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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: Dongyao Jia; Haibo Chen; Zuduo Zheng; David Watling; +3 Authors

    The predictive cruise control (PCC) is a promising method to optimize energy consumption of vehicles, especially the heavy-duty vehicles (HDV). Due to the limited sensing range and computational capabilities available on-board, the conventional PCC system can only obtain a sub-optimal speed trajectory based on a shorter prediction horizon. The recently emerging information and communication technologies such as vehicular communication, cloud computing, and Internet of Things provide huge potentials to improve the traditional PCC system. In this paper, we propose a general framework for the enhanced cloud-based PCC system which integrates a data-driven traffic predictive model and the instantaneous control algorithms. Specifically, we introduce a novel multi-view CNN deep learning algorithm to predict traffic situation based on the historical and real-time traffic data collected from fields, and the time-varying adaptive model predictive control (MPC) to calculate the instantaneous optimal speed profile with the aim of minimizing energy consumption. We verified our approach via simulations in which the impact of various traffic condition on the PCC-enabled HDV has been fully evaluated.

    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/ IEEE Transactions on...arrow_drop_down
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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/ IEEE Transactions on...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/
      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
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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: Vasilaki, V; Pijuan, M; Duan, H; Katsou, E;

    Chapter six of the Open Access book, 'Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems', published by IWA Publishing, is available online at https://iwaponline.com/ebooks/book/844/Quantification-and-Modelling-of-Fugitive . Copyright © 2022 The Authors and Editors. This chapter reviews the studies from N2 O and CH4 monitoring campaigns in full-scale wastewater treatment plants (WWTPs) and sewer networks. The focus is on greenhouse gas (GHG) emissions from WWTPs as more literature is available. The analysis classifies quantified N2 O and CH4 emission factors (EFs), triggering operational conditions and formation pathways for different configurations. Control strategies to minimize N2 O emissions are proposed for different process groups. The main reasons for EF discrepancies are discussed. Overall, N2 O emission factors for processes treating lowstrength wastewater streams range between 0.003 and 5.6% of the N-load (average equal to 0.9% of the N-load). Emissions higher than mainstream process average emissions have been reported in sequencing batch reactors (average equal to 3.6% of the influent N-load) and step-fed plug flow reactors. In full-scale sidestream processes, less than 15 monitoring campaigns have reported EFs (average equal to 2.5% of the N-load). Differences in the EFs among the process groups are partially attributed to disparities in the control strategies (i.e. aeration control), configuration, and operational and environmental conditions that favour the preferred enzymatic pathways. Overall, triggering operational conditions for elevated N2 O emissions in full-scale wastewater treatment processes include (i) increased NH4+ concentrations leading to a high ammonia oxidation rate (AOR) and increased production of intermediates (e.g. NH2 OH, NO−, etc.), (ii) improper aeration control (i.e. inadequate aeration and non-aeration duration, over-aeration, under-aeration), (iii) NO2− accumulation triggering the nitrifier denitrification pathway, and (iv) sudden shifts in incomplete heterotrophic denitrification (i.e. due to excess dissolved oxygen (DO), chemical oxygen demand (COD) limitation etc.). The N2 O monitoring strategies can also influence the reliability of the quantified EFs. Due to temporal variation of N2 O emissions, short-term studies are not sufficient to quantify annual EFs. The analysis showed that the average EF for processes treating low-strength streams monitored for less than a week is 0.66% of the influent N-load. On the other hand, processes monitored over 6 months have an average EF equal to 1.74%. Compared with N2 O, CH4 quantification from full-scale WWTPs is less investigated, while it also contributes significantly to the overall plant carbon footprint. The results of full-scale CH4 quantification studies are summarized in this chapter. Emissions of CH4 in WWTPs mainly originate from the influent, anaerobic wastewater treatment and anaerobic sludge handling processes. The amount of CH4 emissions varies greatly with different configurations of WWTPs. For WWTPs without anaerobic sludge handling processes, the CH4 emissions can mainly be traced back to the CH4 dissolved in the influent. When anaerobic treatment is applied in WWTPs for wastewater COD removal, its CH4 emissions might substantially increase the overall plant carbon footprint. GHG monitoring campaigns carried out in WWTPs should include the monitoring of fugitive CH4 emissions. Finally, CH4 and N2 O emissions reported from sewer networks are also summarized in this chapter. The last part of the chapter summarizes some mitigation strategies applied at full-scale to control fugitive CHG emissions from WWTPs and sewers. Maite Pijuan acknowledges the support from the Economy and Knowledge Department of the Catalan Government through a Consolidated Research Group (ICRA-TECH – 2017 SGR 1318) – Catalan Institute for Water Research and the Spanish Government through the Salvador de Madariaga mobility program (PRX19/00051). Vasileia Vasilaki and Evina Katsou would like to acknowledge the Horizon 2020 research and innovation program, SMART-Plant under grant agreement No 690323. Haoran Duan acknowledges the support of the Australian Research Council (ARC) through project DP180103369.

