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  • SDSN - Greece
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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: H. Goelzer; H. Goelzer; H. Goelzer; S. Nowicki; +49 Authors

    Abstract. The Greenland ice sheet is one of the largest contributors to global meansea-level rise today and is expected to continue to lose mass as the Arcticcontinues to warm. The two predominant mass loss mechanisms are increasedsurface meltwater run-off and mass loss associated with the retreat ofmarine-terminating outlet glaciers. In this paper we use a large ensemble ofGreenland ice sheet models forced by output from a representative subset ofthe Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level risecontributions over the 21st century. The simulations are part of theIce Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We estimate thesea-level contribution together with uncertainties due to future climateforcing, ice sheet model formulations and ocean forcing for the twogreenhouse gas concentration scenarios RCP8.5 and RCP2.6. The resultsindicate that the Greenland ice sheet will continue to lose mass in bothscenarios until 2100, with contributions of 90±50 and 32±17 mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largestmass loss is expected from the south-west of Greenland, which is governed bysurface mass balance changes, continuing what is already observed today.Because the contributions are calculated against an unforced controlexperiment, these numbers do not include any committed mass loss, i.e. massloss that would occur over the coming century if the climate forcingremained constant. Under RCP8.5 forcing, ice sheet model uncertaintyexplains an ensemble spread of 40 mm, while climate model uncertainty andocean forcing uncertainty account for a spread of 36 and 19 mm,respectively. Apart from those formally derived uncertainty ranges, thelargest gap in our knowledge is about the physical understanding andimplementation of the calving process, i.e. the interaction of the ice sheetwith the ocean. info:eu-repo/semantics/published

    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
    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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    Article . 2020
    License: CC BY
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    The Cryosphere (TC)
    Other literature type . Article . 2020 . Peer-reviewed
    License: CC BY
    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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    St Andrews Research Repository
    Article . 2020 . Peer-reviewed
    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
    Article . 2020
    Data sources: NARCIS
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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/
    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
    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/10.5194/tc-201...
    Preprint . 2020
    License: CC BY
    Data sources: Crossref
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    https://epic.awi.de/id/eprint/...
    Other literature type
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    Data sources: UnpayWall
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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; The Cryosphere (TC)
    Article . Preprint . 2020
    License: CC BY
    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/
    Hal-Diderot
    Article . 2020
    Data sources: Hal-Diderot
    https://doi.org/10.5194/egusph...
    Other literature type . 2020
    Data sources: Crossref
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      Article . 2020
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      The Cryosphere (TC)
      Other literature type . Article . 2020 . Peer-reviewed
      License: CC BY
      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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      St Andrews Research Repository
      Article . 2020 . Peer-reviewed
      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
      Article . 2020
      Data sources: NARCIS
      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/
      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
      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/10.5194/tc-201...
      Preprint . 2020
      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/
      https://epic.awi.de/id/eprint/...
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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/
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      The Cryosphere; The Cryosphere (TC)
      Article . Preprint . 2020
      License: CC BY
      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/
      Hal-Diderot
      Article . 2020
      Data sources: Hal-Diderot
      https://doi.org/10.5194/egusph...
      Other literature type . 2020
      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: J. A. Franke; J. A. Franke; C. Müller; J. Elliott; +33 Authors

    Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.

    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/ Geoscientific Model ...arrow_drop_down
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    Authors: Diana E. Bowler; Anne D. Bjorkman; Maria Dornelas; Isla H. Myers-Smith; +17 Authors

    AbstractClimate change and other anthropogenic drivers of biodiversity change are unequally distributed across the world. The geographic patterns of different drivers, and the spatial overlap among these drivers, have important implications for the direction and pace of biodiversity change, yet are not well documented. Moreover, it is unknown if the geographic patterns of drivers differ between the terrestrial and marine realm, as expected due to marked differences in how humans interact with the land and ocean.We compiled global gridded datasets on climate change, land-use, resource exploitation, pollution, species invasions, and human population density. We used multivariate statistics to examine the spatial relationships among the datasets and to characterize the typical combinations of drivers experienced by different parts of the world.We found stronger positive correlations among drivers in the terrestrial than in the marine realm, leading to areas of high intensities of multiple drivers on land. Climate change tended to be negatively correlated with other drivers in the terrestrial realm (e.g., in the tundra and boreal forest with high climate change but low human use and pollution) whereas the opposite was true in the marine realm (e.g., in the Indo-Pacific with high climate change and high fishing).We show that different regions of the world can be defined by anthropogenic threat complexes (ATCs), distinguished by different sets of drivers with varying intensities. The ATCs can be used to test hypothesis about the pattern of biodiversity change, especially the joint effects of multiple drivers. More generally, our global analysis highlights the broad conservation priorities needed to mitigate the effects of anthropogenic change on biodiversity responses, with different priorities emerging on land and in the ocean, and in different parts of the world.

