• Energy Research
• ES close
• Universidade Católica Portuguesa close

The interplay between metal contamination and climate change may exacerbate the negative impact on the soil microbiome and, consequently, on soil health and ecosystem services. We assessed the response of the microbial community of a heavy metal-contaminated soil when exposed to short-term (48 h) variations in air temperature, soil humidity or ultraviolet (UV) radiation in the absence and presence of Enchytraeus crypticus (soil invertebrate). Each of the climate scenarios simulated significantly altered at least one of the microbial parameters measured. Irrespective of the presence or absence of invertebrates, the effects were particularly marked upon exposure to increased air temperature and alterations in soil moisture levels (drought and flood scenarios). The observed effects can be partly explained by significant alterations in soil properties such as pH, dissolved organic carbon, and water-extractable heavy metals, which were observed for all scenarios in comparison to standard conditions. The occurrence of invertebrates mitigated some of the impacts observed on the soil microbial community, particularly in bacterial abundance, richness, diversity, and metabolic activity. Our findings emphasize the importance of considering the interplay between climate change, anthropogenic pressures, and soil biotic components to assess the impact of climate change on terrestrial ecosystems and to develop and implement effective management strategies.

This study develops a scale to measure wine tourism experiences and was tested in Portugal, in two of the main wine tourism centres: Porto and Madeira. The wine experience scale combines experience traits with the traditional approach to scales related to wine tourism. The development of the scale follows the most recognised validated procedures. Data were collected from a total of 647 international wine tourists in the wine cellars of the two main fortified wine tourism regions visiting areas: Porto and Madeira. Structural equation modelling (SEM-AMOS) was used as the main analysis and validation tool. The resulting 18-item wine experience scale comprises four major dimensions: (1) Wine storytelling, (2) wine tasting excitement, (3) wine involvement, and (4) winescape. All these showed reliable and validated indicators. This new scale presents a valid new tool to better measure and evaluate experiences in a wine tourism setting. This study offers a broad range of use for academics, managers, planners, and practitioners. It shows how a new measurement tool focused on the wine tourism experience in terms of several outcomes and applications, addressing important practical managerial implications, can have an impact on academic research. Most previous tourism scales still fail to measure the specifics of wine settings. This is the first scale that comprises the dimensions of experience with wine senses, applied in a relevant wine destination where research is still limited. The results are relevant in boosting the increasingly recognized awareness of Portugal as wine tourism, as well as bringing experience scales to the body of knowledge.

The benefits for specific health impacts related to air and water quality were measured in simultaneous contingent valuation surveys conducted in five different European countries. Consistent inter-country differences in willingness to pay to avoid ill health episodes could not be explained by measurable differences in individual characteristics. International transfer of unit values resulted in an average transfer error of 38%. Accounting for measurable differences among countries in health status, income and other demographic measures, either through ad hoc adjustments to the transferred values or through value function transfer, did not improve transfer performance.

Abstract Nannochloropsis oculata is naturally rich in eicosapentaenoic acid (EPA). To turn this microalga into an economically viable source for commercial applications, extraction efficiency must be achieved. Pursuing this goal, emerging technologies such as high hydrostatic pressure (HHP) and moderate electric fields (MEF) were tested, aiming to increase EPA accessibility and subsequent extraction yields. The innovative approach used in this study combined these technologies and associated tailored, less hazardous different solvent mixtures (SM) with distinct polarity indexes. Although the classical Folch SM with chloroform: methanol (PI 4.4) provided the highest yield concerning total lipids (166.4 mglipid/gbiomass), diethyl ether: ethanol (PI 3.6) presented statistically higher values in terms of EPA per biomass, corresponding to 1.3-fold increase. When SM were used in HHP and MEF, neither technology independently improved EPA extraction yields, although the sequential combination of technologies did result in 62% increment in EPA extraction. Overall, the SM and extraction methodologies tested (HHP—200 MPa, 21 °C, 15 min, followed by MEF processing at 40 °C, 15 min) enabled increased EPA extraction yields from wet N. oculata biomass. These findings are of high relevance for the food and pharmaceutical industries, providing viable alternatives to the “classical” extraction methodologies and solvents, with increased yields and lower environmental impact. Key points • Et2O: EtOH is a less toxic and more efficient alternative to Folch solvent mixture • HHP or MEF per se was not able to significantly increase EPA extraction yield • Combinations of HHP and MEF technologies increased both lipids and EPA yields Graphical abstract

In the current work, we study the capacity of 30 peptones obtained by enzyme proteolysis of ten discarded fish species (hake, megrim, red scorpionfish, pouting, mackerel, gurnard, blue whiting, Atlantic horse mackerel, grenadier, and boarfish) to support the growth and metabolite production of four lactic acid bacteria (LAB) of probiotic and technological importance. Batch fermentations of Lactobacillus plantarum, L. brevis, L. casei, and Leuconostoc mesenteroides in most of the media formulated with fish peptones (87% of the cases) led to similar growths (quantified as dry-weight biomass and viable cells) and metabolites (mainly lactic acid) than in commercial control broth (MRS). Comparisons among cultures were performed by means of the parameters obtained from the mathematical fittings of experimental kinetics to the logistic equation. Modelling among experimental and predicted data from each bioproduction was generally accurate. A simple economic assessment demonstrated the profitability achieved when MRS is substituted by media formulated with fish discards: a 3–4-fold reduction of costs for LAB biomass, viable cells formation, and lactic and acetic acid production. Thus, these fish peptones are promising alternatives to the expensive commercial peptones as well as a possible solution to valorize discarded fish biomasses and by-products.

[EN] Current approaches for risk management in energy market participation mostly refer to portfolio optimization for long-term planning, and stochastic approaches to deal with uncertainties related to renewable energy gen- eration and market prices variation. Risk assessment and management as integrated part of actual market ne- gotiation strategies is lacking from the current literature. This paper addresses this gap by proposing a novel model for decision support of players’ strategic participation in electricity market negotiations, which considers risk management as a core component of the decision-making process. The proposed approach addresses the adaptation of players’ behaviour according to the participation risk, by combining the two most commonly used approaches of forecasting in a company’s scope: the internal data analysis, and the external, or sectorial, data analysis. The internal data analysis considers the evaluation of the company’s evolution in terms of market power and profitability, while the sectorial analysis addresses the assessment of the competing entities in the market sector using a K-Means-based clustering approach. By balancing these two components, the proposed model enables a dynamic adaptation to the market context, using as reference the expected prices from com- petitor players, and the market price prediction by means of Artificial Neural Networks (ANN). Results under realistic electricity market simulations using real data from the Iberian electricity market operator show that the proposed approach is able to outperform most state-of-the-art market participation strategies, reaching a higher accumulated profit, by adapting players’ actions according to the participation risk.