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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: orcid Poul Alberg Østergaard;
    Poul Alberg Østergaard
    ORCID
    Harvested from ORCID Public Data File

    Poul Alberg Østergaard in OpenAIRE
    orcid Anders N. Andersen;
    Anders N. Andersen
    ORCID
    Harvested from ORCID Public Data File

    Anders N. Andersen in OpenAIRE

    Abstract District heating (DH) enables the utilisation and distribution of heating from sources unfeasible for stand-alone applications and combined with cogeneration of heat and power (CHP), has been the cornerstone of Denmark’s realisation of a steady national primary energy supply over the last four decades. However, progressively more energy-efficient houses and a steadily improving heat pump (HP) performance for individual dwellings is straining the competitive advantage of the CHP–DH combination as DH grid losses are growing in relative terms due to decreasing heating demands of buildings and relatively high DH supply temperatures. A main driver for the DH water temperature is the requirements for domestic hot water (DHW) production. This article investigates two alternatives for DHW supply: (a) DH based on central HPs combined with a heat exchanger, and (b) a combination of DH based on central HPs and a small booster HP using DH water as low-temperature source for DHW production. The analyses are conducted using the energyPRO simulation model and are conducted with hourly varying factors; heating demands, DH grid losses, HP coefficient of performance (COP) and spot market prices in order to be able to analyse the relative performance of the two options and their performance over the year. Results are also compared to individual boilers and individual HPs. The results indicate that applying booster HPs enables the DH system to operate at substantially lower temperature levels, improving the COP of central DH HPs while simultaneously lowering DH grid losses significantly. Thus, DH performance is increased significantly. Additionally, performance for the DH HP with booster combination is considerably better than individual boiler or HP solutions.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Applied Energyarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Applied Energy
    Article . 2016 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    VBN
    Article . 2016
    Data sources: VBN
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    citations146
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Applied Energyarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Applied Energy
      Article . 2016 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Crossref
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      VBN
      Article . 2016
      Data sources: VBN
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid bw Lorenzo Colone;
    Lorenzo Colone
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Lorenzo Colone in OpenAIRE
    orcid Nikolay Dimitrov;
    Nikolay Dimitrov
    ORCID
    Harvested from ORCID Public Data File

    Nikolay Dimitrov in OpenAIRE
    orcid Daniel Straub;
    Daniel Straub
    ORCID
    Harvested from ORCID Public Data File

    Daniel Straub in OpenAIRE

    AbstractWe devise a methodology to predict failures in wind turbine drive‐train components and quantify its utility. The methodology consists of two main steps. The first step is the set up of a predictive model for shutdown events, which is able to raise an alarm in advance of the fault‐induced shutdown. The model is trained on data for shutdown events retrieved from the alarm log of an offshore wind farm. Here, it is assumed that the timely prediction of low‐severity events, typically caused by abnormal component operation, allows for an intervention that can prevent premature component failures. The prediction models are based on statistical classification using only supervisory control and data acquisition (SCADA) data. In the second step, the shutdown prediction model is combined with a cost model to provide an estimate of the benefits associated with implementing the predictive maintenance system. This is achieved by computing the maximum net utility attainable as a function of the model performance and efficiency of intervention carried out by the user. Results show that the system can be expected to be cost‐effective under specific conditions. A discussion about potential improvements of the approach is provided, along with suggestions for further research in this area.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Wind Energyarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Wind Energy
    Article . 2019 . Peer-reviewed
    License: Wiley Online Library User Agreement
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Wind Energyarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Wind Energy
      Article . 2019 . Peer-reviewed
      License: Wiley Online Library User Agreement
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid bw Manuela Mancini;
    Manuela Mancini
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Manuela Mancini in OpenAIRE
    orcid bw Åsmund Rinnan;
    Åsmund Rinnan
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Åsmund Rinnan in OpenAIRE