    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/ Brunel University Re...arrow_drop_down
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    Brunel University Research Archive
    Part of book or chapter of book . 2022
    License: CC BY NC ND
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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/ Brunel University Re...arrow_drop_down
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      Brunel University Research Archive
      Part of book or chapter of book . 2022
      License: CC BY NC ND
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    Authors: Vasileia Vasilaki; Maite Pijuan; Haoran Duan; Evina Katsou;
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    https://doi.org/10.2166/978178...
    Part of book or chapter of book . 2022 . Peer-reviewed
    License: CC BY NC ND
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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/10.2166/978178...
      Part of book or chapter of book . 2022 . Peer-reviewed
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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: Fraser Lott; Andrew Ciavarella; John Kennedy; Andrew King; +3 Authors

    <p><strong>Probabilistic event attribution aims to quantify the role of anthropogenic climate change in altering the intensity or probability of extreme climate and weather events. It was originally conceived to calculate the costs associated with any increased likelihood of the meteorological event in question. However, only recently have such studies attempted to divide liability between polluting nations and ascribe a cost. Recent protests indicate a perception that older generations have the greater responsibility for climate change. In this paper, we examine how a portion of the cost of an event can be attributed to any individual person, according to their age and nationality. We demonstrate that this is quantitatively feasible using the example of the 2018 summer heatwave in eastern China and its impact on aquaculture. A relatively simple technique finds sample individuals responsible for between 0.53 and 18.10 yuan, increasing with their age and their country’s emissions over their adult lifetime since the first international consensus on carbon emissions was reached. This provides an illustration of the scale of such responsibilities, and how it is affected by national development and demographics. Such data can support decisions, at national and international levels, on how to fund recovery from climate impacts. It offers a simple quantitative approach for individuals to know their impact on the climate, or for governments to use in making policy decisions about how best to distribute costs of climate change. </strong></p>

    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/ Edinburgh Research E...arrow_drop_down
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    Environmental Research Letters
    Article . 2021
    Data sources: DOAJ
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    Environmental Research Letters
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    https://doi.org/10.5194/egusph...
    Other literature type . 2022
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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/ Edinburgh Research E...arrow_drop_down
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      Environmental Research Letters
      Article . 2021
      Data sources: DOAJ
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      Environmental Research Letters
      Article . 2021 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      https://doi.org/10.5194/egusph...
      Other literature type . 2022
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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: Tamsin L. Edwards; Sophie Nowicki; Ben Marzeion; Regine Hock; +80 Authors

    The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2–8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained. International audience

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    DI-fusion
    Article . 2021 . Peer-reviewed
    Data sources: DI-fusion
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    St Andrews Research Repository
    Article . 2021 . Peer-reviewed
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    Nature
    Article
    Data sources: UnpayWall
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    Nature
    Article . 2021
    Data sources: NARCIS
    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
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    OceanRep; Nature
    Other literature type . Article . 2021 . Peer-reviewed
    License: Springer Nature TDM
    Nature
    Article . 2019
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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/
      DI-fusion
      Article . 2021 . Peer-reviewed
      Data sources: DI-fusion
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      St Andrews Research Repository
      Article . 2021 . Peer-reviewed
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      Nature
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      Nature
      Article . 2021
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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
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      OceanRep; Nature
      Other literature type . Article . 2021 . Peer-reviewed
      License: Springer Nature TDM
      Nature
      Article . 2019
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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: Sjoukje Philip; Sarah F. Kew; Geert Jan van Oldenborgh; Friederike E. L. Otto; +7 Authors

    Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service. International audience

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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/
    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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    DOAJ
    Article . 2020
    Data sources: DOAJ
    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/
    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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    Authors: H. Seroussi; S. Nowicki; A. J. Payne; H. Goelzer; +50 Authors

    Abstract. Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution inresponse to different climate scenarios and assess the mass loss that would contribute tofuture sea level rise. However, there is currently no consensus on estimates of the future massbalance of the ice sheet, primarily because of differences in the representation of physicalprocesses, forcings employed and initial states of ice sheet models. This study presentsresults from ice flow model simulations from 13 international groups focusing on the evolutionof the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet ModelIntercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from theCoupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climatemodel results. Simulations of the Antarctic ice sheet contribution to sea level rise in responseto increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent(SLE) under Representative ConcentrationPathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment withconstant climate conditions and should therefore be added to the mass loss contribution underclimate conditions similar to present-day conditions over the same period. The simulated evolution of theWest Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighingthe increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelfcollapse, here assumed to be caused by large amounts of liquid water ponding at the surface ofice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without iceshelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, thecalibration of these melt rates based on oceanic conditions taken outside of ice shelf cavitiesand the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario basedon two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared tosimulations done under present-day conditions for the two CMIP5 forcings used and displaylimited mass gain in East Antarctica. info:eu-repo/semantics/published

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    OceanRep
    Article . 2020 . Peer-reviewed
    Data sources: OceanRep
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    The Cryosphere (TC)
    Article . 2020
    Data sources: JAIRO
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    MPG.PuRe
    Article . 2020
    Data sources: MPG.PuRe
    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/
    DOAJ
    Article . 2020
    Data sources: DOAJ
    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/
    DI-fusion
    Article . 2020 . Peer-reviewed
    Data sources: DI-fusion
    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/
    MPG.PuRe
    Article . 2020
    License: CC BY
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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/ The Cryosphere; Vrij...arrow_drop_down
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      OceanRep
      Article . 2020 . Peer-reviewed
      Data sources: OceanRep
      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/
      The Cryosphere (TC)
      Article . 2020
      Data sources: JAIRO
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      MPG.PuRe
      Article . 2020
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      DOAJ
      Article . 2020
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      DI-fusion
      Article . 2020 . Peer-reviewed
      Data sources: DI-fusion
      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/
      MPG.PuRe
      Article . 2020
      License: CC BY
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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: Greve, Ralf; Calov, Reinhard; Obase, Takashi; Saito, Fuyuki; +2 Authors

    The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) brings together a consortium of international ice-sheet and climate modellers to simulate the contribution from the Greenland and Antarctic ice sheets to future sea-level rise. In this document, we describe the set-up and main results of the ISMIP6 Antarctica Tier-1 and Tier-2 experiments carried out with the ice-sheet model SICOPOLIS. The companion document for the Greenland ice sheet is available at https://doi.org/10.5281/zenodo.3971251. V1.0.1: References updated; some minor corrections. V1: Full report. V0.1: Abstract only. Funding acknowledgements: Japan Society for the Promotion of Science (JSPS) KAKENHI grant Nos. JP16H02224, JP17H06104 and JP17H06323. PalMod project (PalMod 1.1 and 1.3 with grants 01LP1502C and 01LP1504D) of the German Federal Ministry of Education and Research (BMBF).

    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
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    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
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      ZENODO
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      ZENODO
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      ZENODO
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    Authors: Ali Zare; Timothy A. Bodisco; Puneet Verma; Mohammad Jafari; +7 Authors

