BUSCADOR RECOLECTA

Ozone concentrations in ambient air collected using low-cost sensor technologies, in the framework of EU project CAPTOR. Data collected during summer 2018 in NE Spain and N Italy. Sensors are metal-oxide. Data are calibrated using multiple linear regression, and validated against official reference data from each local air quality monitoring network. More details on the calibration and data validation may be found in A. Ripoll et al. / Science of the Total Environment 651 (2019) 1166–1179., European Commission: CAPTOR - Collective Awareness Platform for Tropospheric Ozone Pollution (688110), Peer reviewed

Ozone concentrations in ambient air collected using low-cost sensor technologies, in the framework of EU project CAPTOR. Data collected during summer 2017 in NE Spain and N Italy. Sensors are metal-oxide. Data are calibrated using multiple linear regression, and validated against official reference data from each local air quality monitoring network. More details on the calibration and data validation may be found in A. Ripoll et al. / Science of the Total Environment 651 (2019) 1166–1179., European Commission: CAPTOR - Collective Awareness Platform for Tropospheric Ozone Pollution (688110), Peer reviewed

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)

Data used in paper "A comparative study of calibration methods for low-cost ozone sensors in IoT platforms", submitted for publication. The data consists of: (i) raw data from three nodes with four MICS 2614 metal-oxide ozone sensors deployed in Spain, summer 2017, and (ii) raw data of five alphasense OX-B431 and NO2-B43F electro-chemical sensors, four deployed in Italy and one in Austria, summers 2017 and 2018. Moreover, we have added the calibrated data using four machine learning methods: Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR)., Data used in paper "A comparative study of calibration methods for low-cost ozone sensors in IoT platforms", submitted for publication. The data consists of: (i) raw data from three nodes with four MICS 2614 metal-oxide ozone sensors deployed in Spain, summer 2017, and (ii) raw data of five alphasense OX-B431 and NO2-B43F electro-chemical sensors, four deployed in Italy and one in Austria, summers 2017 and 2018. Moreover, we have added the calibrated data using four machine learning methods: Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR)., Peer reviewed