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Research data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 13 Apr 2022Publisher:Dryad Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; Xie, Shuyu; Gao, Kunshan;The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 European UnionLes conditions géothermiques souterraines, quelle que soit la position des aquifères, sont montrées avec des cartes géothermiques appropriées. Cette carte représente les lignes de température attendues à une profondeur de 3 000 m de la carte de la distribution spatiale de la température attendue à une profondeur de 3 000 m (carte géothermique), qui est faite avec des données de 214 forages. Il est fabriqué sur la base des températures mesurées dans des puits accessibles dans tout le pays. Cependant, puisque le champ de température dépend de la composition géologique en profondeur et des caractéristiques tectoniques, le cours des isothermes est le résultat de nombreuses influences telles que la conductivité thermique des roches, la perméabilité et la fissuration des roches, qui se reflètent toutes dans les températures mesurées des puits. À cette profondeur, la chaleur radiogénique dans les roches a également une influence mineure. La répartition des puits, utiles pour les mesures de température, est très inégale et varie en profondeur. Après des températures à une profondeur de 3 000 m, il y a une anomalie positive plus forte dans la partie nord-est de la Slovénie, de la ligne Maribor-Rogatec à l’est, alors qu’il n’y a pas d’anomalie dans la partie orientale du bassin de Krško. Dans la partie nord-est du pays, cela est dû à la croûte terrestre plus mince et au flux de chaleur conductif plus élevé du manteau terrestre. Ailleurs, les températures sont beaucoup plus basses. Las condiciones geotérmicas subterráneas, independientemente de la posición de los acuíferos, se muestran con mapas geotérmicos adecuados. Este mapa representa las líneas de temperatura esperadas a una profundidad de 3 000 m del mapa de la distribución espacial de la temperatura esperada a una profundidad de 3 000 m (Mapa Geotérmico), que se realiza con datos de 214 pozos. Se realiza sobre la base de temperaturas medidas en pozos accesibles en todo el país. Sin embargo, dado que el campo de temperatura depende de la composición geológica en profundidades y características tectónicas, el curso de las isotermas es el resultado de numerosas influencias, como la conductividad térmica de las rocas, la permeabilidad y el agrietamiento de las rocas, todas las cuales se reflejan en temperaturas bien medidas. A esta profundidad, el calor radiogénico en las rocas también tiene una influencia menor. La distribución de los pozos, que fueron útiles para las mediciones de temperatura, es muy desigual y varía en profundidad. Después de temperaturas a una profundidad de 3 000 m, hay una anomalía positiva más fuerte en la parte noreste de Eslovenia, desde la línea Maribor-Rogatec hacia el este, mientras que no hay anomalía en la parte oriental de la cuenca de Krško. En la parte noreste del país, esto se debe a la corteza terrestre más delgada y al mayor flujo de calor conductor del manto de la Tierra. En otros lugares, las temperaturas son mucho más bajas. Die unterirdischen Geothermiebedingungen, unabhängig von der Lage der Grundwasserleiter, werden mit geeigneten geothermischen Karten dargestellt. Diese Karte stellt die erwarteten Temperaturlinien in einer Tiefe von 3 000 m von der Karte der räumlichen Verteilung der erwarteten Temperatur in einer Tiefe von 3 000 m (Geothermiekarte) dar, die mit Daten aus 214 Bohrlöchern erstellt wird. Es wird auf der Grundlage der gemessenen Temperaturen in zugänglichen Brunnen im ganzen Land gemacht. Da das Temperaturfeld jedoch von der geologischen Zusammensetzung in Tiefen und tektonischen Eigenschaften abhängt, ist der Verlauf der Isothermen das Ergebnis zahlreicher Einflüsse wie Wärmeleitfähigkeit von Gesteinen, Durchlässigkeit und Rissbildung von Gesteinen, die alle in gemessenen Brunnentemperaturen reflektiert werden. In dieser Tiefe hat auch radiogene Hitze in Gesteinen einen geringen Einfluss. Die Verteilung der Brunnen, die für Temperaturmessungen nützlich waren, ist sehr ungleichmäßig und variiert in der Tiefe. Nach Temperaturen in einer Tiefe von 3 000 m gibt es eine stärkere positive Anomalie im nordöstlichen Teil Sloweniens, von der Linie Maribor-Rogatec nach Osten, während es im östlichen Teil des Krško-Beckens keine Anomalie gibt. Im Nordosten des Landes ist dies auf die dünnere Erdkruste und die höhere leitfähige Wärmeströmung aus dem Erdmantel zurückzuführen. Anderswo sind die Temperaturen viel niedriger. Le condizioni geotermiche sotterranee, indipendentemente dalla posizione delle falde acquifere, sono mostrate con adeguate mappe geotermiche. Questa mappa rappresenta le linee di temperatura previste ad una profondità di 3 000 m dalla mappa della distribuzione spaziale della temperatura prevista ad una profondità di 3 000 m (Carta geotermica), che è fatta con i dati di 214 pozzi. È realizzato sulla base delle temperature misurate in pozzi accessibili in tutto il paese. Tuttavia, poiché il campo di temperatura dipende dalla composizione geologica in profondità e caratteristiche tettoniche, il decorso delle isoterme è il risultato di numerose influenze come la conducibilità termica delle rocce, la permeabilità e la fessura delle rocce, che si riflettono tutte in temperature misurate bene. A questa profondità, anche il calore radiogenico nelle rocce ha un'influenza minore. La distribuzione dei pozzi, utili per le misurazioni della temperatura, è molto irregolare e varia in profondità. Dopo temperature a una profondità di 3 000 m, c'è un'anomalia positiva più forte nella parte nord-orientale della Slovenia, dalla linea Maribor-Rogatec a est, mentre non vi è alcuna anomalia nella parte orientale del bacino di Krško. Nella parte nord-orientale del paese, questo è dovuto alla crosta terrestre più sottile e al più alto flusso di calore conduttivo dal mantello terrestre. Altrove, le temperature sono molto più basse. De ondergrondse geothermische omstandigheden, ongeacht de positie van de watervoerende lagen, worden weergegeven met geschikte geothermische kaarten. Deze kaart geeft de verwachte temperatuurlijnen weer op een diepte van 3 000 m van de kaart van de ruimtelijke verdeling van de verwachte temperatuur op een diepte van 3 000 m (Geothermiekaart), die wordt gemaakt met gegevens van 214 boorgaten. Het wordt gemaakt op basis van gemeten temperaturen in toegankelijke putten in het hele land. Aangezien het temperatuurveld echter afhankelijk is van de geologische samenstelling in diepten en tektonische kenmerken, is het verloop van isothermen het resultaat van talrijke invloeden zoals thermische geleidbaarheid van gesteenten, doorlaatbaarheid en kraken van gesteenten, die allemaal worden weerspiegeld in gemeten goedtemperaturen. Op deze diepte heeft radiogene warmte in rotsen ook een kleine invloed. De verdeling van putten, die nuttig waren voor temperatuurmetingen, is zeer ongelijk en varieert in diepte. Na temperaturen op een diepte van 3 000 m is er een sterkere positieve anomalie in het noordoosten van Slovenië, van de lijn Maribor-Rogatec naar het oosten, terwijl er geen anomalie is in het oostelijke deel van het Krško-bekken. In het noordoosten van het land is dit te wijten aan de dunnere aardkorst en de hogere geleidende warmtestroom uit de mantel van de aarde. Elders zijn de temperaturen veel lager. Οι υπόγειες γεωθερμικές συνθήκες, ανεξάρτητα από τη θέση των υδροφόρων οριζόντων, παρουσιάζονται με κατάλληλους γεωθερμικούς χάρτες. Ο χάρτης αυτός αναπαριστά τις αναμενόμενες γραμμές θερμοκρασίας σε βάθος 3 000 m από τον χάρτη της χωρικής κατανομής της αναμενόμενης θερμοκρασίας σε βάθος 3 000 m (Γεωθερμικός Χάρτης), ο οποίος γίνεται με δεδομένα από 214 γεωτρήσεις. Γίνεται με βάση τις μετρούμενες θερμοκρασίες σε προσβάσιμα πηγάδια σε όλη τη χώρα. Ωστόσο, δεδομένου ότι το πεδίο θερμοκρασίας εξαρτάται από τη γεωλογική σύνθεση σε βάθη και τεκτονικά χαρακτηριστικά, η πορεία των ισοθερμικών είναι το αποτέλεσμα πολυάριθμων επιδράσεων όπως η θερμική αγωγιμότητα των πετρωμάτων, η διαπερατότητα και η ρωγμή των πετρωμάτων, οι οποίες αντανακλώνται σε μετρημένες θερμοκρασίες φρεατίων. Σε αυτό το βάθος, η ραδιογενής θερμότητα στους βράχους έχει επίσης μια μικρή επιρροή. Η κατανομή των φρεάτων, τα οποία ήταν χρήσιμα για μετρήσεις θερμοκρασίας, είναι πολύ άνιση και ποικίλλει σε βάθος. Μετά από θερμοκρασίες σε βάθος 3000 μέτρων, υπάρχει μια ισχυρότερη θετική ανωμαλία στο βορειοανατολικό τμήμα της Σλοβενίας, από τη γραμμή Maribor-Rogatec προς τα ανατολικά, ενώ δεν υπάρχει ανωμαλία στο ανατολικό τμήμα της λεκάνης Krško. Στο βορειοανατολικό τμήμα της χώρας, αυτό οφείλεται στον λεπτότερο φλοιό της Γης και την υψηλότερη αγώγιμη ροή θερμότητας από τον μανδύα της Γης. Αλλού, οι θερμοκρασίες είναι πολύ χαμηλότερες. The underground geothermal conditions can be presented, irrespective of the aquifers' position, with the appropriate geothermal maps. This map represents the expected temperature lines at a depth of 3000 m and is derived from Geothermal map - Expected temperatures at a depth of 3000 m, which is made with data from 214 