Contamination by Coal Dust in the Neighborhood of the Tarragona Harbor (Catalonia, Spain): A Preliminary Study

Microplastics levels, size, morphology and composition in marine water, sediments and sand beaches. Case study of Tarragona coast (western Mediterranean)

Mediterranean Sea has been proposed as the sixth greatest accumulation zone for marine litter and the most affected regarding to microplastics (MPs). Tarragona (Catalonia, NE Spain) coastal region suffers high pressure due to urbanization, tourism, industrial harbour and petrochemical/plastic industries. The present study aims to quantify and characterize in size, morphology and composition the MPs present in sandy beaches, marine sediments, and surface seawaters of Tarragona coastal region. MPs mean abundance were 1.30 items/m³ in surface seawaters, 32.4 items/kg in marine sediments, and 10.7 items/kg in sandy beaches. Polyester fibres were dominant MPs in bottom sediments and seawater meanwhile polyethylene and polypropylene fragments were the main MPs in beaches. The fibres balls associated with bottom sediments, organic matter and plankton were abundant, masking the real quantity of fibres in each reservoir. The abundance by volume of seawater MPs was higher to those found in oceanic areas and similar to other areas of Mediterranean Sea, corroborating that Western Mediterranean Sea as a region of MPs accumulation. MPs composition and abundance suggested the input of numerous land-base-sources, WWTP (wastewater treatment plants) effluents discharges, and emissaries as the most important. Marine MPs pollution were studied from an integrative point of view, that includes superficial sea water, sand from beaches and sediments. The dynamics of MPs in Tarragona coast were characterized by seawater as the media that receive and facilitate dispersion and fragmentation. The shoreline acts as an intermediate reservoir with constant weathering and active exchange with seawater surface and the sediments acts as a significant sink for medium MPs sizes. It is necessary to develop protocols and guidelines for MPs analysis to obtain harmonized and comparable results.

Comparison of Support Vector Machines and Random Forests for Corine Land Cover Mapping

Land cover information is essential in European Union spatial management, particularly that of invasive species, natural habitats, urbanization, and deforestation; therefore, the need for accurate and objective data and tools is critical. For this purpose, the European Union’s flagship program, the Corine Land Cover (CLC), was created. Intensive works are currently being carried out to prepare a new version of CLC+ by 2024. The geographical, climatic, and economic diversity of the European Union raises the challenge to verify various test areas’ methods and algorithms. Based on the Corine program’s precise guidelines, Sentinel-2 and Landsat 8 satellite images were tested to assess classification accuracy and regional and spatial development in three varied areas of Catalonia, Poland, and Romania. The method is dependent on two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM). The bias of classifications was reduced using an iterative of randomized training, test, and verification pixels. The ease of the implementation of the used algorithms makes reproducing the results possible and comparable. The results show that an SVM with a radial kernel is the best classifier, followed by RF. The high accuracy classes that can be updated and classes that should be redefined are specified. The methodology’s potential can be used by developers of CLC+ products as a guideline for algorithms, sensors, and the possibilities and difficulties of classifying different CLC classes.

Obesity associated with coal ash inhalation triggers systemic inflammation and oxidative damage in the hippocampus of rats

People with large amounts of adipose tissue are more vulnerable and more likely to develop diseases where oxidative stress and inflammation play a pivotal role, than persons with a healthy weight. Atmospheric contamination is a reality to which a large part of the worldwide population is exposed. Half of today's global electrical energy is derived from coal. Each organism, in its complexity, responds in different ways to dietary compounds and air pollution. The objective of this study was to investigate the effects of obesity and coal ash inhalation within the parameters of oxidative damage and inflammation in different regions of the brain of rats. A diet containing high-fat concentration was administered chronically to rats, along with exposure to coal ash, simulating the contamination that occurs daily throughout human life. High-resolution transmission electron microscopy was performed to identify the particles present in coal ash samples. Our results demonstrated that obese rats exposed to coal ash inhalation were more affected by oxidative damage with subsequent systemic inflammation in the hippocampus. Since there is an inflammatory predisposition caused by obesity, the inhalation of nanoparticles increases the levels of free radicals, resulting in systemic inflammation and oxidative damage, which can lead to chronic neurodegeneration.