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    bioRxiv
    Preprint . 2018
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      bioRxiv
      Preprint . 2018
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      https://www.biorxiv.org/conten...
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    Authors: Gytis Dudas; Luiz Max Carvalho; Trevor Bedford; Andrew J. Tatem; +92 Authors

    The 2013-2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic 'gravity' model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics. ispartof: Nature vol:544 issue:7650 pages:309- ispartof: location:England status: published

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    e-Prints Soton
    Article . 2017 . Peer-reviewed
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    Europe PubMed Central
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    Lirias
    Article . 2017
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    Nature
    Article
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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/
    Apollo
    Other literature type . 2017
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    Nature
    Other literature type . Article . 2017 . Peer-reviewed
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    Nature
    Article . 2017
    Data sources: NARCIS
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    Apollo
    Article . 2018
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      e-Prints Soton
      Article . 2017 . Peer-reviewed
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      Europe PubMed Central
      Other literature type . 2017
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      Lirias
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      Nature
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      Apollo
      Other literature type . 2017
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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
      Nature
      Other literature type . Article . 2017 . Peer-reviewed
      License: Springer TDM
      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
      Nature
      Article . 2017
      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
      Apollo
      Article . 2018
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    Authors: J. Kaiser; Glenn M. Wolfe; Birger Bohn; Sebastian Broch; +18 Authors

    Ozone concentrations in the Po Valley of northern Italy often exceed international regulations. As both a source of radicals and an intermediate in the oxidation of most volatile organic compounds (VOCs), formaldehyde (HCHO) is a useful tracer for the oxidative processing of hydrocarbons that leads to ozone production. We investigate the sources of HCHO in the Po Valley using vertical profile measurements acquired from the airship Zeppelin NT over an agricultural region during the PEGASOS 2012 campaign. Using a 1-D model, the total VOC oxidation rate is examined and discussed in the context of formaldehyde and ozone production in the early morning. While model and measurement discrepancies in OH reactivity are small (on average 3.4 ± 13%), HCHO concentrations are underestimated by as much as 1.5 ppb (45%) in the convective mixed layer. A similar underestimate in HCHO was seen in the 2002–2003 FORMAT Po Valley measurements, though the additional source of HCHO was not identified. Oxidation of unmeasured VOC precursors cannot explain the missing HCHO source, as measured OH reactivity is explained by measured VOCs and their calculated oxidation products. We conclude that local direct emissions from agricultural land are the most likely source of missing HCHO. Model calculations demonstrate that radicals from degradation of this non-photochemical HCHO source increase model ozone production rates by as much as 0.6 ppb h−1 (12%) before noon. Atmospheric Chemistry and Physics, 15 (3) ISSN:1680-7375 ISSN:1680-7367

    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/ NARCIS; Research@WURarrow_drop_down
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    NARCIS; Research@WUR
    Other literature type . Article . 2015
    License: CC BY
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    Research Collection
    Article . 2015
    License: CC BY
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref; NARCIS
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    Atmospheric Chemistry and Physics (ACP)
    Article
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    ETH Zürich Research Collection
    Article . 2015
    License: CC BY
    Data sources: Datacite
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      Other literature type . Article . 2015
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      Research Collection
      Article . 2015
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2015 . Peer-reviewed
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      Atmospheric Chemistry and Physics (ACP)
      Article
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      ETH Zürich Research Collection
      Article . 2015
      License: CC BY
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    Authors: Graham Mann; Kenneth S. Carslaw; Carly Reddington; Kirsty J. Pringle; +48 Authors

    Abstract. Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by twelve global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean dataset simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

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    https://www.atmos-chem-phys.ne...
    Preprint
    License: CC BY
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    MPG.PuRe
    Article . 2014
    License: CC BY
    Data sources: MPG.PuRe
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    http://www.atmos-chem-phys-dis...
    Article . 2013 . Peer-reviewed
    Data sources: SNSF P3 Database
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      https://www.atmos-chem-phys.ne...
      Preprint
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      MPG.PuRe
      Article . 2014
      License: CC BY
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      http://www.atmos-chem-phys-dis...
      Article . 2013 . Peer-reviewed
      Data sources: SNSF P3 Database
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    Authors: Frank E. Muller-Karger; Patricia Miloslavich; Patricia Miloslavich; Nicholas J. Bax; +39 Authors

    Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary Materials for a glossary of acronyms). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world's biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing biodiversity and understanding its drivers will require incorporation of observations from traditional and molecular taxonomy, animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory initiatives including the deep ocean and seafloor. The partnership between large-scale ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS) is an expedited, effective way to support international policy-level assessments (e.g., the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES), along with the implementation of international development goals (e.g., the United Nations Sustainable Development Goals).

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    Frontiers in Marine Science
    Other literature type . Article . 2018 . Peer-reviewed
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    Frontiers in Marine Science
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    Horizon / Pleins textes
    Other literature type . 2018
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      Frontiers in Marine Science
      Other literature type . Article . 2018 . Peer-reviewed
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      Frontiers in Marine Science
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      Horizon / Pleins textes
      Other literature type . 2018
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    Authors: Jean-Pierre Gattuso; Jean-Pierre Gattuso; Jean-Pierre Gattuso; Alexandre K. Magnan; +21 Authors

    International audience; The Paris Agreement target of limiting global surface warming to 1.5–2∘C compared to pre-industrial levels by 2100 will still heavily impact the ocean. While ambitious mitigation and adaptation are both needed, the ocean provides major opportunities for action to reduce climate change globally and its impacts on vital ecosystems and ecosystem services. A comprehensive and systematic assessment of 13 global- and local-scale, ocean-based measures was performed to help steer the development and implementation of technologies and actions toward a sustainable outcome. We show that (1) all measures have tradeoffs and multiple criteria must be used for a comprehensive assessment of their potential, (2) greatest benefit is derived by combining global and local solutions, some of which could be implemented or scaled-up immediately, (3) some measures are too uncertain to be recommended yet, (4) political consistency must be achieved through effective cross-scale governance mechanisms, (5) scientific effort must focus on effectiveness, co-benefits, disbenefits, and costs of poorly tested as well as new and emerging measures.

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    Frontiers in Marine Science
    Other literature type . Article . 2018 . Peer-reviewed
    License: CC BY
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    OceanRep
    Article . 2018 . Peer-reviewed
    Data sources: OceanRep
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    NARCIS
    Article . 2018
    Data sources: NARCIS
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    Frontiers in Marine Science
    Article . 2018
    Data sources: NARCIS
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    Frontiers in Marine Science
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      Frontiers in Marine Science
      Other literature type . Article . 2018 . Peer-reviewed
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      OceanRep
      Article . 2018 . Peer-reviewed
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      Article . 2018
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      Frontiers in Marine Science
      Article . 2018
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      Frontiers in Marine Science
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    Authors: Katrianne Lehtipalo; Linda Rondo; Jenni Kontkanen; Siegfried Schobesberger; +65 Authors

    The growth of freshly formed aerosol particles can be the bottleneck in their survival to cloud condensation nuclei. It is therefore crucial to understand how particles grow in the atmosphere. Insufficient experimental data has impeded a profound understanding of nano-particle growth under atmospheric conditions. Here we study nano-particle growth in the CLOUD (Cosmics Leaving OUtdoors Droplets) chamber, starting from the formation of molecular clusters. We present measured growth rates at sub-3 nm sizes with different atmospherically relevant concentrations of sulphuric acid, water, ammonia and dimethylamine. We find that atmospheric ions and small acid-base clusters, which are not generally accounted for in the measurement of sulphuric acid vapour, can participate in the growth process, leading to enhanced growth rates. The availability of compounds capable of stabilizing sulphuric acid clusters governs the magnitude of these effects and thus the exact growth mechanism. We bring these observations into a coherent framework and discuss their significance in the atmosphere. The growth rates of freshly formed aerosol particles influence what fraction of these can reach sizes large enough to affect cloud formation and climate. Here, the authors show that the nano-particle growth in a sulphuric acid containing system can be enhanced by the presence of ions or small acid-base clusters.

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    Europe PubMed Central
    Article . 2016
    Data sources: PubMed Central
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    Caltech Authors
    Article . 2016 . Peer-reviewed
    Data sources: Caltech Authors
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    Nature Communications
    Article . 2016
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