boreholes. It is made on the basis of measured temperatures in accessible boreholes throughout the country. However, since the temperature field depends on the geological structure in the depths and tectonic characteristics, the course of the isotherms is a result of many influences, such as thermal conductivity of rocks, permeability and fracturing of rocks, all of which are reflected in the measured temperatures in boreholes. In this depth also a radiogenic heat production in the rocks has smaller influence. The distribution of boreholes, which were useful for the measurement of temperature, is very uneven and different as regard the depths. Following the expected temperatures at a depth of 3000 m a stronger positive anomaly is in the northeastern part of Slovenia, from the line Maribor-Rogatec to the east, while in the eastern part of the Krka basin there is no anomaly any more. In the northeastern part of the country the anomaly is the result of the thinning of the Earth's crust and greater conductive heat flow from the Earth's mantle. Elsewhere temperatures are much lower. Condițiile geotermale subterane, indiferent de poziția acviferelor, sunt afișate cu hărți geotermale adecvate. Această hartă reprezintă liniile de temperatură așteptate la o adâncime de 3 000 m de la harta distribuției spațiale a temperaturii așteptate la o adâncime de 3 000 m (Harta geotermală), care este realizată cu date de la 214 găuri de foraj. Se face pe baza temperaturilor măsurate în puțuri accesibile din întreaga țară. Cu toate acestea, deoarece câmpul de temperatură depinde de compoziția geologică în adâncimi și caracteristici tectonice, cursul izotermelor este rezultatul a numeroase influențe, cum ar fi conductivitatea termică a rocilor, permeabilitatea și fisurarea rocilor, toate acestea fiind reflectate în temperaturile sondei măsurate. La această adâncime, căldura radiogenică din roci are, de asemenea, o influență minoră. Distribuția puțurilor, care au fost utile pentru măsurarea temperaturii, este foarte inegală și variază în profunzime. După temperaturi la o adâncime de 3 000 m, există o anomalie pozitivă mai puternică în partea de nord-est a Sloveniei, de la linia Maribor-Rogatec la est, în timp ce nu există nicio anomalie în partea estică a bazinului Krško. În partea de nord-est a țării, acest lucru se datorează scoarței mai subțiri a Pământului și fluxului de căldură mai mare din mantaua Pământului. În alte părți, temperaturile sunt mult mai scăzute. Il-kundizzjonijiet ġeotermali taħt l-art, irrispettivament mill-pożizzjoni tal-akwiferi, huma murija b’mapep ġeotermali adattati. Din il-mappa tirrappreżenta l-linji tat-temperatura mistennija f’fond ta’ 3 000 m mill-mappa tad-distribuzzjoni spazjali tat-temperatura mistennija f’fond ta’ 3 000 m (Mappa Ġeotermali), li hija magħmula b’data minn 214 boreholes. Dan isir fuq il-bażi ta’ temperaturi mkejla fi bjar aċċessibbli fil-pajjiż kollu. Madankollu, peress li l-kamp tat-temperatura jiddependi fuq il-kompożizzjoni ġeoloġika fil-fond u l-karatteristiċi tettoniċi, il-kors tal-isotermi huwa r-riżultat ta’ bosta influwenzi bħall-konduttività termali tal-blat, il-permeabilità u l-qsim tal-blat, li kollha huma riflessi f’temperaturi mkejla tal-bjar. F’dan il-fond, sħana radjoġenika fil-blat għandha wkoll influwenza minuri. Id-distribuzzjoni tal-bjar, li kienu utli għall-kejl tat-temperatura, hija irregolari ħafna u tvarja fil-fond. Wara temperaturi f’fond ta’ 3 000 m, hemm anomalija pożittiva aktar qawwija fil-parti tal-Grigal tas-Slovenja, mil-linja Maribor-Rogatec lejn il-Lvant, filwaqt li ma hemm l-ebda anomalija fil-parti tal-Lvant tal-baċir ta’ Krško. Fil-parti tal-grigal tal-pajjiż, dan huwa dovut għall-qoxra tad-Dinja irqaq u l-fluss tas-sħana konduttiv ogħla mill-mantell tad-Dinja. Band’oħra, it-temperaturi huma ħafna aktar baxxi. As condições geotérmicas subterrâneas, independentemente da posição dos aquíferos, são mostradas com mapas geotérmicos adequados. Este mapa representa as linhas de temperatura esperadas a uma profundidade de 3 000 m do mapa da distribuição espacial da temperatura esperada a uma profundidade de 3 000 m (Mapa geotérmico), que é feita com dados de 214 furos. É feita com base nas temperaturas medidas em poços acessíveis em todo o país. No entanto, uma vez que o campo de temperatura depende da composição geológica em profundidades e características tectónicas, o curso das isotérmicas é o resultado de inúmeras influências, tais como condutividade térmica das rochas, permeabilidade e rachadura de rochas, todas elas refletidas em temperaturas medidas. A esta profundidade, o calor radiogénico nas rochas também tem uma pequena influência. A distribuição dos poços, que foram úteis para medições de temperatura, é muito desigual e varia em profundidade. Depois de temperaturas a uma profundidade de 3 000 m, há uma anomalia positiva mais forte na parte nordeste da Eslovénia, da linha Maribor-Rogatec ao leste, enquanto não há anomalia na parte oriental da bacia de Krško. Na parte nordeste do país, isto é devido à crosta mais fina da Terra e ao maior fluxo de calor condutor do manto da Terra. Em outros locais, as temperaturas são muito mais baixas.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:The Smithsonian Institution Authors: Paton, Steve;doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
Monthly and daily summary from the Fortuna Station (Centro de Investigaciones Jorge L. Arauz)Location: 8° 43.340'N, 82° 14.241'WParameters: air temperature, wind speed and direction, precipitation, solar radiation (pyranometer)Located in the highlands of the Chiriqui Province, in western Panama.There are three sensor locations: north clearing, south clearing, and a 15m tower.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | PARIS REINFORCEEC| PARIS REINFORCEDoukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; Nikas, Alexandros;This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022 European UnionPublisher:kanton-thurgau Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики O conjunto de dados inclui o consumo final de energia no setor da construção para calor ambiente e água quente de acordo com as fontes de energia no cantão de Thurgau a partir de 2015. A energia final é a energia que chega ao consumidor final. O consumo final de energia no setor da construção inclui o consumo de edifícios residenciais e de serviços — excluindo edifícios industriais e agrícolas — no território do cantão de Thurgau.Fonte de dados: Escritório de Energia O conjunto de dados inclui o consumo final de energia no setor da construção para calor ambiente e água quente de acordo com as fontes de energia no cantão de Thurgau a partir de 2015. A energia final é a energia que chega ao consumidor final. O consumo final de energia no setor da construção inclui o consumo de edifícios residenciais e de serviços — excluindo edifícios industriais e agrícolas — no território do cantão de Thurgau.Fonte de dados: Escritório de Energia Súbor údajov zahŕňa konečnú spotrebu energie v stavebníctve na vykurovanie miestností a teplú vodu podľa zdrojov energie v kantóne Thurgau od roku 2015. Konečná energia je energia, ktorá sa dostáva ku konečnému spotrebiteľovi. Konečná spotreba energie v stavebníctve zahŕňa spotrebu bytových a servisných budov – okrem priemyselných a poľnohospodárskych budov – na území kantónu Thurgau.Zdroj údajov: Úrad pre energetiku Súbor údajov zahŕňa konečnú spotrebu energie v stavebníctve na vykurovanie miestností a teplú vodu podľa zdrojov energie v kantóne Thurgau od roku 2015. Konečná energia je energia, ktorá sa dostáva ku konečnému spotrebiteľovi. Konečná spotreba energie v stavebníctve zahŕňa spotrebu bytových a servisných budov – okrem priemyselných a poľnohospodárskych budov – na území kantónu Thurgau.Zdroj údajov: Úrad pre energetiku Datasetet omfattar den slutliga energianvändningen inom byggsektorn för rumsvärme och varmvatten enligt energikällor i Thurgaus kanton från 2015. Den slutliga energin är den energi som når slutkonsumenten. Den slutliga energianvändningen inom byggsektorn omfattar förbrukningen av bostads- och servicebyggnader – utom industri- och jordbruksbyggnader – i kantonen Thurgau.Datakälla: Energikontoret Datasetet omfattar den slutliga energianvändningen inom byggsektorn för rumsvärme och varmvatten enligt energikällor i Thurgaus kanton från 2015. Den slutliga energin är den energi som når slutkonsumenten. Den slutliga energianvändningen inom byggsektorn omfattar förbrukningen av bostads- och servicebyggnader – utom industri- och jordbruksbyggnader – i kantonen Thurgau.Datakälla: Energikontoret L’ensemble de données comprend la consommation finale d’énergie dans le secteur des bâtiments pour la chaleur ambiante et l’eau chaude par source d’énergie dans le canton de Thurgovie à partir de 2015.L’énergie finale est l’énergie qui arrive au consommateur final. La consommation finale d’énergie dans le secteur du bâtiment comprend la consommation des bâtiments résidentiels et de services, à l’exclusion des bâtiments industriels et agricoles, sur le territoire du canton de Thurgovie.Source de données: Office de l’énergie El conjunto de datos incluye el consumo final de energía en el sector de la construcción para el calor ambiente y el agua caliente según fuentes de energía en el cantón de Thurgau a partir de 2015.La energía final es la energía que llega al consumidor final. El consumo final de energía en el sector de la construcción incluye el consumo de edificios residenciales y de servicio, excluidos los edificios industriales y agrícolas, en el territorio del cantón de Thurgau.Fuente de datos: Oficina de Energía Áirítear sa tacar sonraí tomhaltas deiridh fuinnimh in earnáil na bhfoirgneamh le haghaidh teas seomra agus uisce te de réir foinsí fuinnimh i gcantún Thurgau ó 2015. Is é an fuinneamh deiridh an fuinneamh a shroicheann an tomhaltóir deiridh. Áirítear leis an tomhaltas deiridh fuinnimh san earnáil tógála tomhaltas foirgneamh cónaithe agus foirgneamh seirbhíse — gan foirgnimh thionsclaíocha agus talmhaíochta a áireamh — ar chríoch chantún Thurgau.Foinse sonraí: Oifig an Fhuinnimh