    This study investigates the effect of engine temperature during cold start and hot start engine operation on particulate matter emissions and engine performance parameters. In addition to a fundamental study on cold start operation and the effect of lubricating oil during combustion, this research introduces important knowledge about regulated particulate number emissions and particulate size distribution during cold start, which is an emerging area in the literature. A further aspect of this work is to introduce waste lubricating oil as a fuel. By using diesel and two blends of diesel with 1 and 5% waste lubricating oil in a 6-cylinder turbocharged engine on a cold start custom test, this investigation studied particle number (PN), friction losses and combustion instability with diesel and waste lubricating oil fuel blends. In order to understand and explain the results the following were also studied: particle size distribution and median diameter, engine oil, coolant and exhaust gas temperatures, start of injection, friction mean effective pressure (FMEP), mechanical efficiency, coefficient of variation (CoV) of engine speed, CoV of indicated mean effective pressure (IMEP) and maximum rate of pressure rise were also studied. The results showed that during cold start the increase in engine temperature was associated with an increase in PN and size of particles, and a decrease in FMEP and maximum rate of pressure rise. Compared to a warmed up engine, during cold start, PN, start of injection and mechanical efficiency were lower; while FMEP, CoV of IMEP and maximum rate of pressure rise were higher. Adding 5% waste lubricating oil to the fuel was associated with a decrease in PN (during cold start), decreased particle size, maximum rate of pressure rise and CoV of IMEP and was associated with an increase in PN and nucleation mode particles (during hot start) and FMEP.

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    Energy Conversion and Management
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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
    Energy Conversion and Management
    Article . 2020 . Peer-reviewed
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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/ CORE (RIOXX-UK Aggre...arrow_drop_down
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      Energy Conversion and Management
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      Energy Conversion and Management
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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: Galparsoro, Ibon; Murillas, Arantza; Pinarbasi, Kemal; Sequeira, Ana M. M.; +20 Authors

    AbstractMarine aquaculture is the most promising industry for ensuring future provision of seafood. Yet, the worldwide growth and expansion of this industry have been slower than expected, calling for the identification of environmentally suitable sites while accounting for all factors that could constrain or benefit its establishment. Here, we determine the main obstacles and risks hindering the growth and expansion of marine aquaculture, as well as the needs and recommendations to overcome such constraints. Our analysis is based on results obtained from a consultation process held in 16 study sites located around the world with the participation of 614 stakeholders representing the research community, aquaculture industry, government, conservation groups, and education and fishermen associations. A high level of commonality exists in the main issues hindering aquaculture growth and expansion in coastal, off‐the‐coast and offshore aquaculture with most being attributed to interactions with other maritime activities, including conflicts with other users and administrative procedures, including licensing. Critical needs for improved management and expansion of the aquaculture industry are related to planning and management of developments and technological advances, with economic and market needs featuring to a lesser extent. Key procedures recommended to assist further aquaculture growth are the standardisation and simplification of regulatory frameworks, improvement of governance, and the adoption of participatory processes to facilitate meaningful and productive stakeholder engagement. We strongly recommend stakeholder participation to enhance insights on the full environmental and human dimensions of marine management and for implementation of ecosystem‐based marine spatial planning.

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    Reviews in Aquaculture
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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: Dongyao Jia; Haibo Chen; Zuduo Zheng; David Watling; +3 Authors

    The predictive cruise control (PCC) is a promising method to optimize energy consumption of vehicles, especially the heavy-duty vehicles (HDV). Due to the limited sensing range and computational capabilities available on-board, the conventional PCC system can only obtain a sub-optimal speed trajectory based on a shorter prediction horizon. The recently emerging information and communication technologies such as vehicular communication, cloud computing, and Internet of Things provide huge potentials to improve the traditional PCC system. In this paper, we propose a general framework for the enhanced cloud-based PCC system which integrates a data-driven traffic predictive model and the instantaneous control algorithms. Specifically, we introduce a novel multi-view CNN deep learning algorithm to predict traffic situation based on the historical and real-time traffic data collected from fields, and the time-varying adaptive model predictive control (MPC) to calculate the instantaneous optimal speed profile with the aim of minimizing energy consumption. We verified our approach via simulations in which the impact of various traffic condition on the PCC-enabled HDV has been fully evaluated.

