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Research data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Funded by:EC | Open ENTRANCEEC| Open ENTRANCEAuthors:O'Reilly, Ryan;
O'Reilly, Ryan
O'Reilly, Ryan in OpenAIRECohen, Jed;
Cohen, Jed
Cohen, Jed in OpenAIREReichl, Johannes;
Reichl, Johannes
Reichl, Johannes in OpenAIREThree data files are provided for Case Study 1 in the openENTRANCE project: Full_potential.V9.csv, metaData.Full_Potential.csv, and acheivable_NUTS2_summary.csv. The data covers 10 residential devices on the NUTS2 level for the EU27 + UK +TR + NO + CH from 2020-2050. The devices included are storage heater, water heater with storage capabilitites, air conditiong, heat circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier. Full_potential.V9.csv shows the NUTS2 level unadjusted loads for residential storage heater, water heater, air conditiong, circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier using representative hours from 2020-2050. The loads provided here have not been adjusted with the direct load participation rates (see paper for more details). More details on the dataset can be found in the metaData.Full_Potential.csv file. The acheivable_NUTS2_summary.csv shows the NUTS2 level acheivable direct load control potentials for the average hour in the respective year (years - 2020, 2022,2030,2040, 2050).
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visibility 26visibility views 26 download downloads 33 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 SpainPublisher:MDPI AG Authors:Daniel Icaza;
Daniel Icaza
Daniel Icaza in OpenAIREDavid Borge-Diez;
David Borge-Diez
David Borge-Diez in OpenAIRESantiago Pulla Galindo;
Carlos Flores-Vázquez;Santiago Pulla Galindo
Santiago Pulla Galindo in OpenAIREdoi: 10.3390/en16104045
handle: 2117/393220
This research presents a 100% renewable energy (RE) scenario by 2050 with a high share of electric vehicles on the grid (V2G) developed in Ecuador with the support of the EnergyPLAN analysis tool. Hour-by-hour data iterations were performed to determine solutions among various features, including energy storage, V2G connections that spanned the distribution system, and long-term evaluation. The high participation in V2G connections keeps the electrical system available; meanwhile, the high proportions of variable renewable energy are the pillar of the joint electrical system. The layout of the sustainable mobility scenario and the high V2G participation maintain the balance of the electrical system during most of the day, simplifying the storage equipment requirements. Consequently, the influence of V2G systems on storage is a significant result that must be considered in the energy transition that Ecuador is developing in the long term. The stored electricity will not only serve as storage for future grid use. Additionally, the V2G batteries serve as a buffer between generation from diversified renewable sources and the end-use stage.
Universitat Politècn... arrow_drop_down Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledgeArticle . 2023License: CC BYFull-Text: https://www.mdpi.com/1996-1073/16/10/4045Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticleLicense: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en16104045&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 7 citations 7 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 12visibility views 12 download downloads 4 Powered bymore_vert Universitat Politècn... arrow_drop_down Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledgeArticle . 2023License: CC BYFull-Text: https://www.mdpi.com/1996-1073/16/10/4045Data sources: Bielefeld Academic Search Engine (BASE)Recolector de Ciencia Abierta, RECOLECTAArticleLicense: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023Publisher:MDPI AG Authors:Andrzej Kubik;
Andrzej Kubik
Andrzej Kubik in OpenAIREKatarzyna Turoń;
Katarzyna Turoń
Katarzyna Turoń in OpenAIREPiotr Folęga;
Piotr Folęga
Piotr Folęga in OpenAIREFeng Chen;
Feng Chen
Feng Chen in OpenAIREdoi: 10.3390/en16052185
Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions.