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2020 United StatesPublisher:ClinicalTrials.org Approximately 11,000 Veterans present to a VAMC annually with an acute ischemic stroke or TIA. The cornerstone of secondary stroke/TIA prevention includes delivering timely, guideline-concordant vascular risk factor management. Over the past decade, OSA has been recognized as a potent, underdiagnosed, and inadequately treated cerebrovascular risk factor. OSA is very common among patients with stroke/TIA with a prevalence of 70-80%. Despite being highly prevalent, 70-80% of patients with OSA are neither diagnosed nor treated. Untreated OSA has been associated with poor outcomes among patients with cerebrovascular disease including higher mortality and worse functional status. The mainstay of OSA therapy is positive airway pressure (PAP). PAP reduces recurrent vascular events, improves neurological symptoms and functional status among stroke/TIA patients with OSA. The evidence favoring neurological recovery is strongest when interventions are applied early post-stroke/TIA. Guidelines recommend diagnosing and treating OSA for stroke and TIA patients; however, within VHA, very few stroke or TIA patients receive OSA screening. This guideline recommendation was informed in part by clinical trials utilizing an acute OSA assessment protocol developed and implemented by the investigators' group. To address the observed gap in care, the investigators propose a Hybrid Type I, randomized, stepped-wedge trial at 6 VAMCs to increase the rate of timely, guideline-concordant diagnosis and treatment of OSA among Veterans with ischemic stroke/TIA and thereby reduce recurrent vascular events and hospital readmissions. The investigators will identify matched control sites for each ASAP implementation site to examine temporal trends in outcomes among non-intervention sites. For example, the investigators will use administrative data to examine the use of polysomnography across stroke/TIA patients in the VA system and compare changes in matched controls versus the intervention sites on the diagnostic rate. The same adjustment approach will be used for ASAP intervention sites and for control sites. Effectively identifying and treating risk factors for ischemic stroke and transient ischemic attack (TIA) is important to patients, their family members, and healthcare systems. While obstructive sleep apnea (OSA) is a known risk factor for stroke and TIA that is present in more than 70% of stroke/TIA survivors, testing for OSA is infrequently performed for patients and within healthcare systems. The Addressing Sleep Apnea Post-Stroke/TIA (ASAP) study intends to improve rates of guideline-recommended OSA testing and treatment through local quality improvement initiatives (QI) conducted within and across 6 VA Medical Centers. ASAP will also determine the impact of these local QI initiatives on rates of OSA diagnosis, OSA treatment, treatment adherence, recurrent vascular events, and hospital readmissions.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020 European UnionPublisher:EEA The Regulation (EU) No 2019/631 (and before that Regulation (EU) No 510/2011) requires Member States to record information for each new van registered in its territory. Every year, each Member State shall submit to the Commission all the information related to their new registrations. In particular, the following details are required for each new van registered: manufacturer name, type approval number, type, variant, version, make and commercial name, specific emissions of CO2, mass of the vehicle, wheel base, track width, fuel type and fuel mode. Additional information, such as engine power and engine capacity were also submitted. Data for EU-28 are reported in the main database. Since 2018 Iceland and since 2019 Norway are also included in the database.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021 GermanyPublisher:Bielefeld University Authors: Hötte, Kerstin; Lafond, François; Pichler, Anton;This data publication offers updated data about low-carbon energy technology (LCET) patents and citations links to the scientific literature. Compared to a [previous version](https://doi.org/10.4119/unibi/2941555), it also contains data on biofuels and fuels from waste technologies. The updated version also contains the code (R-scripts) that have been used to (1) compile the data and (2) to reproduce the statistical analysis including figures and tables presented in the final paper Hötte, Pichler, Lafond (2021): "The rise of science in low-carbon energy technologies", RSER. DOI: [10.1016/j.rser.2020.110654](10.1016/j.rser.2020.110654). This data publication contains different data sets (in .RData and (long-term archivable) .tsv format). Further information about each data set is provided in more detail below. - "all_papers.RData" : Data on scientific papers from Microsoft Academic Graph (MAG), 3 columns: Paper ID, Paper year, cited (binary 0-1, indicates whether the paper is cited by a patent). - "all_patents.RData" : Data on USPTO utility patents, 6 columns: Patent number, Patent year (grant year), CPC class, Patent date, Patent title, citing_to_science (binary 0-1, indicates whether the patent is citing to science). - "LCET_patents.RData" : Subset of LCET patents, 6 columns: Patent number, Patent year (grant year), Technology type, CPC class, Patent date, Patent title. - "LCET_patent_citations.RData" : Citations from LCET patents to other patents, 2 columns: citing, cited (Patent numbers). - "LCET_subset_with_metainfo_final.RData" : Citations from LCET patents to scientific papers from MAG, complemented by meta-information on patents and papers, 18 columns: Patent number, Paper ID, Patent year, Paper year, Technology type, WoS field, Patent title, Paper title, DOI, Confidence Score, Citation type, Reference type, Journal/ Conf. name, Journal ID, Conference ID, CPC class, Patent date, US patent. - "patent:citations.RData": Patent citations among all patents (not only LCET), 2 columns: citing, cited (Patent numbers). Moreover, this data publication contains a folder "code" with 2 subfolders: - "R_code_create_data" contains the R-scripts used to create the data sample. - "R_code_plots_and_figures" contains all R-scripts used to make the statistical analyses presented in the text (including figures and tables). Please check the read-me documents in the code folder for further detail. ### License and terms of use ### This data is licensed under the CC BY 4.0 license. See: https://creativecommons.org/licenses/by/4.0/legalcode Please find the full license text below. If you want to use the data, do not forget to give appropriate credit by citing this article: Kerstin Hötte, Anton Pichler, François Lafond, The rise of science in low-carbon energy technologies, Renewable and Sustainable Energy Reviews, Volume 139, 2021. https://doi.org/10.1016/j.rser.2020.110654 ### LCET definition and concepts ### LCET are defined by Cooperative Patent Classification (CPC) codes. CPC offers "tags" that are assigned to patents that are useful for the adaptation and mitigation of climate chagen. LCET are identified by YO2E codes, i.e. that are assigned to technologies that contribute to the "REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION". Only the subset of Y02E01 ("Energy generation through renewable energy sources"), Y02E03 ("Energy generation of nuclear origin") and Y02E5 ("Technologies for the production of fuel of non-fossil origin") technologies are used. 10 different LCET are distinguished: Solar PV, Wind, Solar thermal, Ocean power, Hydroelectric, Geothermal, Biofuels, Fuels from waste, Nuclear fission and Nuclear fusion. More information about the Y02-tags can be found in: Veefkind, Victor, et al. "A new EPO classification scheme for climate change mitigation technologies." World Patent Information 34.2 (2012): 106-111. DOI: [https://doi.org/10.1016/j.wpi.2011.12.004](https://doi.org/10.1016/j.wpi.2011.12.004) ### Data sources and compilation ### The data was generated by the merge of different data sets. 1.) Patent data from USPTO was downloaded here: https://bulkdata.uspto.gov/ 2.) Complementary data on grant year and patent title was taken from: https://cloud.google.com/blog/products/gcp/google-patents-public-datasets-connecting-public-paid-and-private-patent-data 3.) Citations to science come from