111 research outputs found

    IMPAcT-RLS2: Indagine nazionale sulla salute e la sicurezza sul lavoro: il ruolo dei Rappresentanti dei Lavoratori per la Sicurezza

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    L’Indagine IMPAcT-RLS2 si inserisce nel più ampio programma di ricerca INSuLa2, la cui prima edizione, condotta nel 2014 e rivolta a tutti gli attori della prevenzione, ha approfondito aspetti della tutela della salute e sicurezza sul lavoro (SSL) secondo il punto di vista delle varie figure intervistate. La survey indirizzata ai Rappresentanti dei lavoratori per la sicurezza (RLS), focalizzata inizialmente su tre contesti regionali, è stata implementata grazie all’indagine IMPAcT-RLS, realizzata nel 2016, che ha coinvolto un campione di circa 2.100 soggetti, rappresentativo a livello nazionale, per dimensione aziendale e settore di attività economica. L’indagine ha evidenziato l’importanza di disporre di informazioni sempre più approfondite sul ruolo dei RLS e di monitorarne l’andamento nel tempo. Il presente studio ribadisce l’importanza di istituire rilevazioni periodiche e replicabili, finalizzate ad aumentare le conoscenze e la consapevolezza sui sistemi di prevenzione e promuovere interventi sempre più mirati per il miglioramento della tutela della SSL.The IMPAcT-RLS2 survey is part of a larger context of INSuLa2 research program; its first edition was conducted in 2014 and targeted to all prevention professionals, investigating occupational health and safety (OSH) protection issues perceived by the various professionals’ point of view. The survey addressed to Health and Safety Representatives (HS reps.), focused on three regional contexts, was further implemented in 2016 through the IMPAcT-RLS survey, which involved a sample representative at national level, by company size and economic activity sector consisting of about 2,100 subjects. The survey highlighted the importance of having ever more in-depth information on the role of HS reps. and monitoring their evolution over time. This study arises from the need to create periodic and replicable surveys, aimed at increasing knowledge and awareness of prevention systems and promoting increasingly targeted interventions for improving the protection of OS

    Reconstructing extreme AMOC events through nudging of the ocean surface: a perfect model approach

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    While the Atlantic Meridional Overturning Circulation (AMOC) is thought to be a crucial component of the North Atlantic climate, past changes in its strength are challenging to quantify, and only limited information is available. In this study, we use a perfect model approach with the IPSL-CM5A-LR model to assess the performance of several surface nudging techniques in reconstructing the variability of the AMOC. Special attention is given to the reproducibility of an extreme positive AMOC peak from a preindustrial control simulation. Nudging includes standard relaxation techniques towards the sea surface temperature and salinity anomalies of this target control simulation, and/or the prescription of the wind-stress fields. Surface nudging approaches using standard fixed restoring terms succeed in reproducing most of the target AMOC variability, including the timing of the extreme event, but systematically underestimate its amplitude. A detailed analysis of the AMOC variability mechanisms reveals that the underestimation of the extreme AMOC maximum comes from a deficit in the formation of the dense water masses in the main convection region, located south of Iceland in the model. This issue is largely corrected after introducing a novel surface nudging approach, which uses a varying restoring coefficient that is proportional to the simulated mixed layer depth, which, in essence, keeps the restoring time scale constant. This new technique substantially improves water mass transformation in the regions of convection, and in particular, the formation of the densest waters, which are key for the representation of the AMOC extreme. It is therefore a promising strategy that may help to better constrain the AMOC variability and other ocean features in the models. As this restoring technique only uses surface data, for which better and longer observations are available, it opens up opportunities for improved reconstructions of the AMOC over the last few decades
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