    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/ IEEE Transactions on...arrow_drop_down
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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
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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/ IEEE Transactions on...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/
      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
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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: Vasilaki, V; Pijuan, M; Duan, H; Katsou, E;

    Chapter six of the Open Access book, 'Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems', published by IWA Publishing, is available online at https://iwaponline.com/ebooks/book/844/Quantification-and-Modelling-of-Fugitive . Copyright © 2022 The Authors and Editors. This chapter reviews the studies from N2 O and CH4 monitoring campaigns in full-scale wastewater treatment plants (WWTPs) and sewer networks. The focus is on greenhouse gas (GHG) emissions from WWTPs as more literature is available. The analysis classifies quantified N2 O and CH4 emission factors (EFs), triggering operational conditions and formation pathways for different configurations. Control strategies to minimize N2 O emissions are proposed for different process groups. The main reasons for EF discrepancies are discussed. Overall, N2 O emission factors for processes treating lowstrength wastewater streams range between 0.003 and 5.6% of the N-load (average equal to 0.9% of the N-load). Emissions higher than mainstream process average emissions have been reported in sequencing batch reactors (average equal to 3.6% of the influent N-load) and step-fed plug flow reactors. In full-scale sidestream processes, less than 15 monitoring campaigns have reported EFs (average equal to 2.5% of the N-load). Differences in the EFs among the process groups are partially attributed to disparities in the control strategies (i.e. aeration control), configuration, and operational and environmental conditions that favour the preferred enzymatic pathways. Overall, triggering operational conditions for elevated N2 O emissions in full-scale wastewater treatment processes include (i) increased NH4+ concentrations leading to a high ammonia oxidation rate (AOR) and increased production of intermediates (e.g. NH2 OH, NO−, etc.), (ii) improper aeration control (i.e. inadequate aeration and non-aeration duration, over-aeration, under-aeration), (iii) NO2− accumulation triggering the nitrifier denitrification pathway, and (iv) sudden shifts in incomplete heterotrophic denitrification (i.e. due to excess dissolved oxygen (DO), chemical oxygen demand (COD) limitation etc.). The N2 O monitoring strategies can also influence the reliability of the quantified EFs. Due to temporal variation of N2 O emissions, short-term studies are not sufficient to quantify annual EFs. The analysis showed that the average EF for processes treating low-strength streams monitored for less than a week is 0.66% of the influent N-load. On the other hand, processes monitored over 6 months have an average EF equal to 1.74%. Compared with N2 O, CH4 quantification from full-scale WWTPs is less investigated, while it also contributes significantly to the overall plant carbon footprint. The results of full-scale CH4 quantification studies are summarized in this chapter. Emissions of CH4 in WWTPs mainly originate from the influent, anaerobic wastewater treatment and anaerobic sludge handling processes. The amount of CH4 emissions varies greatly with different configurations of WWTPs. For WWTPs without anaerobic sludge handling processes, the CH4 emissions can mainly be traced back to the CH4 dissolved in the influent. When anaerobic treatment is applied in WWTPs for wastewater COD removal, its CH4 emissions might substantially increase the overall plant carbon footprint. GHG monitoring campaigns carried out in WWTPs should include the monitoring of fugitive CH4 emissions. Finally, CH4 and N2 O emissions reported from sewer networks are also summarized in this chapter. The last part of the chapter summarizes some mitigation strategies applied at full-scale to control fugitive CHG emissions from WWTPs and sewers. Maite Pijuan acknowledges the support from the Economy and Knowledge Department of the Catalan Government through a Consolidated Research Group (ICRA-TECH – 2017 SGR 1318) – Catalan Institute for Water Research and the Spanish Government through the Salvador de Madariaga mobility program (PRX19/00051). Vasileia Vasilaki and Evina Katsou would like to acknowledge the Horizon 2020 research and innovation program, SMART-Plant under grant agreement No 690323. Haoran Duan acknowledges the support of the Australian Research Council (ARC) through project DP180103369.

    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/ Brunel University Re...arrow_drop_down
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    Brunel University Research Archive
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      Brunel University Research Archive
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    Authors: Vasileia Vasilaki; Maite Pijuan; Haoran Duan; Evina Katsou;
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    https://doi.org/10.2166/978178...
    Part of book or chapter of book . 2022 . Peer-reviewed
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      https://doi.org/10.2166/978178...
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    Authors: Fraser Lott; Andrew Ciavarella; John Kennedy; Andrew King; +3 Authors