the Reliance on Science (RoS) data set https://zenodo.org/record/3685972 (v23, Feb. 24, 2020) DOI: 10.5281/zenodo.3685972 The directory ("code") offers the R-scripts that were used to process MAG data and to link it to patent data. The header of the R-scripts offer additional technical information about the subsetting procedures and data retrieval. For more information about the patent data, see: Pichler, A., Lafond, F. & J, F. D. (2020), Technological interdependencies predict innovation dynamics, Working paper pp. 1–33. URL: [https://arxiv.org/abs/2003.00580](https://arxiv.org/abs/2003.00580) For more information about MAG data, see: Marx, Matt, and Aaron Fuegi. "Reliance on science: Worldwide front‐page patent citations to scientific articles." Strategic Management Journal 41.9 (2020): 1572-1594. DOI: [https://doi.org/10.1002/smj.3145](https://doi.org/10.1002/smj.3145) Marx, Matt and Fuegi, Aaron, Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles. Boston University Questrom School of Business Research Paper No. 3331686. DOI: [http://dx.doi.org/10.2139/ssrn.3331686 ](http://dx.doi.org/10.2139/ssrn.3331686 ) ### Detailed information about the data ### - "all_papers.RData" : Data on scientific papers from Microsoft Academic Graph (MAG), 3 columns: Paper ID: Unique paper-identifier used by MAG Paper year: Year of publication cited: binary 0-1, indicates whether the paper is cited by a patent, citation links are made in the text body and front-page of the patent, and added by examiners and applicants. - "all_patents.RData" : Data on USPTO utility patents, 6 columns: Patent number: Number given by USPTO. Can be used for manual patent search in http://patft.uspto.gov/netahtml/PTO/srchnum.htm (numeric) Patent year: Year when the patent was granted (numeric) CPC class: Detailed 8-digit CPC code (numeric) Patent date: Exact date of patent granting (numeric) Patent title: Short title (character) citing_to_science: binary 0-1, indicates whether the patent is citing to science as identified by citation links in RoS. (numeric) - "LCET_patents.RData" : Subset of LCET patents, 6 columns: Patent number: (numeric) Patent year: (numeric) Technology type: Short code used to tag 10 different types of LCET (pv, (nuclear) fission, (solar) thermal, (nuclear) fusion, wind, geo(termal), sea (ocean power), hydro, biofuels, (fuels from) waste) (character) CPC class: Detailed 8-digit CPC code (character) Patent date: (numeric) Patent title: (numeric) - "LCET_patent_citations.RData" : Citations from LCET patents to other patents, 2 columns: citing: Number of citing patent (numeric) cited: Number of cited patent (numeric) - "LCET_subset_with_metainfo_final.RData" : Citations from LCET patents to scientific papers from MAG, complemented by meta-information on patents and papers, 18 columns: Patent number: see above (numeric) Paper ID: see above (numeric) Patent year: see above (numeric) Paper year: see above (numeric) Technology type: see above (character) WoS field: Web of Science field of research, WoS fields were probabilistically assigned to papers and are used as given by RoS (character) Patent title: see above (character) Paper title: Title of scientific article (character) DOI: Paper DOI if available (character) Confidence Score: Reliability score of citation link (numeric). Links were probabilistically assigned. See Marx and Fuegi 2019 for further detail. Citation type: Indicates whether citation made in text body of patent document or its front page (character) Reference type: Examiner or applicant added citation link (or unknown). (character) Journal/ Conf. name: Name of journal or conference proceeding where the cited paper was published (character) Journal ID: Journal identifier in MAG (numeric) Conference ID: Conference identifier in MAG (numeric) CPC class: see above (character) Patent date: see above (numeric) US patent: binary US-patent indicator as provided by RoS (numeric) - "patent:citations.RData": Patent citations among all patents (not only LCET), 2 columns: citing: Number of citing patent (numeric) cited: Number of cited patent (numeric) **Note:** The citation links were probabilistically retrieved. During the analysis, we identified manually some false-positives are removed them from the "LCET_subset_with_metainfo_final.RData" data set. The list is available, too: "list_of_false_positives.tsv" We do not claim to have a perfect coverage, but expect a precision of >98% as described by Marx and Fuegi 2019. ### Statistics about the data ### Full data set: - #papers in MAG: 179,083,029 - #all patents: 10,160,667 - #citing patents: 2,058,233 - #cited papers: 4,404,088 - #citation links from patents to papers: 34,959,193 LCET subset: - #LCET patents: 65,305 - #citing LCET patents: 22,017 - #cited papers: 103,645 - #citation links from LCET patents to papers: 396,504 Meta-information: Papers: - Publication year, 251 Web-of-Science (WoS) categories, Journal/ conference proceedings name, DOI, Paper title Patents: - Grant year, >240,000 hierarchical CPC classes, 10 LCET types Citation links: - Reference type, citation type, reliability score If you have further questions about the data or suggestions, please contact: **kerstin.hotte@oxfordmartin.ox.ac.uk** ### Acknowledgements ### The authors want to thank the Center for Research Data Management of Bielefeld University and in particular Cord Wiljes for excellent support. ### License issues ### Terms of use of the source data: - Reliance on Science data [https://zenodo.org/record/3685972](https://zenodo.org/record/3685972), Open Data Commons Attribution License (ODC-By) v1.0, https://opendatacommons.org/licenses/by/1.0/ - "Google Patents Public Data” by IFI CLAIMS Patent Services and Google (https://cloud.google.com/blog/products/gcp/google-patents-public-datasets-connecting-public-paid-and-private-patent-data), Creative Commons Attribution 4.0 International License (CC BY 4.0), https://console.cloud.google.com/marketplace/details/google_patents_public_datasets/google-patents-public-data - USPTO patent data (https://bulkdata.uspto.gov/), see: https://bulkdata.uspto.gov/data/2020TermsConditions.docx
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Dittmann, Anna; Dinger, Florian; Herzberg, Wiebke; Holland, Nicolas; Karalus, Steffen; Braun, Christian; Zähringer, Ralph; Heydenreich, Wolfgang; Lorenz, Elke;The PV-Live dataset comprises data from a network of 40 solar irradiance measurement stations across the German state of Baden-Württemberg. All stations measure global horizontal irradiance and temperature with a pyranometer, and global tilted irradiance in east, south, and west direction with tilt angles of 25° with three photovoltaic reference cells in minute resolution. A quality control scheme has been developed specifically for this dataset and is applied to the measurements before publication. The minute resolution irradiance and temperature measurements are published with the derived quality flags. A description of the dataset and the quality control scheme is given in Lorenz et al. (2022) and Lorenz et al. (2020). The dataset contains data from September 2020 onwards. It will be continuously extended by adding data of the previous month on a monthly basis. QUALITY FLAGS Two types of flags are provided with the data. Each sensor is assigned a general quality flag, which is based on a combination of different tests. In addition, a shading flag is given, which is not sensor specific, i.e. it applies to all irradiance sensors simultaneously. The flags can have the levels 'passed, all tests complete', 'passed, not all tests complete', 'failed tests, likely erroneous' or 'failed tests, most likely erroneous'. If the flag level of the general quality flags is 'failed tests, most likely erroneous' the corresponding measurement value is set to NaN. DATA FORMAT The data is published as monthly .zip archives. Each archive contains the following files: 1. Tab separated data files (tng000XX_YYYY-MM.tsv) for each station, containing measurements and quality flags of one month 2. Tab separated station location metadata (metadata_stations_YYYY-MM.tsv) 3. Metadata of the dataset describing variable names and quality flag levels (metadata_measurements.json) 4. General comments on data availability and quality for the month (comments_quality_control_YYYY-MM.txt) 5. Log file of changes (change_log_YYYY-MM.txt) Station location metadata is given on a monthly basis because stations can be relocated. Therefore, we recommend to use the metadata valid for its corresponding month. VERSION UPDATES Version 7: - Recalculation of height information for all stations - One station has been moved to a new, nearby location on 16th September 2021 ACKNOWLEDGEMENTS The data have been collected and processed by Fraunhofer ISE in the framework of PV-Live, a project in cooperation with TransnetBW. We thank our station partners for cooperation in installing and maintaining our measurement stations: EnBW Solar, Badenova, Pohlen Solar, Oekogeno Solar7, Ecovision, Hochschule Ulm, Hofgemeinschaft Heggelbach, Soltechnics-solution and the Stadtwerke Karlsruhe, Grünstadt, Buchen, Crailsheim, Schwäbisch Hall, Pforzheim, Konstanz, Waldshut-Tiengen, Schwäbisch Gmünd, Ravensburg, Eberbach, Baden-Baden.