    The three datasets contain the spectral data acquired on waste wood samples using a handheld spectrophotometer (MicroNIR™ OnSite instrument). The waste wood samples have been collected in a panel board company located in the Northern part of Italy during two days of sampling (February 18-19, 2020). In detail, 24 randomly distributed increments have been collected from 16 static lots, resulting in a total of 384 samples (we note these DT-SamTot). All the samples have been analyzed by Near-Infrared (NIR) spectrophotometer directly on site. In addition, four of the 24 increments for each lot - resulting in a total of 64 samples - have been sent to the lab for further analysis (DT-Lab). Additionally, another dataset has been created based on a reduced DT-SamTot dataset, where we only consider the four of 24 increments for each lot that were sent to the lab (DT-SamRed). It is important for having more accurate indications about the differences in variability between DT-Lab and DT-SamTot samples. We provide three CSV files: DT-Sam_Tot_270521_v01.csv: spectral data and information of DT-SamTot.; DT-Sam_Red_270521_v01.csv: spectral data and information of DT-SamRed. DT-Lab_270521_v01.csv: spectral data and information of DT-Lab. The three CSV files contain similar information in the columns: Sample code: it is reporting the sample code where S1 is the number of lot, the successive number is the number of sample (from 1 to 24) and the last number the NIR replicate. E.g. S4-13-1.sam: lot number 4, sample number 13, NIR replicate number 1. Please note that for DT-Lab dataset we have a different coding where labA and labB are the two sample replicates for the moisture content analysis. Rep: number indicating the NIR replicates for each sample. Please note that for DT-Lab dataset we have also rep2 column reporting the sample replicates for the moisture content analysis. Lot: number of lot to which the sample belongs (from 1 to 16). Day: day in which the sample has been collected (1 = 18/02/2020; 2 = 19/02/2020). Mois: moisture content of the sample (%). PCN: net calorific value of the sample (J/g). Spectral data: absorbance values for each sample from 908.1 nm to 1676.2 nm. The aim behind this dataset is to investigate the variability of the waste wood (WP1 of WoodSpec project) and this information is essential for increasing the reuse of the material and guarantee an accurate and successful use of a NIR sensor into real industrial applications. A second aim is the development of regression models for predicting the moisture content and net calorific value of the samples (WP3 of WoodSpec project). First indications about the variability and the chemical-physical characteristics of the material are essential for determining the suitability in energy applications. If you would like know more about the data, or to use these data, please refer to our article in Renewable Energy, doi: https://doi.org/10.1016/j.renene.2021.05.137 Funding: The project leading to this application has received funding from theEuropean Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 838560. Terms of use: These data are provided "as is", without any warranties of any kind. The data are provided under the Creative Commons Attribution 4.0 International license.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Qiming Zheng;
    Qiming Zheng
    ORCID
    Harvested from ORCID Public Data File

    Qiming Zheng in OpenAIRE
    Tim Ha; orcid Alexander V. Prishchepov;
    Alexander V. Prishchepov
    ORCID
    Harvested from ORCID Public Data File

    Alexander V. Prishchepov in OpenAIRE
    orcid Yiwen Zeng;
    Yiwen Zeng
    ORCID
    Harvested from ORCID Public Data File

    Yiwen Zeng in OpenAIRE
    +2 Authors

    Abstract Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr− 1 of food production potential and 290 to 1,066 MtCO2 yr− 1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.2...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.21203/rs.3....
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Communications
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Nature Communications
    Article . 2023
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.2...arrow_drop_down
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      https://doi.org/10.21203/rs.3....
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nature Communications
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Article . 2023
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    Authors: orcid Riti Thapar Kapoor;
    Riti Thapar Kapoor
    ORCID
    Harvested from ORCID Public Data File

    Riti Thapar Kapoor in OpenAIRE
    orcid Mohd Rafatullah;
    Mohd Rafatullah
    ORCID
    Harvested from ORCID Public Data File

