For around two decades, artificial snow has been used by numerous winter sports resorts to ensure good snow cover at low altitude areas or more generally, to lengthen the skiing season. Biological additives derived from certain bacteria are regularly used to make artificial snow. However, the use of these additives has raised doubts concerning the potential impact on human health and the environment. In this context, the French health authorities have requested the French Agency for Environmental and Occupational Health Safety (Afsset) to assess the health risks resulting from the use of such additives. The health risk assessment was based on a review of the scientific literature, supplemented by professional consultations and expertise. Biological or chemical hazards from additives derived from the ice nucleation active bacterium Pseudomonas syringae were characterised. Potential health hazards to humans were considered in terms of infectious, toxic and allergenic capacities with respect to human populations liable to be exposed and the means of possible exposure. Taking into account these data, a qualitative risk assessment was carried out, according to four exposure scenarios, involving the different populations exposed, and the conditions and routes of exposure. It was concluded that certain health risks can exist for specific categories of professional workers (mainly snowmakers during additive mixing and dilution tank cleaning steps, with risks estimated to be negligible to low if workers comply with safety precautions). P. syringae does not present any pathogenic capacity to humans and that the level of its endotoxins found in artificial snow do not represent a danger beyond that of exposure to P. syringae endotoxins naturally present in snow. However, the risk of possible allergy in some particularly sensitive individuals cannot be excluded. Another important conclusion of this study concerns use of poor microbiological water quality to make artificial snow.
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http://dx.doi.org/10.1016/j.scitotenv.2010.01.009 | DOI Listing |
Sci Rep
January 2025
UNESCO Centre of Water Law, Policy & Science, University of Dundee, Dundee, UK.
Understanding snow and ice melt dynamics is vital for flood risk assessment and effective water resource management in populated river basins sourced in inaccessible high-mountains. This study provides an AI-enabled hybrid approach integrating glacio-hydrological model outputs (GSM-SOCONT), with different machine learning and deep learning techniques framed as alternative 'computational scenarios, leveraging both physical processes and data-driven insights for enhanced predictive capabilities. The standalone deep learning model (CNN-LSTM), relying solely on meteorological data, outperformed its counterpart machine learning and glacio-hydrological model equivalents.
View Article and Find Full Text PDFAm J Sports Med
January 2025
Integrative Neuromuscular Sport Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Background: The individual variation in on-snow performance outcomes after anterior cruciate ligament (ACL) reconstruction (ACLR) in elite alpine ski racers has not been reported and may be influenced by specific injury characteristics.
Purpose: To report the performance statistics of elite ski racers before and after ACLR and to identify surgical and athlete-specific factors that may be associated with performance recovery.
Study Design: Descriptive epidemiological study.
Environ Monit Assess
January 2025
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China.
Exploring the response relationship between civil war, population and land cover change is of great practical significance for social stability in Myanmar. However, the ongoing civil war in Myanmar hinders direct understanding of the situation on the ground, which in turn limits detailed study of the intricate relationship between the dynamics of the civil war and its impact on population and land. Therefore, this paper explores the response relationship between civil war conflict and population and land cover change in Myanmar from 2010 to 2020 from the perspective of remote sensing using the land cover data we produced, the open spatial demographics data, and the armed conflict location and event data project.
View Article and Find Full Text PDFData Brief
December 2024
Faculty of Civil Engineering and Geosciences, Department of Hydraulic Engineering, Delft University of Technology, Delft 2628 CN, the Netherlands.
A field campaign in the Vallunden lagoon in the Van Mijenfjorden on Spitsbergen was conducted to gather data on sea ice restoration by artificial flooding. Sea ice thickening was initiated by pumping sea water from below the first-year sea ice onto the surface without removing the covering snow layer. Part of the data was collected by four thermistor strings, two radiation sensors, and one anemometer.
View Article and Find Full Text PDFThe current investigation proposes a novel hybrid methodology for the diagnosis of the foot fractures. The method uses a combination of deep learning methods and a metaheuristic to provide an efficient model for the diagnosis of the foot fractures problem. the method has been first based on applying some preprocessing steps before using the model for the features extraction and classification of the problem.
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