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Research data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 13 Apr 2022Publisher:Dryad Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; Xie, Shuyu; Gao, Kunshan;The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 European UnionLes conditions géothermiques souterraines, quelle que soit la position des aquifères, sont montrées avec des cartes géothermiques appropriées. Cette carte représente les lignes de température attendues à une profondeur de 3 000 m de la carte de la distribution spatiale de la température attendue à une profondeur de 3 000 m (carte géothermique), qui est faite avec des données de 214 forages. Il est fabriqué sur la base des températures mesurées dans des puits accessibles dans tout le pays. Cependant, puisque le champ de température dépend de la composition géologique en profondeur et des caractéristiques tectoniques, le cours des isothermes est le résultat de nombreuses influences telles que la conductivité thermique des roches, la perméabilité et la fissuration des roches, qui se reflètent toutes dans les températures mesurées des puits. À cette profondeur, la chaleur radiogénique dans les roches a également une influence mineure. La répartition des puits, utiles pour les mesures de température, est très inégale et varie en profondeur. Après des températures à une profondeur de 3 000 m, il y a une anomalie positive plus forte dans la partie nord-est de la Slovénie, de la ligne Maribor-Rogatec à l’est, alors qu’il n’y a pas d’anomalie dans la partie orientale du bassin de Krško. Dans la partie nord-est du pays, cela est dû à la croûte terrestre plus mince et au flux de chaleur conductif plus élevé du manteau terrestre. Ailleurs, les températures sont beaucoup plus basses. Las condiciones geotérmicas subterráneas, independientemente de la posición de los acuíferos, se muestran con mapas geotérmicos adecuados. Este mapa representa las líneas de temperatura esperadas a una profundidad de 3 000 m del mapa de la distribución espacial de la temperatura esperada a una profundidad de 3 000 m (Mapa Geotérmico), que se realiza con datos de 214 pozos. Se realiza sobre la base de temperaturas medidas en pozos accesibles en todo el país. Sin embargo, dado que el campo de temperatura depende de la composición geológica en profundidades y características tectónicas, el curso de las isotermas es el resultado de numerosas influencias, como la conductividad térmica de las rocas, la permeabilidad y el agrietamiento de las rocas, todas las cuales se reflejan en temperaturas bien medidas. A esta profundidad, el calor radiogénico en las rocas también tiene una influencia menor. La distribución de los pozos, que fueron útiles para las mediciones de temperatura, es muy desigual y varía en profundidad. Después de temperaturas a una profundidad de 3 000 m, hay una anomalía positiva más fuerte en la parte noreste de Eslovenia, desde la línea Maribor-Rogatec hacia el este, mientras que no hay anomalía en la parte oriental de la cuenca de Krško. En la parte noreste del país, esto se debe a la corteza terrestre más delgada y al mayor flujo de calor conductor del manto de la Tierra. En otros lugares, las temperaturas son mucho más bajas. Die unterirdischen Geothermiebedingungen, unabhängig von der Lage der Grundwasserleiter, werden mit geeigneten geothermischen Karten dargestellt. Diese Karte stellt die erwarteten Temperaturlinien in einer Tiefe von 3 000 m von der Karte der räumlichen Verteilung der erwarteten Temperatur in einer Tiefe von 3 000 m (Geothermiekarte) dar, die mit Daten aus 214 Bohrlöchern erstellt wird. Es wird auf der Grundlage der gemessenen Temperaturen in zugänglichen Brunnen im ganzen Land gemacht. Da das Temperaturfeld jedoch von der geologischen Zusammensetzung in Tiefen und tektonischen Eigenschaften abhängt, ist der Verlauf der Isothermen das Ergebnis zahlreicher Einflüsse wie Wärmeleitfähigkeit von Gesteinen, Durchlässigkeit und Rissbildung von Gesteinen, die alle in gemessenen Brunnentemperaturen reflektiert werden. In dieser Tiefe hat auch radiogene Hitze in Gesteinen einen geringen Einfluss. Die Verteilung der Brunnen, die für Temperaturmessungen nützlich waren, ist sehr ungleichmäßig und variiert in der Tiefe. Nach Temperaturen in einer Tiefe von 3 000 m gibt es eine stärkere positive Anomalie im nordöstlichen Teil Sloweniens, von der Linie Maribor-Rogatec nach Osten, während es im östlichen Teil des Krško-Beckens keine Anomalie gibt. Im Nordosten des Landes ist dies auf die dünnere Erdkruste und die höhere leitfähige Wärmeströmung aus dem Erdmantel zurückzuführen. Anderswo sind die Temperaturen viel niedriger. Le condizioni geotermiche sotterranee, indipendentemente dalla posizione delle falde acquifere, sono mostrate con adeguate mappe geotermiche. Questa mappa rappresenta le linee di temperatura previste ad una profondità di 3 000 m dalla mappa della distribuzione spaziale della temperatura prevista ad una profondità di 3 000 m (Carta geotermica), che è fatta con i dati di 214 pozzi. È realizzato sulla base delle temperature misurate in pozzi accessibili in tutto il paese. Tuttavia, poiché il campo di temperatura dipende dalla composizione geologica in profondità e caratteristiche tettoniche, il decorso delle isoterme è il risultato di numerose influenze come la conducibilità termica delle rocce, la permeabilità e la fessura delle rocce, che si riflettono tutte in temperature misurate bene. A questa profondità, anche il calore radiogenico nelle rocce ha un'influenza minore. La distribuzione dei pozzi, utili per le misurazioni della temperatura, è molto irregolare e varia in profondità. Dopo temperature a una profondità di 3 000 m, c'è un'anomalia positiva più forte nella parte nord-orientale della Slovenia, dalla linea Maribor-Rogatec a est, mentre non vi è alcuna anomalia nella parte orientale del bacino di Krško. Nella parte nord-orientale del paese, questo è dovuto alla crosta terrestre più sottile e al più alto flusso di calore conduttivo dal mantello terrestre. Altrove, le temperature sono molto più basse. De ondergrondse geothermische omstandigheden, ongeacht de positie van de watervoerende lagen, worden weergegeven met geschikte geothermische kaarten. Deze kaart geeft de verwachte temperatuurlijnen weer op een diepte van 3 000 m van de kaart van de ruimtelijke verdeling van de verwachte temperatuur op een diepte van 3 000 m (Geothermiekaart), die wordt gemaakt met gegevens van 214 boorgaten. Het wordt gemaakt op basis van gemeten temperaturen in toegankelijke putten in het hele land. Aangezien het temperatuurveld echter afhankelijk is van de geologische samenstelling in diepten en tektonische kenmerken, is het verloop van isothermen het resultaat van talrijke invloeden zoals thermische geleidbaarheid van gesteenten, doorlaatbaarheid en kraken van gesteenten, die allemaal worden weerspiegeld in gemeten goedtemperaturen. Op deze diepte heeft radiogene warmte in rotsen ook een kleine invloed. De verdeling van putten, die nuttig waren voor temperatuurmetingen, is zeer ongelijk en varieert in diepte. Na temperaturen op een diepte van 3 000 m is er een sterkere positieve anomalie in het noordoosten van Slovenië, van de lijn Maribor-Rogatec naar het oosten, terwijl er geen anomalie is in het oostelijke deel van het Krško-bekken. In het noordoosten van het land is dit te wijten aan de dunnere aardkorst en de hogere geleidende warmtestroom uit de mantel van de aarde. Elders zijn de temperaturen veel lager. Οι υπόγειες γεωθερμικές συνθήκες, ανεξάρτητα από τη θέση των υδροφόρων οριζόντων, παρουσιάζονται με κατάλληλους γεωθερμικούς χάρτες. Ο χάρτης αυτός αναπαριστά τις αναμενόμενες γραμμές θερμοκρασίας σε βάθος 3 000 m από τον χάρτη της χωρικής κατανομής της αναμενόμενης θερμοκρασίας σε βάθος 3 000 m (Γεωθερμικός Χάρτης), ο οποίος γίνεται με δεδομένα από 214 γεωτρήσεις. Γίνεται με βάση τις μετρούμενες θερμοκρασίες σε προσβάσιμα πηγάδια σε όλη τη χώρα. Ωστόσο, δεδομένου ότι το πεδίο θερμοκρασίας εξαρτάται από τη γεωλογική σύνθεση σε βάθη και τεκτονικά χαρακτηριστικά, η πορεία των ισοθερμικών είναι το αποτέλεσμα πολυάριθμων επιδράσεων όπως η θερμική αγωγιμότητα των πετρωμάτων, η διαπερατότητα και η ρωγμή των πετρωμάτων, οι οποίες αντανακλώνται σε μετρημένες θερμοκρασίες φρεατίων. Σε αυτό το βάθος, η ραδιογενής θερμότητα στους βράχους έχει επίσης μια μικρή επιρροή. Η κατανομή των φρεάτων, τα οποία ήταν χρήσιμα για μετρήσεις θερμοκρασίας, είναι πολύ άνιση και ποικίλλει σε βάθος. Μετά από θερμοκρασίες σε βάθος 3000 μέτρων, υπάρχει μια ισχυρότερη θετική ανωμαλία στο βορειοανατολικό τμήμα της Σλοβενίας, από τη γραμμή Maribor-Rogatec προς τα ανατολικά, ενώ δεν υπάρχει ανωμαλία στο ανατολικό τμήμα της λεκάνης Krško. Στο βορειοανατολικό τμήμα της χώρας, αυτό οφείλεται στον λεπτότερο φλοιό της Γης και την υψηλότερη αγώγιμη ροή θερμότητας από τον μανδύα της Γης. Αλλού, οι θερμοκρασίες είναι πολύ χαμηλότερες. The underground geothermal conditions can be presented, irrespective of the aquifers' position, with the appropriate geothermal maps. This map represents the expected temperature lines at a depth of 3000 m and is derived from Geothermal map - Expected temperatures at a depth of 3000 m, which is made with data from 214 boreholes. It is made on the basis of measured temperatures in accessible boreholes throughout the country. However, since the temperature field depends on the geological structure in the depths and tectonic characteristics, the course of the isotherms is a result of many influences, such as thermal conductivity of rocks, permeability and fracturing of rocks, all of which are reflected in the measured temperatures in boreholes. In this depth also a radiogenic heat production in the rocks has smaller