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Downtimes due to ice formation on rotor blades reduce the economic efficiency of wind turbines. An accurate ice prediction is required to operate active de-icing measures such as blade heating as an anti-icing system. Building upon our previous research, this paper proposes the use of a convolutional neural network model with dual inputs and one-dimensional convolution filters using historical data from the wind turbine as well as weather forecasts to predict the ice situation for the next 24 hours. The model is validated using data from three different wind farms and shows an average balanced accuracy of 97.9%.

In the era of digitalization, electronic Kanban (e-Kanban) extends the traditional Kanban with additional data and information sharing that allows for more flexible and optimized inventory planning. The lack of automated fill level measurements for load carriers still hinders the full automation of the process. Our aim is to develop a self-learning e-Kanban system that automatically triggers replenishment orders using machine learning and data from low cost, autonomous sensor modules that measure the fill level of load carriers. This paper explains the concept and presents a first version of the mentioned sensor module that consists of an Intel Realsense sensor and an NVIDIA Jetson Nano. An evaluation is presented as well using small load carriers, which shows the suitability of the proposed method.

Ice formation on rotor blades of wind turbines cause significant downtimes in cold regions. Existing ice sensors can detect, but cannot predict ice. Therefore, our research aims to develop an ice prediction system based on historical and forecasted data. In a first step, the detection process is analyzed in this research paper. Two machine learning models are trained using minimalistic input parameters. A full-factorial experiment design is performed for the models, using the fl-score as the response variable. The most significant input parameter was the external temperature for both models.

Ice formed on wind turbines not only causes economic damage but also poses a risk to nearby humans. Countermeasuring ice formation requires reliable detection systems. Existing ice detection solutions have improved with time, but are still not sufficiently accurate. This paper investigates the use of different convolutional neural networks (CNNs) and RGB images taken from cameras installed on the nacelle of wind turbines to detect ice on the rotor blades. In our research, the VGG19 model achieved the best performance with an accuracy and an f1-score of (96 ± 2) %.

This study describes the contamination, accumulation, and ecological risk assessment of five trace metals (Cd, Pb, Cu, Zn, and Cr) in sediments of an urbanized beach in the central Atlantic coastline of Morocco. The two-year investigation (2018 and 2019) included six sampling sites along a 6 km coastal reach. In both years, none of the studied trace metals exceeded the background or the sediment quality guidelines (SQGs). The eco-toxicological indices revealed low degree of contamination, unpolluted ecosystem, and low ecological risk of metals. However, Cd exceeded the background value and some SQGs following the increase of anthropogenic activities in 2019. Likewise, it indicated unpolluted to moderately polluted sediment as well as moderate ecological risk. Overall, it is highly recommended to mitigate the avoidable anthropogenic activities (marine litter generation, sewage discharge, intense urbanization, and vehicle traffic on the beach) that lead to the elevation of metal pollution in the study area.

In cold regions like Northern Europe or Northern America, formation of ice on wind turbines not only reduces the power output of the system, but also leads to wind turbine breakdowns and poses a risk to nearby vehicles and people. Economical solutions for anti-icing systems such as preventive heating are required. Purely meteorological icing predictions are not sufficient to accurately predict icing on wind turbines. Therefore, this paper proposes an icing prediction approach that uses historical weather data and data from a supervisory control and data acquisition (SCADA) system plus methods from supervised machine learning to predict the risk of icing. The first results of the prediction model show its capability to predict most of the icing events. The discussion shows that the model should consider more meteorological data that describe the icing risk such as humidity or liquid water content to achieve better prediction results. The final aim is a prediction system that will use real-time data to determine icing risks hours beforehand, allowing the operation of existing anti-icing systems more efficiently.

Digital twins perform process-accompanying services of machining processes or even of complete production systems. This article examines the interconnection between a physical production system and its digital twin, focusing on required sensors and the number of synchronization points to realize a dedicated control by the digital twin. Therefore, the physical system is modeled within AnyLogic to simulate different sensor configurations and breakdowns. A simulation-based digital twin is implemented to control the production system over a TCP/IP interface. As a result, a simulation-based examination of sensor configurations and their impact on the overall production system’s performance is proposed.