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For further information contact us at helpdesk@openaire.euAccess Routesgold 12 citations 12 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:NSF | Collaborative research: U...NSF| Collaborative research: Understanding the effects of acidification and hypoxia within and across generations in a coastal marine fishAuthors:Murray, Christopher S;
Murray, Christopher S
Murray, Christopher S in OpenAIREBaumann, Hannes;
Baumann, Hannes
Baumann, Hannes in OpenAIREWhether marine fish will grow differently in future high pCO2 environments remains surprisingly uncertain. Long-term and whole-life cycle effects are particularly unknown, because such experiments are logistically challenging, space demanding, exclude long-lived species, and require controlled, restricted feeding regimes—otherwise increased consumption could mask potential growth effects. Here, we report on repeated, long-term, food-controlled experiments to rear large populations (>4,000 individuals total) of the experimental model and ecologically important forage fish Menidia menidia (Atlantic silverside) under contrasting temperature (17°, 24°, and 28°C) and pCO2 conditions (450 vs. 2,200 μatm) from fertilization to a third of this annual species' life span. Quantile analyses of trait distributions showed mostly negative effects of high pCO2 on long-term growth. At 17°C and 28°C, but not at 24°C, high pCO2 fish were significantly shorter [17°C: -5 to -9%; 28°C: -3%] and weighed less [17°C: -6 to -18%; 28°C: -8%] compared to ambient pCO2 fish. Reductions in fish weight were smaller than in length, which is why high pCO2 fish at 17°C consistently exhibited a higher Fulton's k (weight/length ratio). Notably, it took more than 100 days of rearing for statistically significant length differences to emerge between treatment populations, showing that cumulative, long-term CO2 effects could exist elsewhere but are easily missed by short experiments. Long-term rearing had another benefit: it allowed sexing the surviving fish, thereby enabling rare sex-specific analyses of trait distributions under contrasting CO2 environments. We found that female silversides grew faster than males, but there was no interaction between CO2 and sex, indicating that males and females were similarly affected by high pCO2. Because Atlantic silversides are known to exhibit temperature-dependent sex determination, we also analyzed sex ratios, revealing no evidence for CO2-dependent sex determination in this species. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-12-25.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.926048&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.926048&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:[no funder available]Authors: Spisla, Carsten;Bach, Lennart Thomas;
Bach, Lennart Thomas
Bach, Lennart Thomas in OpenAIRETaucher, Jan;
Taucher, Jan
Taucher, Jan in OpenAIREBoxhammer, Tim;
+1 AuthorsBoxhammer, Tim
Boxhammer, Tim in OpenAIRESpisla, Carsten;Bach, Lennart Thomas;
Bach, Lennart Thomas
Bach, Lennart Thomas in OpenAIRETaucher, Jan;
Taucher, Jan
Taucher, Jan in OpenAIREBoxhammer, Tim;
Boxhammer, Tim
Boxhammer, Tim in OpenAIREYong, Jaw-Chuen;
Yong, Jaw-Chuen
Yong, Jaw-Chuen in OpenAIRETo evaluate the influence of episodic extreme ocean acidification events in coastal regions, we deployed eight pelagic mesocosms for 53 days in Raunefjord, Norway, and enclosed 60 m³ of local seawater containing a natural plankton community under post-bloom conditions. Four mesocosms were manipulated to simulate extreme pCO2 levels of 2069 µatm while the other four served as untreated controls. To monitor the effects of extreme pCO2 conditions, a variety of physical, ecological, and biogeochemical parameters inside and outside the mesocosms were measured over the course of the experiment in regular intervals.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2020License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2020License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.911638&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Embargo end date: 01 Nov 2018Publisher:Mendeley Authors: Zhou, W;This is the second paper in a series of two that introduce our research on dynamic programming on new energy vehicles. In the first paper, we introduce the four main problems (the interpolation leakage problem, the dimension disaster problem, the standardization problem and the Markov problem) of dynamic programming on new energy vehicles, and put forward a unified dynamic programming model and its solution method for electric vehicles and hybrid electric vehicles. In this paper, we present a unified dynamic programming model and its solution method to solve these problems for fuel cell electric vehicles. The results demonstrate that the proposed method is much better than Basic Dynamic Programming and Level-Set Dynamic Programming in both calculation time and computation accuracy.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: von Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; +58 Authorsvon Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; Kirchengast, Gottfried; Adusumilli, Susheel; Straneo, Fiammetta; Allan, Richard; Barker, Paul M.; Beltrami, Hugo; Boyer, Tim; Cheng, Lijing; Church, John; Desbruyeres, Damien; Dolman, Han;Domingues, Catia M.;
García-García, Almudena; Gilson, John; Gorfer, Maximilian; Haimberger, Leopold; Hendricks, Stefan; Hosoda, Shigeki; Johnson, Gregory C.; Killick, Rachel; King, Brian A.; Kolodziejczyk, Nicolas; Korosov, Anton;Domingues, Catia M.