influence. The distribution of boreholes, which were useful for the measurement of temperature, is very uneven and different as regard the depths. Following the expected temperatures at a depth of 3000 m a stronger positive anomaly is in the northeastern part of Slovenia, from the line Maribor-Rogatec to the east, while in the eastern part of the Krka basin there is no anomaly any more. In the northeastern part of the country the anomaly is the result of the thinning of the Earth's crust and greater conductive heat flow from the Earth's mantle. Elsewhere temperatures are much lower. Condițiile geotermale subterane, indiferent de poziția acviferelor, sunt afișate cu hărți geotermale adecvate. Această hartă reprezintă liniile de temperatură așteptate la o adâncime de 3 000 m de la harta distribuției spațiale a temperaturii așteptate la o adâncime de 3 000 m (Harta geotermală), care este realizată cu date de la 214 găuri de foraj. Se face pe baza temperaturilor măsurate în puțuri accesibile din întreaga țară. Cu toate acestea, deoarece câmpul de temperatură depinde de compoziția geologică în adâncimi și caracteristici tectonice, cursul izotermelor este rezultatul a numeroase influențe, cum ar fi conductivitatea termică a rocilor, permeabilitatea și fisurarea rocilor, toate acestea fiind reflectate în temperaturile sondei măsurate. La această adâncime, căldura radiogenică din roci are, de asemenea, o influență minoră. Distribuția puțurilor, care au fost utile pentru măsurarea temperaturii, este foarte inegală și variază în profunzime. După temperaturi la o adâncime de 3 000 m, există o anomalie pozitivă mai puternică în partea de nord-est a Sloveniei, de la linia Maribor-Rogatec la est, în timp ce nu există nicio anomalie în partea estică a bazinului Krško. În partea de nord-est a țării, acest lucru se datorează scoarței mai subțiri a Pământului și fluxului de căldură mai mare din mantaua Pământului. În alte părți, temperaturile sunt mult mai scăzute. Il-kundizzjonijiet ġeotermali taħt l-art, irrispettivament mill-pożizzjoni tal-akwiferi, huma murija b’mapep ġeotermali adattati. Din il-mappa tirrappreżenta l-linji tat-temperatura mistennija f’fond ta’ 3 000 m mill-mappa tad-distribuzzjoni spazjali tat-temperatura mistennija f’fond ta’ 3 000 m (Mappa Ġeotermali), li hija magħmula b’data minn 214 boreholes. Dan isir fuq il-bażi ta’ temperaturi mkejla fi bjar aċċessibbli fil-pajjiż kollu. Madankollu, peress li l-kamp tat-temperatura jiddependi fuq il-kompożizzjoni ġeoloġika fil-fond u l-karatteristiċi tettoniċi, il-kors tal-isotermi huwa r-riżultat ta’ bosta influwenzi bħall-konduttività termali tal-blat, il-permeabilità u l-qsim tal-blat, li kollha huma riflessi f’temperaturi mkejla tal-bjar. F’dan il-fond, sħana radjoġenika fil-blat għandha wkoll influwenza minuri. Id-distribuzzjoni tal-bjar, li kienu utli għall-kejl tat-temperatura, hija irregolari ħafna u tvarja fil-fond. Wara temperaturi f’fond ta’ 3 000 m, hemm anomalija pożittiva aktar qawwija fil-parti tal-Grigal tas-Slovenja, mil-linja Maribor-Rogatec lejn il-Lvant, filwaqt li ma hemm l-ebda anomalija fil-parti tal-Lvant tal-baċir ta’ Krško. Fil-parti tal-grigal tal-pajjiż, dan huwa dovut għall-qoxra tad-Dinja irqaq u l-fluss tas-sħana konduttiv ogħla mill-mantell tad-Dinja. Band’oħra, it-temperaturi huma ħafna aktar baxxi. As condições geotérmicas subterrâneas, independentemente da posição dos aquíferos, são mostradas com mapas geotérmicos adequados. Este mapa representa as linhas de temperatura esperadas a uma profundidade de 3 000 m do mapa da distribuição espacial da temperatura esperada a uma profundidade de 3 000 m (Mapa geotérmico), que é feita com dados de 214 furos. É feita com base nas temperaturas medidas em poços acessíveis em todo o país. No entanto, uma vez que o campo de temperatura depende da composição geológica em profundidades e características tectónicas, o curso das isotérmicas é o resultado de inúmeras influências, tais como condutividade térmica das rochas, permeabilidade e rachadura de rochas, todas elas refletidas em temperaturas medidas. A esta profundidade, o calor radiogénico nas rochas também tem uma pequena influência. A distribuição dos poços, que foram úteis para medições de temperatura, é muito desigual e varia em profundidade. Depois de temperaturas a uma profundidade de 3 000 m, há uma anomalia positiva mais forte na parte nordeste da Eslovénia, da linha Maribor-Rogatec ao leste, enquanto não há anomalia na parte oriental da bacia de Krško. Na parte nordeste do país, isto é devido à crosta mais fina da Terra e ao maior fluxo de calor condutor do manto da Terra. Em outros locais, as temperaturas são muito mais baixas.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:The Smithsonian Institution Authors: Paton, Steve;doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
Monthly and daily summary from the Fortuna Station (Centro de Investigaciones Jorge L. Arauz)Location: 8° 43.340'N, 82° 14.241'WParameters: air temperature, wind speed and direction, precipitation, solar radiation (pyranometer)Located in the highlands of the Chiriqui Province, in western Panama.There are three sensor locations: north clearing, south clearing, and a 15m tower.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | PARIS REINFORCEEC| PARIS REINFORCEDoukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; Nikas, Alexandros;This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022 European UnionPublisher:kanton-thurgau Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Το σύνολο δεδομένων περιλαμβάνει την τελική κατανάλωση ενέργειας στον κτιριακό τομέα για τη θερμότητα δωματίου και το ζεστό νερό σύμφωνα με τις πηγές ενέργειας στο καντόνι του Thurgau από το 2015.Η τελική ενέργεια είναι η ενέργεια που φτάνει στον τελικό καταναλωτή. Η τελική κατανάλωση ενέργειας στον κτιριακό τομέα περιλαμβάνει την κατανάλωση κατοικιών και κτιρίων παροχής υπηρεσιών — εξαιρουμένων των βιομηχανικών και γεωργικών κτιρίων — στο έδαφος του καντόνι Thurgau.Πηγή δεδομένων: Γραφείο Ενέργειας Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Il set di dati include il consumo di energia finale nel settore edilizio per il calore ambiente e l'acqua calda secondo fonti energetiche nel Canton Turgovia dal 2015.L'energia finale è l'energia che raggiunge il consumatore finale. Il consumo di energia finale nel settore edilizio comprende il consumo di edifici residenziali e di servizi — esclusi gli edifici industriali e agricoli — sul territorio del cantone di Thurgau. Ufficio dell'energia Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Zbiór danych obejmuje końcowe zużycie energii w sektorze budowlanym do ogrzewania pomieszczeń i ciepłej wody zgodnie ze źródłami energii w kantonie Thurgau od 2015 r. Energia końcowa to energia, która dociera do konsumenta końcowego. Końcowe zużycie energii w sektorze budowlanym obejmuje zużycie budynków mieszkalnych i usługowych – z wyłączeniem budynków przemysłowych i rolniczych – na terytorium kantonu Thurgau.Źródło danych: Urząd Energetyki Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики Набір даних включає в себе кінцеве споживання енергії в будівельному секторі для кімнатного тепла і гарячої води відповідно до джерел енергії в кантоні Тургау з 2015 року. Кінцеве споживання енергії в будівельному секторі включає споживання житлових і службових будівель — без урахування промислових і сільськогосподарських будівель — на території кантону Тургау. Офіс енергетики O conjunto de dados inclui o consumo final de energia no setor da construção para calor ambiente e água quente de acordo com as fontes de energia no cantão de Thurgau a partir de 2015. A energia final é a energia que chega ao consumidor final. O consumo final de energia no setor da construção inclui o consumo de edifícios residenciais e de serviços — excluindo edifícios industriais e agrícolas — no território do cantão de Thurgau.Fonte de dados: Escritório de Energia O conjunto de dados inclui o consumo final de energia no setor da construção para calor ambiente e água quente de acordo com as fontes de energia no cantão de Thurgau a partir de 2015. A energia final é a energia que chega ao consumidor final. O consumo final de energia no setor da construção inclui o consumo de edifícios residenciais e de serviços — excluindo edifícios industriais e agrícolas — no território do cantão de Thurgau.Fonte de dados: Escritório de Energia Súbor údajov zahŕňa konečnú spotrebu energie v stavebníctve na vykurovanie miestností a teplú vodu podľa zdrojov energie v kantóne Thurgau od roku 2015. Konečná energia je energia, ktorá sa dostáva ku konečnému spotrebiteľovi. Konečná spotreba energie v stavebníctve zahŕňa spotrebu bytových a servisných budov – okrem priemyselných a poľnohospodárskych budov – na území kantónu Thurgau.Zdroj údajov: Úrad pre energetiku Súbor údajov zahŕňa konečnú spotrebu energie v stavebníctve na vykurovanie miestností a teplú vodu podľa zdrojov energie v kantóne Thurgau od roku 2015. Konečná energia je energia, ktorá sa dostáva ku konečnému spotrebiteľovi. Konečná spotreba energie v stavebníctve zahŕňa spotrebu bytových a servisných budov – okrem priemyselných a poľnohospodárskych budov – na území kantónu Thurgau.Zdroj údajov: Úrad pre energetiku Datasetet omfattar den slutliga energianvändningen inom byggsektorn för rumsvärme och varmvatten enligt energikällor i Thurgaus kanton från 2015. Den slutliga energin är den energi som når slutkonsumenten. Den slutliga energianvändningen inom byggsektorn omfattar förbrukningen av bostads- och servicebyggnader – utom industri- och jordbruksbyggnader – i kantonen Thurgau.Datakälla: Energikontoret Datasetet omfattar den slutliga energianvändningen inom byggsektorn för rumsvärme och varmvatten enligt