    <p><strong>Probabilistic event attribution aims to quantify the role of anthropogenic climate change in altering the intensity or probability of extreme climate and weather events. It was originally conceived to calculate the costs associated with any increased likelihood of the meteorological event in question. However, only recently have such studies attempted to divide liability between polluting nations and ascribe a cost. Recent protests indicate a perception that older generations have the greater responsibility for climate change. In this paper, we examine how a portion of the cost of an event can be attributed to any individual person, according to their age and nationality. We demonstrate that this is quantitatively feasible using the example of the 2018 summer heatwave in eastern China and its impact on aquaculture. A relatively simple technique finds sample individuals responsible for between 0.53 and 18.10 yuan, increasing with their age and their country’s emissions over their adult lifetime since the first international consensus on carbon emissions was reached. This provides an illustration of the scale of such responsibilities, and how it is affected by national development and demographics. Such data can support decisions, at national and international levels, on how to fund recovery from climate impacts. It offers a simple quantitative approach for individuals to know their impact on the climate, or for governments to use in making policy decisions about how best to distribute costs of climate change. </strong></p>

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    Environmental Research Letters
    Article . 2021
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    Environmental Research Letters
    Article . 2021 . Peer-reviewed
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      Environmental Research Letters
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    Authors: Tamsin L. Edwards; Sophie Nowicki; Ben Marzeion; Regine Hock; +80 Authors

    The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2–8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained. International audience

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    DI-fusion
    Article . 2021 . Peer-reviewed
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    Nature
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    Other literature type . Article . 2021 . Peer-reviewed
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    Article . 2019
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    Authors: Sjoukje Philip; Sarah F. Kew; Geert Jan van Oldenborgh; Friederike E. L. Otto; +7 Authors

    Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service. International audience

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    DOAJ
    Article . 2020
    Data sources: DOAJ
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    Authors: H. Seroussi; S. Nowicki; A. J. Payne; H. Goelzer; +50 Authors

    Abstract. Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution inresponse to different climate scenarios and assess the mass loss that would contribute tofuture sea level rise. However, there is currently no consensus on estimates of the future massbalance of the ice sheet, primarily because of differences in the representation of physicalprocesses, forcings employed and initial states of ice sheet models. This study presentsresults from ice flow model simulations from 13 international groups focusing on the evolutionof the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet ModelIntercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from theCoupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climatemodel results. Simulations of the Antarctic ice sheet contribution to sea level rise in responseto increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent(SLE) under Representative ConcentrationPathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment withconstant climate conditions and should therefore be added to the mass loss contribution underclimate conditions similar to present-day conditions over the same period. The simulated evolution of theWest Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighingthe increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelfcollapse, here assumed to be caused by large amounts of liquid water ponding at the surface ofice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without iceshelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, thecalibration of these melt rates based on oceanic conditions taken outside of ice shelf cavitiesand the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario basedon two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared tosimulations done under present-day conditions for the two CMIP5 forcings used and displaylimited mass gain in East Antarctica. info:eu-repo/semantics/published

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    OceanRep
    Article . 2020 . Peer-reviewed
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    The Cryosphere (TC)
    Article . 2020
    Data sources: JAIRO
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    MPG.PuRe
    Article . 2020
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    DOAJ
    Article . 2020
    Data sources: DOAJ
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    DI-fusion
    Article . 2020 . Peer-reviewed
    Data sources: DI-fusion
    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/
    MPG.PuRe
    Article . 2020
    License: CC BY
    Data sources: MPG.PuRe
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      OceanRep
      Article . 2020 . Peer-reviewed
      Data sources: OceanRep
      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/
      The Cryosphere (TC)
      Article . 2020
      Data sources: JAIRO
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      MPG.PuRe
      Article . 2020
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      DOAJ
      Article . 2020
      Data sources: DOAJ
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      DI-fusion
      Article . 2020 . Peer-reviewed
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      MPG.PuRe
      Article . 2020
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    Authors: Greve, Ralf; Calov, Reinhard; Obase, Takashi; Saito, Fuyuki; +2 Authors

    The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) brings together a consortium of international ice-sheet and climate modellers to simulate the contribution from the Greenland and Antarctic ice sheets to future sea-level rise. In this document, we describe the set-up and main results of the ISMIP6 Antarctica Tier-1 and Tier-2 experiments carried out with the ice-sheet model SICOPOLIS. The companion document for the Greenland ice sheet is available at https://doi.org/10.5281/zenodo.3971251. V1.0.1: References updated; some minor corrections. V1: Full report. V0.1: Abstract only. Funding acknowledgements: Japan Society for the Promotion of Science (JSPS) KAKENHI grant Nos. JP16H02224, JP17H06104 and JP17H06323. PalMod project (PalMod 1.1 and 1.3 with grants 01LP1502C and 01LP1504D) of the German Federal Ministry of Education and Research (BMBF).