Domingues, Catia M. in OpenAIREKrinner, Gerhard;
Kuusela, Mikael; Langer, Moritz; Lavergne, Thomas; Lawrence, Isobel; Li, Yuehua; Lyman, John; Marzeion, Ben; Mayer, Michael; MacDougall, Andrew; McDougall, Trevor; Monselesan, Didier Paolo; Nitzbon, Jean; Otosaka, Inès;Krinner, Gerhard
Krinner, Gerhard in OpenAIREPeng, Jian;
Purkey, Sarah; Roemmich, Dean; Sato, Kanako; Sato, Katsunari;Peng, Jian
Peng, Jian in OpenAIRESavita, Abhishek;
Schweiger, Axel; Shepherd, Andrew; Seneviratne, Sonia I.; Slater, Donald A.; Slater, Thomas; Simons, Leon; Steiner, Andrea K.; Szekely, Tanguy; Suga, Toshio; Thiery, Wim; Timmermanns, Mary-Louise; Vanderkelen, Inne; Wijffels, Susan E.; Wu, Tonghua; Zemp, Michael;Savita, Abhishek
Savita, Abhishek in OpenAIREProject: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors:Dix, Martin;
Bi, Daohua;Dix, Martin
Dix, Martin in OpenAIREDobrohotoff, Peter;
Fiedler, Russell; +30 AuthorsDobrohotoff, Peter
Dobrohotoff, Peter in OpenAIREDix, Martin;
Bi, Daohua;Dix, Martin
Dix, Martin in OpenAIREDobrohotoff, Peter;
Fiedler, Russell;Dobrohotoff, Peter
Dobrohotoff, Peter in OpenAIREHarman, Ian;
Harman, Ian
Harman, Ian in OpenAIRELaw, Rachel;
Law, Rachel
Law, Rachel in OpenAIREMackallah, Chloe;
Mackallah, Chloe
Mackallah, Chloe in OpenAIREMarsland, Simon;
O'Farrell, Siobhan; Rashid, Harun;Marsland, Simon
Marsland, Simon in OpenAIRESrbinovsky, Jhan;
Srbinovsky, Jhan
Srbinovsky, Jhan in OpenAIRESullivan, Arnold;
Sullivan, Arnold
Sullivan, Arnold in OpenAIRETrenham, Claire;
Trenham, Claire
Trenham, Claire in OpenAIREVohralik, Peter;
Vohralik, Peter
Vohralik, Peter in OpenAIREWatterson, Ian;
Williams, Gareth;Watterson, Ian
Watterson, Ian in OpenAIREWoodhouse, Matthew;
Woodhouse, Matthew
Woodhouse, Matthew in OpenAIREBodman, Roger;
Bodman, Roger
Bodman, Roger in OpenAIREDias, Fabio Boeira;
Dias, Fabio Boeira
Dias, Fabio Boeira in OpenAIREDomingues, Catia M.;
Hannah, Nicholas;Domingues, Catia M.
Domingues, Catia M. in OpenAIREHeerdegen, Aidan;
Heerdegen, Aidan
Heerdegen, Aidan in OpenAIRESavita, Abhishek;
Savita, Abhishek
Savita, Abhishek in OpenAIREWales, Scott;
Allen, Chris; Druken, Kelsey;Wales, Scott
Wales, Scott in OpenAIREEvans, Ben;
Richards, Clare; Ridzwan, Syazwan Mohamed; Roberts, Dale; Smillie, Jon;Evans, Ben
Evans, Ben in OpenAIRESnow, Kate;
Snow, Kate
Snow, Kate in OpenAIREWard, Marshall;
Yang, Rui;Ward, Marshall
Ward, Marshall in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CSIRO-ARCCSS.ACCESS-CM2.ssp245' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Climate Model Version 2 climate model, released in 2019, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: CABLE2.5, ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE5.1.2 (same grid as ocean). The model was run by the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science). Mailing address: CSIRO, c/o Simon J. Marsland, 107-121 Station Street, Aspendale, Victoria 3195, Australia (CSIRO-ARCCSS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Authors:Ulrich, Veit;
Brückner, Josephine; Schultz, Michael;Ulrich, Veit
Ulrich, Veit in OpenAIREVardag, Sanam;
+5 AuthorsVardag, Sanam
Vardag, Sanam in OpenAIREUlrich, Veit;
Brückner, Josephine; Schultz, Michael;Ulrich, Veit
Ulrich, Veit in OpenAIREVardag, Sanam;
Vardag, Sanam
Vardag, Sanam in OpenAIRELudwig, Christina;
Ludwig, Christina
Ludwig, Christina in OpenAIREFürle, Johannes;
Fürle, Johannes
Fürle, Johannes in OpenAIREZia, Mohammed;
Zia, Mohammed
Zia, Mohammed in OpenAIRELautenbach, Sven;
Lautenbach, Sven
Lautenbach, Sven in OpenAIREZipf, Alexander;
Zipf, Alexander
Zipf, Alexander in OpenAIREWe estimated the annual average daily GHG emissions from individual motor traffic for the OSM road network in Berlin by combining the estimated Annual Average Daily Traffic Volume (AADTV) with respective emission factors. The AADTV was calculated by simulating car trips with the open routing engine Openrouteservice, weighted by activity functions based on statistics of the German Mobility Panel.
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visibility 39visibility views 39 download downloads 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | MAT_STOCKSEC| MAT_STOCKSHaberl, Helmut; Wiedenhofer, Dominik; Schug, Franz; Frantz, David; Virag, Doris; Plutzar, Christoph; Gruhler, Karin; Lederer, Jakob; Schiller, Georg; Fishman, Tomer; Lanau, Maud; Gattringer, Andreas; Kemper, Thomas; Liu, Gang; Tanikawa, Hiroki; van der Linden, Sebastian; Hostert, Patrick;Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.
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