BUSCADOR RECOLECTA

Dades primàries associades a l'article publicat: Garrabou, J., Gómez Gras, D., Ledoux, J.B. [et.al]. Collaborative Database to Track Mass Mortality Events in the Mediterranean Sea. Frontiers in Marine Science, 2019, vol. 6 art. núm. 707. Disponible a https://doi.org/10.3389/fmars.2019.00707, The data compiled in the MME-T-MEDNet dataset was gathered from published scientific papers, grey literature and technical reports using different searching strategies in ISI Web of Knowledge and Google Scholar using different sets of keywords (including those used in Rivetti et al. 2014 and Marba et al. 2015) as well as through contacts with researchers across the Mediterranean. The dataset comprises mass mortality events impacts observed at discrete events generally related to warming episodes across the Mediterranean. The dataset provides information about the year, season, geographic coordinates, protection status of the geographic location, species phylum, species name, the degree of mortality impact, depth range of the mortality and reported biotic and abiotic mortality drivers of the event, The Mass Mortality Events (MME-T-MEDNet) dataset compiles information reported on mass mortality events of species in the Mediterranean Sea affecting different organism dwelling in coastal ecosystems, We acknowledge the financial support by the Prince Albert II de Monaco Foundation (MIMOSA project nº 1983) and the project MPA-ADAPT funded by Interreg MED program (European Regional Development Fund)

Dades primàries associades a una comunicació a congrés presentada a CIRED 2019. 25th International Conference on Electricity Distribution: Madrid, 3-6 June 2019, The files are in CSV, no special software required to interpret the data, The dataset includes two files: one called 'demand', with the active power demand from 10 different households, in Watts units and hourly resolution, and another called 'generation', with the solar generation considering the current installed photovoltaic power in each household, in Watts units and hourly resolution. The total peak power installed is 30.5 kWp. The demand dataset was provided by the DSO (Distribution System Operator). No collection/generation work done by the researchers. The solar generation profile was download from PVGIS portal, considering the location and the installed peak power of each household. The study multiplies the data profiles (demand and generation) from the Dataset by different factors according to the scenario. Not other preprocessing than scaling the data. Energy consumption profiles from file 'demand.csv' correspond to the same households than the energy production profiles from file 'generation.csv'. For example, 'C1' column in 'demand.csv' and 'G1' column in 'generation.csv' correspond to consumption and generation profiles from Household 1, respectively. In the study the authors talk about two scenarios. The Scenario 1 considers the current demand profiles, from file 'demand.csv'. The Scenario 2, considers a future high electrification of households final demand, so the demand profiles in file 'demand.csv' are scaled by a factor of 14. In both scenarios, all generation profiles in 'generation.csv' are scaled by a factor depending on the total installed photovoltaic power, considering than the original generation profiles correspond to a total peak power of 30.5 kWp. The dataset contains the data collected from 0:00 am to 11:00 pm on July 1, 2018