ESTCB - Escola Superior de Tecnologia
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Browsing ESTCB - Escola Superior de Tecnologia by contributor "Zanini , Andrea"
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- A geostatistical approach for mercury spatial patterns assessment in sediments in an old mining region: The Caveira Mine case study, PortugalPublication . Mota, Natália; Fonseca, Rita; Araújo, Joana; Isabel Margarida Horta Ribeiro Antunes; Valente, Teresa; Barroso, Ana; Araújo, Alexandre; Albuquerque, Maria Teresa; Zanini , Andrea; D'Oria, MarcoMercury pollution is significant in many former mining communities worldwide, including in developing countries. Anthropic contributions to environmental Hg pollution are mostly connected to fuel fossil emissions, industrial and mining activities. Among mining operations, gold exploration contributes to the highest Hg contamination rates, given the processes, widely used in the past, of mixing Hg with the gold containing ore, to separate this metal from the bulk impurities. This study, as part of the GeoMaTre project, an ongoing collaborative network (2021-2024) between the Polytechnic Institute of Castelo Branco and the University of Évora, Portugal, aimed to evaluate the potential risk of mercury pollution in stream sediments in the Caveira area, an abandoned Cu, Pb, Zn, Ag, and Au mine, included in the Iberian Pyrite Belt, at South Portugal. This mine corresponds to a Gossan developed on pyrite mineralization, with high gold and silver content at the official beginning of its exploitation, in 1863, having exhausted the reserves in these precious metals in the 1920s. Until the date of its abandonment (1966) the exploitation focused on the remaining metals (Cu, Pb, Zn) and S. Currently, the surrounding area of Caveira mine is essentially composed of areas of waste accumulation, from mining activity, with little or no vegetation. Thirty-three sediment samples were collected from within 0 to 10 cm depth, in a grid of 1Km x 1Km. Hg was determined in samples preserved at about 4ºC at the time of collection, through a mercury analyzer (NIC MA 3000) based on thermal decomposition, gold amalgamation, and cold vapor atomic absorption spectroscopy detection.
- Stream sediments pollution: A compositional baseline assessment at the Caveira mine, PortugalPublication . Araújo, Joana; Fonseca, Rita; Mota, Natália; Araújo, Alexandre; Antunes I.M.H.R.; Valente, Teresa; Barroso, Ana; Albuquerque, Maria Teresa; Zanini , Andrea; D'Oria, MarcoA high concentration of Potentially Toxic Elements (PTE) can affect ecosystem health. It is therefore essential that spatial trends of pollutants are assessed and controlled. River sediment pollution is widespread in mining communities around the world, including in developing countries. This study, as part of the GeoMaTre project, restoration of water bodies impacted by mine drainage, an ongoing collaborative project (2021-2024) between the Polytechnic Institute of Castelo Branco and the University of Évora, Portugal, aimed to evaluate the potential risk of PTEs pollution in stream sediments under the direct influence of Caveira mine, a Cu-Pb Zn-Ag-Au old mine included in the Iberian Pyrite Belt, South Portugal. Quantifying pollution implies first the understanding of pollution-free stream sediment. Often, this background, or pollution baseline, is undefined or only partially known. Given that the concentration of chemical elements is compositional, as the attributes vary together, a compositional approach was used aiming to find a compositional balance, based on Compositional Data (CoDa) principles. A dataset of 33 samples was collected from within 0 to 10 cm depth, in a grid of 1Km x 1Km and thirteen chemical elements, including PTEs of variable toxicity (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn, V) and major elements from lithogenic sources (Fe, Al), were analyzed in preservedsamples at about 4°C. The most extractable forms of metals (except for Hg) were obtained by partial digestion with aqua regia (HCl and HNO3) in a high-pressure microwave digestion unit, followed by ICP-OES analysis. Hg was analyzed determined by a mercury analyzer based on thermal decomposition, gold amalgamation, and cold vapor atomic absorption spectroscopy detection.
- Unpacking occupational health data in the tertiary sector. From spatial clustering to bayesian decision makingPublication . Pazo, María; Boente, Carlos; Albuquerque, M.T.D.; Roque, Natália; Gerassis, Saki; Taboada, Javier; Zanini , Andrea; D'Oria, MarcoThe health status of the service sector workforce is a great unknown for medical geography. Despite the advances carried out by spatial epidemiology to predict spatial patterns of disease incidence, there are important challenges unsolved. In particular, the main issue resides in the ability to effectively simplify and visually represent the problem domain, given the need to cover very different service activities and, at the same time, consider the impact of numerous emerging risk factors such as those stemming from bioclimatic and socioeconomic variables. This article proposes a new approach that allows to consider, simplify, prioritise and visualise multiple occupational health risk factors giving rise to not healthy workers. For that, it is used a twofold approach based on an innovative synergy between Bayesian machine learning and geostatistics, to analyse up to 74.401 occupational health surveillance tests gathered between 2012-2016 in Spain. This solution allows to extract relevant patterns over those risk factors that cannot be further discriminated in the Bayesian network, such as spine or limbs observations, depicting distribution maps of key differentiating variables computed by an ordinary kriging approach.