriging method was used to establish the surrogate model of the numerical model. Under the condition of single well monitoring and determined monitoring frequency, with the target of optimization of monitoring position number D and monitoring time interval ∆t, both the single-objective monitoring scheme with the minimum information entropy of the model parameter posterior distribution and the multi-objective monitoring scheme with the minimum information entropy and the shortest monitoring time were optimized respectively. According to the above-optimized monitoring schemes, the delayed rejection adaptive Metropolis algorithm was used to identify the pollution source parameters. The case study results showed that under the condition of pre-set single well monitoring with monitoring frequency of 10 times, the single-objective optimized monitoring scheme was D = 37 and Δt = 20 days. Under this monitoring scheme, the mean errors of inversion pollution source parameters α = (XS, YS, T₁, T₂, QS) were 0.09%, 0.4%, 4.72%, 2.43%, and 9.29%, respectively. The multi-objective optimized monitoring scheme was D = 37 and Δt = 2 days. Under this monitoring scheme, the mean errors of the inversion parameters α = (XS, YS, T₁, T₂, QS) were 12.76%, 3.77%, 5.13%, 1.36%, and 7.68%, respectively. Compared with the monitoring scheme based on the single-objective optimization, although the inversion mean error of the five parameters based on the multi-objective optimized monitoring scheme increased by 2.75%, the monitoring time significantly reduced from 180 to 18 days.

The concentrations and fractions of heavy metal in sediments at different altitudes in the water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) were determined. The Pearson correlation analysis was used to determine the differences between heavy metal fractions and physicochemical properties. The results showed that Cr and Cu were mainly horizontally and vertically distributed in the residual (RE) fractions with the highest stability and relatively low ecological risk. Pb and Zn were mainly in the Fe-Mn oxide-bound (Fe-Mn) fractions, which can be reduced to a bioavailable state when the redox potential decreased or the oxygen was severely depleted in the aquatic environment. There were significant differences in the heavy metal fractions and risks in sediment in the three different altitudes of the TGR. The physicochemical characteristics of the sediment indicated that the sediments in the low altitude area had rough forms and large pores. In addition, heavy metals at low altitudes were likely to be released into the water during antiseasonal water storage, causing secondary pollution, which greatly increased the mobility of heavy metals and ecological risks to the environment.

Chlorinated ethene contaminations are a widespread environmental hazard and a threat to drinking water supplies. Electrochemical methods for in situ degradation of the chlorinated ethenes in the plume are under development. In laboratory, complete electrochemical removal of chlorinated ethenes in undivided flow-through reactors is reported when using palladized iron (Fe) cathodes (C) and cast Fe anodes (A). The cost of the electrodes depends on the Fe purity. In this study, 99.95%, 99.8% and 98+% palladized Fe cathodes, and 99.8% Fe and cast Fe anodes were investigated. The surfaces of the palladized Fe electrodes were examined by scanning electron microscopy. Deposition of palladium by electroless plating onto the Fe surfaces was uneven and disconnected. The less pure the Fe material, the higher the degree of oxide coverage of the cathode’s surface during electroless plating. Electrochemical application via Fe electrodes installed in a flow-through reactor of field-extracted groundwater and sandy sediment was studied for three-electrode configurations of A–A–C and C–C–A. The anodes of 99.8% Fe and cast Fe demonstrated different corrosion patterns; uniform corrosion and graphitization, respectively. Corrosion products clogged the sandy matrix. The corrosion product compositions differed between the A–A–C and C–C–A electrode configurations. The groundwater pH of 7.35 ± 0.05 changed downgradient to the electrochemical zone to 9.5 and 6.2 for the A–A–C and C–C–A reactors, respectively. The response of the hydrogeochemical settings to the established redox zones showed that the C–C–A electrode configuration was less intrusive to the surrounding environment. Graphical Abstract .

With the rapid growth of economy, the environmental pollution problem is becoming increasingly prominent. How to promote the coordinated and balanced development of economy and environment is a strategic problem of great significance that we face urgently. Taking Wuhan City of China as the research object, this paper selects the key indexes of economic growth and environmental pollution and studies the interactive influence between economic growth and environmental pollution in Wuhan. On the one hand, the impact of Wuhan’s economic growth on environmental pollution is analyzed by the proposed time-delay correlation analysis method and the time-delay EKC (Environment Kuznets Curve) models. On the other hand, the impact of Wuhan’s environmental pollution on environmental growth is studied. By establishing the LARS-LASSO (least angle regression-least absolute shrinkage and selection operator) regression model and the stepwise regression model, the main factors affecting economic growth in preliminary environmental pollution indexes are analyzed, and then, an interaction model is established to study the impact of the interaction between any two main environmental factors on economic growth. The results of empirical analysis show that the main factors affecting economic growth are industrial wastewater emissions, industrial waste gas emissions, and industrial smoke and dust emissions, and the interaction between industrial waste gas emissions and industrial wastewater emissions restrains economic growth.

In the last few years, neurodegenerative diseases like Alzheimer’s disease (AD) and Parkinson’s disease (PD) have attracted attention due to their high prevalence worldwide. Environmental factors may be one of the biggest reasons for these diseases related to neuronal dysfunctions. Most of neuronal disorders are strongly associated with pre- and postnatal exposure to environmental toxins released from industries. Some of the neurotoxic metals such as lead, aluminum, mercury, manganese, cadmium, and arsenic as well as some pesticides and metal-based nanoparticles have been involved in AD and PD due to their ability to produce senile/amyloid plaques and NFTs which are the main feature of these neuronal dysfunctions. Exposure to solvents is also majorly responsible for neurodegenerative disorders. The present review highlights the impact of omnipresent heavy metals with some other neurotoxins on human health and how they give rise to neuronal dysfunctions which in turn causes socio-economic consequences due to increasing pollution worldwide. Graphical abstract