    Mohd Rafatullah in OpenAIRE
    orcid bw Masoom Raza Siddiqui;
    Masoom Raza Siddiqui
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Masoom Raza Siddiqui in OpenAIRE
    orcid bw Moonis Ali Khan;
    Moonis Ali Khan
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Moonis Ali Khan in OpenAIRE
    +1 Authors

    Removal of Reactive Black 5 (RB5) dye from an aqueous solution was studied by its adsorption on banana peel biochars (BPBs). The factors affecting RB5 dye adsorption such as pH, exposure time, RB5 dye concentration, adsorbent dose, particle size and temperature were investigated. Maximum 97% RB5 dye removal was obtained at pH 3 with 75 mg/L adsorbate concentration by banana peel biochars. Fourier transform infrared (FTIR) and scanning electron microscopy (SEM) were used to characterize the adsorbent material. The data of equilibrium were analyzed by Langmuir and Freundlich isotherm models. The experimental results were best reflected by Langmuir isotherm with maximum 7.58 mg/g adsorption capacity. Kinetic parameters were explored and pseudo-second order was found suitable which reflected that rate of adsorption was controlled by physisorption. Thermodynamic variables exhibited that the sorption process was feasible, spontaneous, and exothermic in nature. Banana peel biochar showed excellent regeneration efficiency up to five cycles of successive adsorption-desorption. Banana peel biochar maintained >38% sorption potential of RB5 dye even after five cycles of adsorption-desorption. The phytotoxic study exhibited the benign nature of BPB-treated RB5 dye on tomato seeds.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sustainabilityarrow_drop_down
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    Sustainability
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Sustainability
    Article . 2022
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sustainabilityarrow_drop_down
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      Sustainability
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    Authors: orcid Pedro Cabrera;
    Pedro Cabrera
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    orcid Henrik Lund;
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    orcid José A. Carta;
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    This paper presents a new method, based on the Smart Energy Systems concept. The aim is to increase the share of renewable energy penetration on islands. The method is applied to the island of Gran Canaria (Spain), considering the entire energy system of the island. Several smart renewable energy strategies are proposed following a cross-sectoral approach between the electricity, heating/cooling, desalination, transport and gas sectors. The different smart renewable energy strategies were applied in a series of steps, while looking for a transition from the current energy system to a nearly 100% renewable energy system. Based on the results, the study concludes that the suggested method is applicable for increasing renewable integration on islands and can potentially be used in helping energy planners to take decisions about priorities in development of the sector to improve such integration. The results indicate that, for the case of Gran Canaria, a 75.9% renewable energy system could be attained with technologies that can be implemented at present. Furthermore, it is shown that a nearly 100% renewable energy system in Gran Canaria is technically feasible and could be achieved if certain technologies acquire greater maturity. © 2018 Elsevier Ltd 443 421 2,048 5,537 Q1 Q1 SCIE

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    Authors: W. de Jong; C. Tsekos; P.L. Schoenmakers; orcid Konstantinos Anastasakis;
    Konstantinos Anastasakis
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    Konstantinos Anastasakis in OpenAIRE
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    The present work focuses on the sampling procedure and quantification of the PAH yield from the fast pyrolysis of waste softwood. In particular, fast pyrolysis experiments were conducted using a CDS Pyroprobe 5200 at temperatures between 500 °C and 1000 °C, at a heating rate of 600 °C/s for a sample size of 30 mg. High performance liquid chromatography (HPLC) was used for the determination of the PAH compounds present in the liquid sample fraction, while a micro – GC was employed for the analysis of the main gaseous products (CO, CO2, CH4 and H2). An alternative tar sampling protocol was proposed, which employed the use of a cold trap (50 °C) and an isopropanol filled impinger bottle for the collection of the condensable products. The experiments were compared to heated foil reactor based pyrolysis tests within the same temperature range and heating rate, except for a slightly lower sample size (10 mg). The Pyroprobe and adapted sampling system proved to be more efficient regarding PAH capture and quantification compared to the heated foil reactor. Naphthalene, acenaphthylene and phenanthrene were the main PAH compounds detected. The PAH yields increased with pyrolysis temperature, up to values corresponding to roughly 0.2 wt% of the overall yield at 1000 °C. From the results it was derived that PAH evolution is mainly a product of secondary decomposition of primary tar, since the char yield stabilized for higher temperatures and the yields of CO, H2 and CH4 increased. Overall mass balance closure values were around 80 wt% on average. Char and gas yields were determined with high reproducibility, however gravimetric liquid analysis lacked due to the inability to gravimetrically measure the yield condensing in the impinger bottle. Future work is aimed on improving on this particular aspect. Overall, the alternative tar sampling system proposed was successful in the quantification of PAH from biomass fast pyrolysis experiments offering increased flexibility, accuracy and practicality of use.