This work describes the spatiotemporal analysis of microplastics (MPs) pollution in sediments collected on a high urbanized beach located in Taghazout coast, central Atlantic part of Morocco. The study area is mainly composed of moderately well-sorted fine sands with an average density of MPs that ranged between 915 MPs/kg in 2018 and 1448 MPs/kg in 2019. The most polluted sites were in the south part of Taghazout coast, close to facilities of where beachgoers are often found. Microplastic Pollution Index (MPPI), Microplastic Impact Coefficient (CMPI), Agglomerative Hierarchical Clustering (AHC), and Multidimensional Scaling (MDS) revealed spatiotemporal variation of MPs pollution. Thus, the principal component analysis (PCA) showed a low correlation between the sediment characteristics (i.e., grain size, sorting, skewness) and MPs densities. Overall, the outputs of this baseline recommend implementing plastic management strategies to eliminate or at least minimize the collateral effects generated by MPs pollution in sediments of urbanized beaches.

This study describes the use of D. trunculus as a bioindicator of microplastic (MPs) pollution due to beach urbanization related to the development of the Taghazout Bay tourist resort in Morocco. In six sites located on the coast, MPs densities ranged from 1.75 to 5.93 items per gram of D. trunculus wet weight. MPs contamination was significantly influenced spatiotemporally by the urbanization degree in the area. The shapes found were fibers (90.5%) and fragments (9.5%). The Fourier Transform Infrared Spectroscopy (FTIR) analysis reported two polymers: polyethylene (65%) and polypropylene (35%). MPs colors were dark and light, with a predominance of light blue (23.8%). The species ingested different sizes of MPs, mainly the 0.1 and 0.5 mm fractions. Scanning Electron Microscope coupled with an energy dispersive X-ray analyzer (SEM/EDX) revealed weathered MPs with chemical elements adhered to their surface (Cu, Fe, Mg, S, Cl, etc.). The results of this study recommend the use of D. trunculus as a new bioindicator of MPs pollution following an urban change in the coastal scenery. Also, a sustainable coastal management must be implemented in the study area.

The increasing use of personal protective equipment (PPE) as a sanitary measure against the new coronavirus (SARS-CoV-2) has become a significant source of many environmental risks. The majority of the governments enforce the use of PPE in public areas, such as beaches. Thus, the use and disposal of PPE have compromised most solid waste management strategies, ultimately leading to the occurrence of PPE polluting the marine environment. The present study aimed to monitor the PPE pollution associated with COVID-19 along the coastline of Agadir, Morocco. In parallel, the influence of the activities carried out in each sampled beach before and after the lockdown break was reported. Overall, a total number of 689 PPE items were identified, with a mean density of 1.13 × 10−5 PPE m−2 (0–1.21 × 10−4 PPE m−2). The majority of the PPE items found were face masks (96.81%), out of which 98.4% were surgical masks and 1.6% were reusable cloth masks. The most polluted sites were the beaches with recreational activities, followed by surfing, and fishing as the main activity. Importantly, PPE density increased significantly after lockdown measures. Additionally, the discarded PPE sampled in the supralittoral zone was higher than PPE recorded in the intertidal zone. This confirms that PPE items are driven by the beachgoers during their visit. PPE items are a source of microplastic and chemical pollutants, a substrate to invasive species colonization, and a potential threat of entanglement, ingestion, and/or infection among apex predators. In the specific case of Agadir beaches, significant efforts are required to work on the lack of environmental awareness and education. It is recommended to improve beach cleaning strategies and to penalize incorrect PPE disposal. Additional alternatives may be adopted, as the involvement of biodegradable materials in PPE manufacturing, recycling through pyrolysis, and encouraging reusable and washable masks., Graphical abstract Unlabelled Image

