To study the evolution of ochratoxin A (OTA) content from must to wine during the making of Port Wine, grapes from the five most common varieties of Port Wine were harvested and combined in equal percentages in order to perform microvinifications. Three sets of assays were studied: a blank (A), where the most common Port Wine-making process was used; in the second (B), a solution of OTA was added to the initial must; in the third (C), the grapes were aspersed with an inoculating solution of OTA-producing fungi. Samples were collected, in duplicate, on four different occasions throughout the process. The influence of the addition of SO2 to the must was also assessed in each set. The quantification of OTA was based on the standard reference method for wines (European Standard prEN 14133), which includes clean-up via immunoaffinity columns and HPLC with fluorescence detection. The limits of detection were 0.076 microg/l for wine and 0.114 microg/l for must. The method was validated by assessing the precision, accuracy and by obtaining an estimate of the global uncertainty. Overall, the levels of OTA observed during the vinifications dropped by up to 92%, and no grapes used in this work were contaminated naturally.

There is an increasing demand for sea cucumbers, for human consumption, mainly from Asian markets and, as a consequence, NE-Atlantic species are now new targets for exploitation and exportation. Holothuria mammata is one of the most valuable species in Europe. However, the lack of historical economic interest in this species in most European countries has also led to a lack of studies concerning biological and ecological aspects on wild populations and this is a major issue for stock management. This study aims to determine the temporal and spatial patterns of distribution of H. mammata, considering its abundance and demographic structure in a NE-Atlantic area, SW Portugal, as a function of environmental conditions. For that, a population from a marine protected area was followed for 1 year at 1.5-month intervals. Throughout the coastal area, six sites were selected and at each sampling campaign three random transects per site and substrate (rock and sand) in which all H. mammata individuals were counted and measured. For each site and survey several environmental parameters of interest, from the water column, the sediment and substrate cover, were also measured. Generalized Linear Models were used to model the spatial and temporal distribution of the species according to environmental conditions, to determine the species’ habitat preferences. The distribution models indicate that abiotic and biotic parameters of the water column are not the main drivers shaping the distribution of H. mammata. The species has a patchy distribution, and its habitat preferences depend on environmental stability, the presence of shelter and habitat complexity, which is more important for smaller, more vulnerable, individuals, while bigger size classes tend to venture more into less stable environments in an opportunistic fashion. The knowledge of these population traits is determinant to develop stock management measures, which are now urgent to prevent the depletion of commercial sea cucumber populations in the NE-Atlantic. Sustainable fisheries policies should be developed and start by considering to delimit fishing areas and periods, considering the species spatial and temporal distribution patterns.

Abstract. The digital terrain model (DTM), the representation of earth's surface at regularly spaced intervals, is the first input in the computational modelling of atmospheric flows. The ability of computational meshes based on high- (2 m; airborne laser scanning, ASL), medium- (10 m; military maps, Mil) and low-resolution (30 m; Shuttle Radar Topography Mission, SRTM) DTMs to replicate the Perdigão experiment site was appraised in two ways: by their ability to replicate the two main terrain attributes, elevation and slope, and by their effect on the wind flow computational results. The effect on the flow modelling was evaluated by comparing the wind speed, wind direction and turbulent kinetic energy using VENTOS®/2 at three locations, representative of the wind flow in the region. It was found that the SRTM was not an accurate representation of the Perdigão site. A 40 m mesh based on the highest-resolution data yielded an elevation error of less than 1.4 m and an RMSE of less than 2.5 m at five reference points compared to 5.0 m in the case of military maps and 7.6 m in the case of the SRTM. Mesh refinement beyond 40 m yielded no or insignificant changes on the flow field variables, wind speed, wind direction and turbulent kinetic energy. At least 40 m horizontal resolution – threshold resolution – based on topography available from aerial surveys is recommended in computational modelling of the flow over Perdigão.

a b s t r a c tIn the latest years the wind energy sector experienced an exponential growth all over the world. What started as a deployment of onshore projects, soon moved to offshore and, more recently to the urban environment within the context of smart cities and renewable micro-generation. However, urban wind projects using micro turbines do not have enough profit margins to enable the setup of comprehensive and expensive measurement campaigns, a standard procedure for the deployment of large wind parks. To respond to the wind assessment needs of the future smart cities a new and simple methodology for urban wind resource assessment was developed. This methodology is based on the construction of a surface involving a built area in order to estimate the wind potential by treating it as very complex orography. This is a straightforward methodology that allows estimating the sustainable urban wind potential, being suitable to map the urban wind resource in large areas. The methodology was applied to a case study and the results enabled the wind potential assessment of a large urban area being consistent with experimental data obtained in the case study area, with maximum deviations of the order of 10% (mean wind speed) and 20% (power density).

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