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    Journal of Analytical and Applied Pyrolysis
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    Authors: orcid bw Le Meillour, Louise;
    Le Meillour, Louise
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    Le Meillour, Louise in OpenAIRE
    orcid bw Sinet-Mathiot, Virginie;
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    Ásmundsdóttir, Ragnheiður Diljá; Hansen, Jakob; +8 Authors

    Six bones from La Draga (Spain, Holocene, samples LD_01 to LD_06) and Bayisha Karst Cave (China, Pleistocene, samples BKC_07 to BKC_12) were sampled for this study. Initial sampling was divided into three sub-samples for the three digestion durations tested here (site code_sample number_3h, site code_sample number_6h, and site code_sample number_18h). Samples were then processed according to the ZooMS protocol: they were demineralised in 0.6 M hydrochloric acid (HCl) for 24 hours. The HCl supernatant was then removed and samples were rinsed thrice in 100 µL ammonium bicarbonate (50 mM, NH4HCO3, hereafter AmBic) for subsequent gelatinisation in a final volume of 100 µL AmBic for one hour at 65°C. Following gelatinisation, the 100 µL of the AmBic solution was transferred to a new microtube, to which 0.8 µg trypsin (Promega) was added for incubation at 37°C, with mild agitation at 300 rpm (VWR, Thermal Shake lite). Digestion occurred for either 3, 6, or 18 hours. To stop trypsin digestion, 2 µL of 5% trifluoroacetic acid (TFA) was added to each sample. The digested extracts were then split into two parts for separate analyses via matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI-ToF MS) and liquid-chromatography tandem mass spectrometry (LC-MS/MS). To assess any potential contamination by non-endogenous peptides, we performed the extraction of laboratory blanks alongside the samples for each enzymatic digestion condition. Mass spectrometry analyses MALDI-ToF MS and ZooMS data analysis For ZooMS data analysis, before MALDI-ToF MS analysis, peptides were cleaned and desalted using C18 ZipTips (Thermo Fisher) and subsequently spotted in triplicate, consisting of 0.5 µL eluted peptides and 0.5 µL alpha-cyano-4-hydroxycinnamic acid (CHCA) matrix solution, on a 384-well Opti-ToF MALDI plate insert (AB Sciex, Framingham, MA, 01701, USA) and allowed to air-dry at room temperature. MALDI spectra were automatically acquired with an AB SCIEX 5800 MALDI-ToF spectrometer (Framingham, MA, 01701, USA) in positive reflector mode for MS acquisition. Before sample acquisition, an external plate model calibration was achieved on 13 adjacent MS standard spots with a standard peptide mix (Proteomix Peptide calibration mix4, LaserBioLabs, Sophia Antipolis, France) containing bradykinin fragment 1-5 (573.315 Da), human angiotensin II (1046.542 Da), neurotensin (1672.917 Da), ACTH fragment 18-39 (2464.199) and oxidised insulin B chain (3494.651 Da). The concentration in the prepared mixture was between 27 to 167 fmol/µL. The calibration was validated according to the laboratory specifications (resolution above 10000 for 573 Da, 12000 for 1046 Da, and 15 to 25000 for other masses, error tolerance <50ppm). For the spectra where peptides resulting from trypsin autolysis were detected, an internal recalibration was applied to decrease the error tolerance below 10 ppm (trypsin peptides: 842.509 Da, 1045.56 Da, and 2211.104 Da). Laser intensity was set at 50% after optimization of the signal-to-noise ratio on several spots, then operated at up to 3,000 shots accumulated per spot, covering a mass-to-charge range of 1000 to 3500 Da for sample analysis. The triplicate data files were merged in R and converted into .msd files. ZooMS taxonomic identifications were assessed using mMass through manual peptide marker mass identification in comparison to a database of peptide marker series for medium- to large-sized mammals. Glutamine deamidation values were calculated using the Betacalc3 package. Shotgun proteomics For SPIN data analysis, peptide extracts were first separated using an Evosep One (Evosep, Odense, Denmark) with the 100 samples-per-day method (cycle of 14.4 min). Loading of samples was conducted at a flow rate of 2 uL/min using mobile phases of A: 5% acetonitrile and 0.1% formic acid in H2O and B: 0.1% formic acid in H2O with a gradient of 11.5 min at 1.5 uL/min. A polymicro flexible fused silica capillary tubing of 150 um inner diameter and 16 cm long home-pulled was packed with C18 bounded silica particles of 1.9 um diameter (ReproSil-Pur, C18-AQ, Dr. Maisch, Germany). The column was mounted on an electrospray source with a column oven set at 60°C with a source voltage of +2000 V, along with an ion transfer tube set at 275°C. An Exploris 480 (Thermo Fisher Scientific) was operating in data-dependent mode consisting of a first MS1 scan at a resolution of 60 000 between m/z of 350 and 1400. The twelve most intense monoisotopic precursors were selected if above 2e5 intensity with a charge state between 2 and 6 and were then dynamically excluded after one appearance with their isotopes (20 ppm) for 20 seconds. The selected peptides were acquired on MS2 at Orbitrap resolving power of 15000, normalised collision energy (HCD) set at 30%, quadrupole isolation width of 1.3 m/z, and first m/z of 120. Quality control was assessed on HeLa cells using QC displayed of 1289 protein groups for 5561 peptides at a repeating sequencing of 2.90% on MaxQuant v.2.2.3.0. The following parameters were used for the search: the raw data were searched against the human full proteome, with carbamidomethyl (C) as fixed modification and oxidation (M) and acetyl (protein N term) as variable; digestion was set as tryptic and all other parameters were kept as default. MaxQuant search All .raw files were analysed using MaxQuant (v.2.3.1) in two different searches. The first search was performed as described in Ruther et al., 2022 against the protein sequences database provided there. Variable modifications included oxidation (M), deamidation (NQ), Gln (Q) -> pyro-Glu, Glu (E) -> pyro-Glu, and proline (P) hydroxylation. The internal MaxQuant contaminant list was replaced with an in-house database provided by Ruther et al., 2022 (Supplementary File PR200512_HumanCons.fasta). Since all specimens except for one were identified as belonging to either Bos sp. or Bison sp., a second search was performed against the whole Bos taurus reference proteome (downloaded from Uniprot on 2022-01-20) to explore the presence of other, additional non-collagenous proteins (NCPs). Variable modifications for this search included oxidation (M), deamidation (NQ), and proline (P) hydroxylation. The internal MaxQuant contaminant list was used. Both searches were run in semi-specific Trypsin/P digestion mode. Up to five variable modifications were allowed per peptide and all other settings were left as default for both searches. Measurement of electricity consumption A power monitor (Cowell, model no.: PMB01) was placed in between the heating block (VWR, Thermal Shake lite) and the utilised power outlet to measure electricity consumption using either 96-well plates or Eppendorf tubes for 18 hours at 37°C. The measurements for both tubes (1.5 mL Eppendorf Protein LoBind, Eppendorf) and plates (PCR Plate, 96-well, low profile, non-skirted, 0.3 mL, Thermo Fisher Scientific) were separately conducted over the time frame of 18 hours, and replicated thrice in total. Measurements started when the heating block had reached a stable temperature of 37°C. The maximum number of tubes, 40 units, were placed in the heating block with 100µL AmBic in each tube to imitate experiment conditions. Likewise, each well in the 96-well plate was filled with 100 µL AmBic. The emission intensity (gCO2eq; grams of carbon dioxide equivalent) was then calculated by alcesusing the kWh measured and gCO2eq/kWh values available through Electricity Maps for the dates on which our experiments were conducted. The gCO2eq/kWh values were obtained from various countries (Australia, Brazil, Germany, Denmark, France, Japan, the USA, and South Africa). With this selection, we hope to cover a range of countries where high-throughput palaeoproteomics facilities exist. Furthermore, countries differ significantly in the