5 resultados para BASELINE CONCENTRATIONS

em Instituto Politécnico do Porto, Portugal


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Among organic pollutants existing in coastal areas, polycyclic aromatic hydrocarbons (PAHs) are of great concern due to their ubiquity and carcinogenic potential. The aim of this study was to evaluate the seasonal patterns of PAHs in the digestive gland and arm of the common octopus (Octopus vulgaris) from the Northwest Atlantic Portuguese coast. In the different seasons, 18 PAHs were determined and the detoxification capacity of the species was evaluated. Ethoxyresorufin O-deethylase (EROD) and ethoxycoumarin O-deethylase (ECOD) activities were measured to assess phase I biotransformation capacity. Individual PAH ratios were used for major source (pyrolytic/petrogenic) analysis. Risks for human consumption were determined by the total toxicity equivalence approach. Generally, low levels of PAHs were detected in the digestive gland and in the arm of octopus, with a predominance of low molecular over high molecular weight compounds. PAHs exhibited seasonality in the concentrations detected and in their main emission sources. In the digestive gland, the highest total PAH levels were observed in autumn possibly related to fat availability in the ecosystem and food intake. The lack of PAH elimination observed in the digestive gland after captivity could be possibly associated to a low biotransformation capacity, consistent with the negligible/undetected levels of EROD and ECOD activity in the different seasons. The emission sources of PAHs found in the digestive gland varied from a petrogenic profile observed in winter to a pyrolytic pattern in spring. In the arm, the highest PAH contents were observed in June; nevertheless, levels were always below the regulatory limits established for food consumption. The carcinogenic potential calculated for all the sampling periods in the arm were markedly lower than the ones found in various aquatic species from different marine environments. The results presented in this study give relevant baseline data for environmental monitoring of organic pollution in coastal areas.

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The most consumed squid species worldwide were characterized regarding their concentrations of minerals, fatty acids, cholesterol and vitamin E. Interspecific comparisons were assessed among species and geographical origin. The health benefits derived from squid consumption were assessed based on daily minerals intake and on nutritional lipid quality indexes. Squids contribute significantly to daily intake of several macro (Na, K, Mg and P) and micronutrients (Cu, Zn and Ni). Despite their low fat concentration, they are rich in long-chain omega-3 fatty acids, particularly docosahexaenoic (DHA) and eicosapentanoic (EPA) acids, with highly favorable ω-3/ω-6 ratios (from 5.7 to 17.7), reducing the significance of their high cholesterol concentration (140–549 mg/100 g ww). Assessment of potential health risks based on minerals intake, non-carcinogenic and carcinogenic risks indicated that Loligo gahi (from Atlantic Ocean), Loligo opalescens (from Pacific Ocean) and Loligo duvaucelii (from Indic Ocean) should be eaten with moderation due to the high concentrations of Cu and/or Cd. Canonical discriminant analysis identified the major fatty acids (C14:0, C18:0, C18:1, C18:3ω-3, C20:4ω-6 and C22:5ω-6), P, K, Cu and vitamin E as chemical discriminators for the selected species. These elements and compounds exhibited the potential to prove authenticity of the commercially relevant squid species.

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Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

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Demand response has gain increasing importance in the context of competitive electricity markets environment. The use of demand resources is also advantageous in the context of smart grid operation. In addition to the need of new business models for integrating demand response, adequate methods are necessary for an accurate determination of the consumers’ performance evaluation after the participation in a demand response event. The present paper makes a comparison between some of the existing baseline methods related to the consumers’ performance evaluation, comparing the results obtained with these methods and also with a method proposed by the authors of the paper. A case study demonstrates the application of the referred methods to real consumption data belonging to a consumer connected to a distribution network.

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Demand response is an energy resource that has gained increasing importance in the context of competitive electricity markets and of smart grids. New business models and methods designed to integrate demand response in electricity markets and of smart grids have been published, reporting the need of additional work in this field. In order to adequately remunerate the participation of the consumers in demand response programs, improved consumers’ performance evaluation methods are needed. The methodology proposed in the present paper determines the characterization of the baseline approach that better fits the consumer historic consumption, in order to determine the expected consumption in absent of participation in a demand response event and then determine the actual consumption reduction. The defined baseline can then be used to better determine the remuneration of the consumer. The paper includes a case study with real data to illustrate the application of the proposed methodology.