energikällor i Thurgaus kanton från 2015. Den slutliga energin är den energi som når slutkonsumenten. Den slutliga energianvändningen inom byggsektorn omfattar förbrukningen av bostads- och servicebyggnader – utom industri- och jordbruksbyggnader – i kantonen Thurgau.Datakälla: Energikontoret L’ensemble de données comprend la consommation finale d’énergie dans le secteur des bâtiments pour la chaleur ambiante et l’eau chaude par source d’énergie dans le canton de Thurgovie à partir de 2015.L’énergie finale est l’énergie qui arrive au consommateur final. La consommation finale d’énergie dans le secteur du bâtiment comprend la consommation des bâtiments résidentiels et de services, à l’exclusion des bâtiments industriels et agricoles, sur le territoire du canton de Thurgovie.Source de données: Office de l’énergie El conjunto de datos incluye el consumo final de energía en el sector de la construcción para el calor ambiente y el agua caliente según fuentes de energía en el cantón de Thurgau a partir de 2015.La energía final es la energía que llega al consumidor final. El consumo final de energía en el sector de la construcción incluye el consumo de edificios residenciales y de servicio, excluidos los edificios industriales y agrícolas, en el territorio del cantón de Thurgau.Fuente de datos: Oficina de Energía Áirítear sa tacar sonraí tomhaltas deiridh fuinnimh in earnáil na bhfoirgneamh le haghaidh teas seomra agus uisce te de réir foinsí fuinnimh i gcantún Thurgau ó 2015. Is é an fuinneamh deiridh an fuinneamh a shroicheann an tomhaltóir deiridh. Áirítear leis an tomhaltas deiridh fuinnimh san earnáil tógála tomhaltas foirgneamh cónaithe agus foirgneamh seirbhíse — gan foirgnimh thionsclaíocha agus talmhaíochta a áireamh — ar chríoch chantún Thurgau.Foinse sonraí: Oifig an Fhuinnimh
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2020 United StatesPublisher:ClinicalTrials.org Approximately 11,000 Veterans present to a VAMC annually with an acute ischemic stroke or TIA. The cornerstone of secondary stroke/TIA prevention includes delivering timely, guideline-concordant vascular risk factor management. Over the past decade, OSA has been recognized as a potent, underdiagnosed, and inadequately treated cerebrovascular risk factor. OSA is very common among patients with stroke/TIA with a prevalence of 70-80%. Despite being highly prevalent, 70-80% of patients with OSA are neither diagnosed nor treated. Untreated OSA has been associated with poor outcomes among patients with cerebrovascular disease including higher mortality and worse functional status. The mainstay of OSA therapy is positive airway pressure (PAP). PAP reduces recurrent vascular events, improves neurological symptoms and functional status among stroke/TIA patients with OSA. The evidence favoring neurological recovery is strongest when interventions are applied early post-stroke/TIA. Guidelines recommend diagnosing and treating OSA for stroke and TIA patients; however, within VHA, very few stroke or TIA patients receive OSA screening. This guideline recommendation was informed in part by clinical trials utilizing an acute OSA assessment protocol developed and implemented by the investigators' group. To address the observed gap in care, the investigators propose a Hybrid Type I, randomized, stepped-wedge trial at 6 VAMCs to increase the rate of timely, guideline-concordant diagnosis and treatment of OSA among Veterans with ischemic stroke/TIA and thereby reduce recurrent vascular events and hospital readmissions. The investigators will identify matched control sites for each ASAP implementation site to examine temporal trends in outcomes among non-intervention sites. For example, the investigators will use administrative data to examine the use of polysomnography across stroke/TIA patients in the VA system and compare changes in matched controls versus the intervention sites on the diagnostic rate. The same adjustment approach will be used for ASAP intervention sites and for control sites. Effectively identifying and treating risk factors for ischemic stroke and transient ischemic attack (TIA) is important to patients, their family members, and healthcare systems. While obstructive sleep apnea (OSA) is a known risk factor for stroke and TIA that is present in more than 70% of stroke/TIA survivors, testing for OSA is infrequently performed for patients and within healthcare systems. The Addressing Sleep Apnea Post-Stroke/TIA (ASAP) study intends to improve rates of guideline-recommended OSA testing and treatment through local quality improvement initiatives (QI) conducted within and across 6 VA Medical Centers. ASAP will also determine the impact of these local QI initiatives on rates of OSA diagnosis, OSA treatment, treatment adherence, recurrent vascular events, and hospital readmissions.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020 European UnionPublisher:EEA The Regulation (EU) No 2019/631 (and before that Regulation (EU) No 510/2011) requires Member States to record information for each new van registered in its territory. Every year, each Member State shall submit to the Commission all the information related to their new registrations. In particular, the following details are required for each new van registered: manufacturer name, type approval number, type, variant, version, make and commercial name, specific emissions of CO2, mass of the vehicle, wheel base, track width, fuel type and fuel mode. Additional information, such as engine power and engine capacity were also submitted. Data for EU-28 are reported in the main database. Since 2018 Iceland and since 2019 Norway are also included in the database.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021 GermanyPublisher:Bielefeld University Authors: Hötte, Kerstin; Lafond, François; Pichler, Anton;This data publication offers updated data about low-carbon energy technology (LCET) patents and citations links to the scientific literature. Compared to a [previous version](https://doi.org/10.4119/unibi/2941555), it also contains data on biofuels and fuels from waste technologies. The updated version also contains the code (R-scripts) that have been used to (1) compile the data and (2) to reproduce the statistical analysis including figures and tables presented in the final paper Hötte, Pichler, Lafond (2021): "The rise of science in low-carbon energy technologies", RSER. DOI: [10.1016/j.rser.2020.110654](10.1016/j.rser.2020.110654). This data publication contains different data sets (in .RData and (long-term archivable) .tsv format). Further information about each data set is provided in more detail below. - "all_papers.RData" : Data on scientific papers from Microsoft Academic Graph (MAG), 3 columns: Paper ID, Paper year, cited (binary 0-1, indicates whether the paper is cited by a patent). - "all_patents.RData" : Data on USPTO utility patents, 6 columns: Patent number, Patent year (grant year), CPC class, Patent date, Patent title, citing_to_science (binary 0-1, indicates whether the patent is citing to science). - "LCET_patents.RData" : Subset of LCET patents, 6 columns: Patent number, Patent year (grant year), Technology type, CPC class, Patent date, Patent title. - "LCET_patent_citations.RData" : Citations from LCET patents to other patents, 2 columns: citing, cited (Patent numbers). - "LCET_subset_with_metainfo_final.RData" : Citations from LCET patents to scientific papers from MAG, complemented by meta-information on patents and papers, 18 columns: Patent number, Paper ID, Patent year, Paper year, Technology type, WoS field, Patent title, Paper title, DOI, Confidence Score, Citation type, Reference type, Journal/ Conf. name, Journal ID, Conference ID, CPC class, Patent date, US patent. - "patent:citations.RData": Patent citations among all patents (not only LCET), 2 columns: citing, cited (Patent numbers). Moreover, this data publication contains a folder "code" with 2 subfolders: - "R_code_create_data" contains the R-scripts used to create the data sample. - "R_code_plots_and_figures" contains all R-scripts used to make the statistical analyses presented in the text (including figures and tables). Please check the read-me documents in the code folder for further detail. ### License and terms of use ### This data is licensed under the CC BY 4.0 license. See: https://creativecommons.org/licenses/by/4.0/legalcode Please find the full license text below. If you want to use the data, do not forget to give appropriate credit by citing this article: Kerstin Hötte, Anton Pichler, François Lafond, The rise of science in low-carbon energy technologies, Renewable and Sustainable Energy Reviews, Volume 139, 2021. https://doi.org/10.1016/j.rser.2020.110654 ### LCET definition and concepts ### LCET are defined by Cooperative Patent Classification (CPC) codes. CPC offers "tags" that are assigned to patents that are useful for the adaptation and mitigation of climate chagen. LCET are identified by YO2E codes, i.e. that are assigned to technologies that contribute to the "REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION". Only the subset of Y02E01 ("Energy generation through renewable energy sources"), Y02E03 ("Energy generation of nuclear origin") and Y02E5 ("Technologies for the production of fuel of non-fossil origin") technologies are used. 10 different LCET are distinguished: Solar PV, Wind, Solar thermal, Ocean power, Hydroelectric, Geothermal, Biofuels, Fuels from waste, Nuclear fission and Nuclear fusion. More information about the Y02-tags can be found in: Veefkind, Victor, et al. "A new EPO classification scheme for climate change mitigation technologies." World Patent Information 34.2 (2012): 106-111. DOI: [https://doi.org/10.1016/j.wpi.2011.12.004](https://doi.org/10.1016/j.wpi.2011.12.004) ### Data sources and compilation ### The data was generated by the merge of different data sets. 1.) Patent data from USPTO was downloaded here: https://bulkdata.uspto.gov/ 2.) Complementary data on grant year and patent title was taken from: https://cloud.google.com/blog/products/gcp/google-patents-public-datasets-connecting-public-paid-and-private-patent-data 3.) Citations to science come from the Reliance on Science (RoS) data set https://zenodo.org/record/3685972 (v23, Feb. 24, 2020) DOI: 10.5281/zenodo.3685972 The directory ("code") offers the R-scripts that were used to process MAG data and to link it to patent data. The header of the R-scripts offer additional technical information about the subsetting procedures and data retrieval. For more information about the patent data, see: Pichler, A., Lafond, F. & J, F. D. (2020), Technological interdependencies predict innovation dynamics, Working paper pp. 1–33. URL: [https://arxiv.org/abs/2003.00580](https://arxiv.org/abs/2003.00580) For more information about MAG data, see: Marx, Matt, and Aaron Fuegi. "Reliance on science: Worldwide front‐page patent citations to scientific articles." Strategic Management Journal 41.9 (2020): 1572-1594. DOI: [https://doi.org/10.1002/smj.3145](https://doi.org/10.1002/smj.3145) Marx, Matt and Fuegi, Aaron, Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles. Boston University Questrom School of Business Research Paper No. 3331686. DOI: [http://dx.doi.org/10.2139/ssrn.3331686 ](http://dx.doi.org/10.2139/ssrn.3331686 ) ### Detailed information about the data ### - "all_papers.RData" : Data on scientific papers from Microsoft Academic Graph (MAG), 3 columns: Paper ID: Unique paper-identifier used by MAG Paper year: Year of publication cited: binary 0-1, indicates whether the paper is cited by a patent, citation links are made in the text body and front-page of the patent, and added by examiners and applicants. - "all_patents.RData" : Data on USPTO utility patents, 6 columns: Patent number: Number given by USPTO. Can be used for manual patent search in http://patft.uspto.gov/netahtml/PTO/srchnum.htm (numeric) Patent year: Year when the patent was granted (numeric) CPC class: Detailed 8-digit CPC code (numeric) Patent date: Exact date of patent granting (numeric) Patent title: Short title (character) citing_to_science: binary 0-1, indicates whether the patent is citing to science as identified by citation links in RoS. (numeric) - "LCET_patents.RData" : Subset of LCET patents, 6 columns: Patent number: (numeric) Patent year: (numeric) Technology type: Short code used to tag 10 different types of LCET (pv, (nuclear) fission, (solar) thermal, (nuclear) fusion, wind, geo(termal), sea (ocean power), hydro, biofuels, (fuels from) waste) (character) CPC class: Detailed 8-digit CPC code (character) Patent date: (numeric) Patent title: (numeric) - "LCET_patent_citations.RData" : Citations from LCET patents to other patents, 2 columns: citing: Number of citing patent (numeric) cited: Number of cited patent (numeric) - "LCET_subset_with_metainfo_final.RData" : Citations from LCET patents to scientific papers from MAG, complemented by meta-information on patents and papers, 18 columns: Patent number: see above (numeric) Paper ID: see above (numeric) Patent year: see above (numeric) Paper year: see above (numeric) Technology type: see above (character) WoS field: Web of Science field of research, WoS fields were probabilistically assigned to papers and are used as given by RoS (character) Patent title: see above (character) Paper title: Title of scientific article (character) DOI: Paper DOI if available (character) Confidence Score: Reliability score of citation link (numeric). Links were probabilistically assigned. See Marx and Fuegi 2019 for further detail. Citation type: Indicates whether citation made in text body of patent document or its front page (character) Reference type: Examiner or applicant added citation link (or unknown). (character) Journal/ Conf. name: Name of journal or conference proceeding where the cited paper was published (character) Journal ID: Journal identifier in MAG (numeric) Conference ID: Conference identifier in MAG (numeric) CPC class: see above (character) Patent date: see above (numeric) US patent: binary US-patent indicator as provided by RoS (numeric) - "patent:citations.RData": Patent citations among all patents (not only LCET), 2 columns: citing: Number of citing patent (numeric) cited: Number of cited patent (numeric) **Note:** The citation links were probabilistically retrieved. During the analysis, we identified manually some false-positives are removed them from the "LCET_subset_with_metainfo_final.RData" data set. The list is available, too: "list_of_false_positives.tsv" We do not claim to have a perfect coverage, but expect a precision of >98% as described by Marx and Fuegi 2019. ### Statistics about the data ### Full data set: - #papers in MAG: 179,083,029 - #all patents: 10,160,667 - #citing patents: 2,058,233 - #cited papers: 4,404,088 - #citation links from patents to papers: 34,959,193 LCET subset: - #LCET patents: 65,305 - #citing LCET patents: 22,017 - #cited papers: 103,645 - #citation links from LCET patents to papers: 396,504 Meta-information: Papers: - Publication year, 251 Web-of-Science (WoS) categories, Journal/ conference proceedings name, DOI, Paper title Patents: - Grant year, >240,000 hierarchical CPC classes, 10 LCET types Citation links: - Reference type, citation type, reliability score If you have further questions about the data or suggestions, please contact: **kerstin.hotte@oxfordmartin.ox.ac.uk** ### Acknowledgements ### The authors want to thank the Center for Research Data Management of Bielefeld University and in particular Cord Wiljes for excellent support. ### License issues ### Terms of use of the source data: - Reliance on Science data [https://zenodo.org/record/3685972](https://zenodo.org/record/3685972), Open Data Commons Attribution License (ODC-By) v1.0, https://opendatacommons.org/licenses/by/1.0/ - "Google Patents Public Data” by IFI CLAIMS Patent Services and Google (https://cloud.google.com/blog/products/gcp/google-patents-public-datasets-connecting-public-paid-and-private-patent-data), Creative Commons Attribution 4.0 International License (CC BY 4.0), https://console.cloud.google.com/marketplace/details/google_patents_public_datasets/google-patents-public-data - USPTO patent data (https://bulkdata.uspto.gov/), see: https://bulkdata.uspto.gov/data/2020TermsConditions.docx
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Dittmann, Anna; Dinger, Florian; Herzberg, Wiebke; Holland, Nicolas; Karalus, Steffen; Braun, Christian; Zähringer, Ralph; Heydenreich, Wolfgang; Lorenz, Elke;The PV-Live dataset comprises data from a network of 40 solar irradiance measurement stations across the German state of Baden-Württemberg. All stations measure global horizontal irradiance and temperature with a pyranometer, and global tilted irradiance in east, south, and west direction with tilt angles of 25° with three photovoltaic reference cells in minute resolution. A quality control scheme has been developed specifically for this dataset and is applied to the measurements before publication. The minute resolution irradiance and temperature measurements are published with the derived quality flags. A description of the dataset and the quality control scheme is given in Lorenz et al. (2022) and Lorenz et al. (2020). The dataset contains data from September 2020 onwards. It will be continuously extended by adding data of the previous month on a monthly basis. QUALITY FLAGS Two types of flags are provided with the data. Each sensor is assigned a general quality flag, which is based on a combination of different tests. In addition, a shading flag is given, which is not sensor specific, i.e. it applies to all irradiance sensors simultaneously. The flags can have the levels 'passed, all tests complete', 'passed, not all tests complete', 'failed tests, likely erroneous' or 'failed tests, most likely erroneous'. If the flag level of the general quality flags is 'failed tests, most likely erroneous' the corresponding measurement value is set to NaN. DATA FORMAT The data is published as monthly .zip archives. Each archive contains the following files: 1. Tab separated data files (tng000XX_YYYY-MM.tsv) for each station, containing measurements and quality flags of one month 2. Tab separated station location metadata (metadata_stations_YYYY-MM.tsv) 3. Metadata of the dataset describing variable names and quality flag levels (metadata_measurements.json) 4. General comments on data availability and quality for the month (comments_quality_control_YYYY-MM.txt) 5. Log file of changes (change_log_YYYY-MM.txt) Station location metadata is given on a monthly basis because stations can be relocated. Therefore, we recommend to use the metadata valid for its corresponding month. VERSION UPDATES Version 7: - Recalculation of height information for all stations - One station has been moved to a new, nearby location on 16th September 2021 ACKNOWLEDGEMENTS The data have been collected and processed by Fraunhofer ISE in the framework of PV-Live, a project in cooperation with TransnetBW. We thank our station partners for cooperation in installing and maintaining our measurement stations: EnBW Solar, Badenova, Pohlen Solar, Oekogeno Solar7, Ecovision, Hochschule Ulm, Hofgemeinschaft Heggelbach, Soltechnics-solution and the Stadtwerke Karlsruhe, Grünstadt, Buchen, Crailsheim, Schwäbisch Hall, Pforzheim, Konstanz, Waldshut-Tiengen, Schwäbisch Gmünd, Ravensburg, Eberbach, Baden-Baden.
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