amount of carbon released for each unit of electricity consumed, the so-called carbon intensity, for example, due to the use of nuclear energy or largely completed transitions to wind and solar energy sources. The absolute impact of electricity consumption is therefore very different depending on the country, and our selection of countries aims to also cover this range of carbon intensities. Lastly, emission intensities were calculated for each tube and PCR plate well across the three digestion durations (18h, 6h, and 3h), and for each country included in the study. # Increasing sustainability in palaeoproteomics by optimizing digestion times for large-scale archaeological bone analyses [https://doi.org/10.5061/dryad.cz8w9gj8j](https://doi.org/10.5061/dryad.cz8w9gj8j) ## Description of the data and file structure Data deposited on Dryad are structured as follows: 1. Digestion_time_Datasheet.csv containing all information concerning sample names, experimental information (sampling amount), and the palaeoproteomics methods data tested in this study (ZooMS and SPIN). 2. Electicitymeasurement.csv concerning all data gathered during the measurement of electricity consumption of the three digestion times tested in the paper. 3. Three folders: Full proteome MQ (txt files generated after the MaxQuant search against Bos taurus full proteome); msd_files_3replicates (.msd files of all LC-MS/MS raw data) and a SPIN MQ (txt files generated after the MaxQuant search against the SPIN database). 4. Four R code markdowns with statistical analyses of the paper, figure generation, etc. (Full Proteome.Rmd; Main text figures.Rmd; SPIN.Rmd and ZooMS.Rmd). Empty cells in the .csv files indicate that no data were recorded or that the corresponding column does not apply. ## Sharing/Access information Data linked to this paper can be found here (for MALDI-MS raw data and associated spectra merging code): https://doi.org/10.5281/zenodo.8290650 and using identifier PXD045027 on the ProteomeXchange data repository (LC-MS/MS raw data and associated MaxQuant searches output files) ## Code/Software After spectral identification, proteomic data analysis was conducted largely through R v.4.1.2 using tidyverse v.1.3.1, seqinr v.4.2-8, ggpubr v.0.4.0, ggdist v.3.3.0, data.table v.1.14.2, ggsci v.2.9, progressr v.0.10.0, gmp v.0.6-6, reshape2 v.1.4.4, stringi v.1.7.6, MALDIquant v.1.2, MALDIquantForeign v.0.13, janitor v.2.2.0, and wesanderson v.0.3.6. The R scripts used for the shotgun proteomics analysis are available under Rüther et al., 2022. Deamidation was quantified based on spectral intensities. Depending on data types, statistics were calculated using two-way ANOVA (Type II and Type III), linear modelling from lmerTest v.3.1-3, lme4 v.1.1-34, MASS v.7.3-60, and Kruskal Wallis tests from carData v.3.0-5, car v.3.1-0, and rstatix v.0.7.2. As prerequisites for ANOVA tests, normal distribution of residuals was checked using the Shapiro-Wilk normality test and homogeneity of the variances was assessed by Levene’s test. Palaeoproteomic analysis of skeletal proteomes is used to provide taxonomic identifications for an increasing number of archaeological specimens. The success rate depends on a range of taphonomic factors and differences in the extraction protocols employed. By analyzing 12 archaeological bone specimens from two archaeological sites, we demonstrate that reducing digestion duration from 18 to 3 hours has no measurable impact on the obtained taxonomic identifications. Peptide marker recovery, COL1 sequence coverage, or proteome complexity are also not significantly impacted. Although we observe minor differences in sequence coverage and glutamine deamidation, these are not consistent across our dataset. A 6-fold reduction in digestion time reduces electricity consumption, and therefore CO2 emission intensities. We furthermore demonstrate that working in 96-well plates further reduces electricity consumption by 60%, in comparison to individual microtubes. Reducing digestion time therefore has no impact on the taxonomic identifications, while reducing the environmental impact of palaeoproteomic projects.