This paper presents a quantitative and qualitative diagnosis of the current state of marine litter along the northern coastline of Agadir, located on the central Atlantic coast of Morocco. For this, three beaches were surveyed: Taghazout beach, Aourir beach, and Anza beach. Litter densities were highest at Anza beach (D = 1.041 items/m2), followed by Aourir beach (D = 0.339 items/m2), and then Taghazout beach (D = 0.226 items/m2). Plastics represent 79% of all collected items, and they are mainly composed of caps/lids, food containers, other plastic, cigarette butts and filters, polystyrene pieces, small plastic bags, and drink bottles. Metal is the second litter item in number, followed by paper/cardboard, rubber, cloth/textile, wood, and glass/ceramic. The Clean Coast Index (CCI) shows a clean and moderately clean state in the Taghazout and Aourir beaches, while Anza beach is more polluted. The EA/NALG classification showed that all three beaches are classified as “D,” i.e., dirty or poor-quality beaches. Dendrogram analysis showed very highly polluted areas (Anza 1), highly polluted areas (Taghazout 4 and 5; Anza 2; Aourir 3), moderately polluted areas (Taghazout 1 and 2; Aourir 1), and lightly polluted areas (Taghazout 3). Based on the obtained results, we can conclude that tourism and recreational activities were the primary source of marine litter (over 50%), followed by fishing activity (25%). Efforts are necessary to improve the quality of beaches located on the central Atlantic coast of Morocco. The typology of solutions suggested in this work can be divided into four approaches: cleaning, prevention, mitigation, and the most important … behavior change.

This study was conducted to assess the physiological parameters of reproduction (sex ratio and gametogenic cycle), parasitism and biological indices (condition index and gonadal index) in Donax trunculus. Samples were collected monthly over two years (from 2016 to 2017) from three sites along the coast of Taghazout (in Southern Morocco) hosting the tourist resort Taghazout Bay. Five stages were depicted by histological examination of gonads: undifferentiated, developing, mature, spawning, and spent. The results of this histological study of the gonads of D. trunculus show that the reproductive cycle of this species has two periods: the first one is characterized by high sexual activity and extends from February to June and the second one corresponds to sexual rest and lasts from July to October. In all three stations and during both years, individuals in the undifferentiated stage (sexual rest) are encountered from July to October. Two spawning periods were observed: the first in March followed by a resumption of activity in April, and the second from May–June. Seasonal variations of the biological indices (GI and CI) were associated with the reproductive and nutritive status of bivalves. The study of parasitism by the trematode Bacciger Bacciger revealed that all the infected individuals were females in the sporocyst stage with a total prevalence between 0 and 9% in August and September respectively. Our results serve as a warning for future management measures and justify the necessity of taking into account the biology of the species in a particular area for better management of resources.

This present contribution examines by means of a discrete event and agent-based simulation the potential of a joint use of resources in the installation phase of offshore wind energy. To this end, wind farm projects to be installed simultaneously are being examined, the impact of weather restrictions on the processes of loading, transport and installation are also taken into consideration, and both the wind farm specific resource allocation and the approach of a resource pool or resource sharing, respectively, are being implemented. This study is motivated by the large number of wind farms that will be installed in the future and by the potential savings that might be realized through resource sharing. While, so far, the main driver of the resource sharing approach has been the end consumer market, it has been applied in more and more areas, even in relatively conservative industries such as logistics. After the presentation of the backgrounds and of the underlying methodology, and the description of the prior art in this context, the network of the offshore wind energy installation phase will be described. This is the basis for the subsequent determination of the savings potential of a shared resource utilization, which is determined by the performance indicators such as the total installation time and degree of utilization of the resources. The results of the simulation show that weather restrictions have a significant effect on the installation times and the usage times of the resources as well as on their degree of utilization. In addition, the resource sharing approach, has been identified to have significant savings potential for the offshore wind energy installation.