    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
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    ZENODO
    Report . 2020
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Report . 2020
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    ZENODO
    Report . 2020
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Report . 2020
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Report . 2020
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    Authors: Ali Zare; Timothy A. Bodisco; Puneet Verma; Mohammad Jafari; +7 Authors

    This study investigates the effect of engine temperature during cold start and hot start engine operation on particulate matter emissions and engine performance parameters. In addition to a fundamental study on cold start operation and the effect of lubricating oil during combustion, this research introduces important knowledge about regulated particulate number emissions and particulate size distribution during cold start, which is an emerging area in the literature. A further aspect of this work is to introduce waste lubricating oil as a fuel. By using diesel and two blends of diesel with 1 and 5% waste lubricating oil in a 6-cylinder turbocharged engine on a cold start custom test, this investigation studied particle number (PN), friction losses and combustion instability with diesel and waste lubricating oil fuel blends. In order to understand and explain the results the following were also studied: particle size distribution and median diameter, engine oil, coolant and exhaust gas temperatures, start of injection, friction mean effective pressure (FMEP), mechanical efficiency, coefficient of variation (CoV) of engine speed, CoV of indicated mean effective pressure (IMEP) and maximum rate of pressure rise were also studied. The results showed that during cold start the increase in engine temperature was associated with an increase in PN and size of particles, and a decrease in FMEP and maximum rate of pressure rise. Compared to a warmed up engine, during cold start, PN, start of injection and mechanical efficiency were lower; while FMEP, CoV of IMEP and maximum rate of pressure rise were higher. Adding 5% waste lubricating oil to the fuel was associated with a decrease in PN (during cold start), decreased particle size, maximum rate of pressure rise and CoV of IMEP and was associated with an increase in PN and nucleation mode particles (during hot start) and FMEP.

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    Energy Conversion and Management
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    Energy Conversion and Management
    Article . 2020 . Peer-reviewed
    License: Elsevier TDM
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      Energy Conversion and Management
      Article . 2020 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Crossref
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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: Galparsoro, Ibon; Murillas, Arantza; Pinarbasi, Kemal; Sequeira, Ana M. M.; +20 Authors

    AbstractMarine aquaculture is the most promising industry for ensuring future provision of seafood. Yet, the worldwide growth and expansion of this industry have been slower than expected, calling for the identification of environmentally suitable sites while accounting for all factors that could constrain or benefit its establishment. Here, we determine the main obstacles and risks hindering the growth and expansion of marine aquaculture, as well as the needs and recommendations to overcome such constraints. Our analysis is based on results obtained from a consultation process held in 16 study sites located around the world with the participation of 614 stakeholders representing the research community, aquaculture industry, government, conservation groups, and education and fishermen associations. A high level of commonality exists in the main issues hindering aquaculture growth and expansion in coastal, off‐the‐coast and offshore aquaculture with most being attributed to interactions with other maritime activities, including conflicts with other users and administrative procedures, including licensing. Critical needs for improved management and expansion of the aquaculture industry are related to planning and management of developments and technological advances, with economic and market needs featuring to a lesser extent. Key procedures recommended to assist further aquaculture growth are the standardisation and simplification of regulatory frameworks, improvement of governance, and the adoption of participatory processes to facilitate meaningful and productive stakeholder engagement. We strongly recommend stakeholder participation to enhance insights on the full environmental and human dimensions of marine management and for implementation of ecosystem‐based marine spatial planning.

    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/ Reviews in Aquacultu...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/
    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/
    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/
    Reviews in Aquaculture
    Article
    License: CC BY ND SA
    Data sources: UnpayWall
    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
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