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    Authors: orcid bw Serena Fabbri;
    Serena Fabbri
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    Serena Fabbri in OpenAIRE
    orcid bw Mikołaj Owsianiak;
    Mikołaj Owsianiak
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    orcid bw Michael Zwicky Hauschild;
    Michael Zwicky Hauschild
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    Michael Zwicky Hauschild in OpenAIRE

    The supporting information of the journal article "Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment" from Fabbri et al. (2022) includes one file with the following content: S1 Details of consequential modelling: feedstock S1.1 Identification type of changes (demand or supply) S1.2 Identification of constrains in the market S1.3 Identification of product substitutions S1.4 Identification of affected production technology S1.5 Identification of marginal crop and marginal supplier S2 Details of consequential modelling: by-products S3 Model parameters and unit processes S3.1 Sugar beet S3.2 Sugar cane S3.3 Wheat S3.4 Maize S3.5 Wood S3.6 Residual woodchips and sawdust S4 Review of land use change accounting methods S4.1 Direct land use change (dLUC) S4.2. Indirect land use change (iLUC) S5 Additional results S5.1 Influence of spatial differentiation in LCIA S5.2 Influence of indirect land use change (iLUC) S6 References This work was funded by the Innovation Fund Denmark under the Grand Solutions instrument; project ReMEG "Renewable Mono Ethylene Glycol for PET Plastic".

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    Authors: orcid K Ebstrup;
    K Ebstrup
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    K Ebstrup in OpenAIRE
    orcid N N Sørensen;
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    N N Sørensen in OpenAIRE
    orcid F Bertagnolio;
    F Bertagnolio
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    F Bertagnolio in OpenAIRE
    orcid C Grinderslev;
    C Grinderslev
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    C Grinderslev in OpenAIRE
    +1 Authors

    Abstract The vortex-induced forces on an extruded cylinder with a span of two diameters representative of a finite segment of a non-tapered wind turbine tower at a very high Reynolds number (Re = 8.0×106) are numerically investigated using an incompressible Navier-Stokes flow solver with an Improved Delayed Detached Eddy Simulation (IDDES) turbulence model and correlation-based boundary layer transition modelling. The solution shows spanwise correlated structured vortex shedding with the Strouhal number St = 0.48. The boundary layer transition is found to occur at θ transition = 70 ◦ , and boundary layer separation is found to occur at θ separation = 120 ◦ . Results from the grid dependency study strongly imply that when using IDDES, the Strouhal number converges to higher values than previously reported by the literature as the grid is refined, with results ranging from St ∼ 0.44 using a grid with 4.2 × 106 cells, to St = 0.48 for the finest considered grid with 33 × 106 cells. This behaviour is not seen for URANS, where St = 0.33 for the finest grid.

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    Journal of Physics Conference Series
    Article . 2024 . Peer-reviewed
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      Journal of Physics Conference Series
      Article . 2024 . Peer-reviewed
      License: CC BY
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