The study of the structure and the dynamics of populations exposed to environmental pollutants can be a useful investigative tool for finding the connections between different levels of biological organization Population dynamics on wedge clam, Donax trunculus is still unknown in Morocco. FiSAT software (FAO-ICLARM Stock Assessment Tools) was used for calculating population parameters of this species. The specimens of D. trunculus (Linnaeus, 1758) were collected monthly in the Agadir Marine Bay (South of Morocco) for two years (January 2016–December 2017) from three stations (S1, S2 and S3), which are directly exposed to eventual pollutants owing to the developing tourism resort Taghazout Bay. The study of the population dynamics of D. trunculus shows that the annual mean of density, biomass and condition index, presents significant seasonal variations depending on the physico-chemical parameters and the animal’s life cycle. The monitoring of age-class frequency distributions of D. trunculus individuals revealed a slighter difference at the three study stations. Asymptotic length (L ∞ ) was 37.96 mm and growth coefficient (K) was estimated at 1.93 year −1. Total mortality (Z) for D. trunculus was 3.30 year −1. Natural mortality (M) and fishing mortality (F) were 1.73 year−1 and 1.57 year − 1 respectively. Exploitation level (E) was computed as 0.48, indicating an optimum level of exploitation of D. trunculus in the coastal waters of Taghazout. It is well demonstrated that bimodal recruitment takes place twice a year; one in late summer–early autumn and the other in spring. The results of this study provide information on the health status of this ecosystem receiving Taghazout Bay project.

Field investigations on the population dynamics of Nereis diversicolor were carried out from January 2002 to December 2003 in the estuary of Oued Souss (southwestern Morocco) to determine the changes caused by setting up of a domestic and industrial wastewater purification plant (M'zar) before and after by the end of wastewater discharges in November 2002 on the structure of the ecosystem. Samples of N. diversicolor were collected monthly in the intertidal zone at low tide before (during 2002) and after (during 2003) the end of wastewater discharges. Separation of cohorts using the Algorithm EM method (McLachlan, G.J., Krishnan, T., 1997. The EM algorithm and extensions. Wiley Series in Probability and Statistics. Wiley, New York, 274 pp.) allowed determination of the growth rate (mm day −1 ) by cohort and the annual production. The data showed significant differences between populations of Nereis diversicolor before and after the end of wastewater discharges. During the wastewater discharge period (2002), the population had a mean annual density of 1992 ind m −2 , a mean annual biomass of 75.52 g DW m −2 and an annual secondary production of 141.3 g DW m −2 with a P / B ratio of 1.87. After the end of discharges (2003), density, biomass and secondary production decreased significantly. The annual averages for these parameters were 740 ind m −2 , 14.16 g DW m −2 and 23.83 g DW m −2 , respectively, with a P / B ratio of 1.68. The important decrease observed in density, biomass and secondary production of Nereis diversicolor may be attributed (a) to the environmental changes observed after the end of wastewater discharges in the estuary of Oued Souss, namely the increase of salinity and the decrease of organic matter content, and (b) to the migration of this species towards other areas.

The aim of this study was to assess aquatic environmental quality of Oued Souss (Agadir, Morocco). This estuary has been subjected for a long time to large amounts of sewage discharges and industrial effluents. Since November 2002, no waste outlets have been discharged in this site due to their connection to a wastewater purification plant. Firstly, we have compared metal tolerance of the annelid polychaete (Nereis diversicolor) originating from Oued Souss and a relatively clean site (Oualidia, Morocco). Secondly, we have evaluated with a multi-marker approach (acetylcholinesterase [AChE], glutathione-S-transferases [GSTs], catalase, thiobarbituric acid reactive substances [TBARs]) responses of worms to the pollution gradient. Results have shown that worms from Oued Souss have acquired tolerance to copper and zinc due to a long-term sub-lethal metal exposure and this metal tolerance was maintained in spite of the end of wastewater discharges in this site. Higher catalase, GSTs and TBARs values have been observed in worms from Oued Souss sampled before implantation of wastewater treatment. The multi-marker approach confirms that these worms have been submitted to various contaminants. In contrast, high inhibition in AChE activities measured in worms from Oued Souss could be explained by the continuous agricultural influence of nearest areas. The level of contamination was probably maintained since biomarker values were generally higher in worms from Oued Souss when compared to Oualidia.