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  • SDSN - Greece
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  • Fundação para a Ciência e a Tecnologia, I.P.
  • UK Research and Innovation

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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: Santos, Susana; Eekhout, Iris; Voerman, Ellis; Gaillard, Romy; +76 Authors

    Figure S1. Flow chart of participating cohorts and individuals. Table S1. Cohort-specific methods of data collection for maternal anthropometrics and gestational age. Table S2. Box-Cox t model specifications for each maternal pre-pregnancy body mass index group. Table S3. Gestational weight measurements per participating cohort and maternal pre-pregnancy body mass index group. Figure S2. Sample size according to gestational age for each maternal pre-pregnancy body mass index group. Figure S3. Predicted z scores for the average weight gain according to gestational age for each maternal pre-pregnancy body mass index group. Table S4. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy underweight. Table S5. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy normal weight. Table S6. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy overweight. Table S7. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 1. Table S8. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 2. Table S9. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 3. Table S10. Local institutional ethical review boards per cohort. (DOCX 631 kb)

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    Other literature type . 2018
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    Authors: Yves-Marie Saint-Drenan; Romain Besseau; Malte Jansen; Iain Staffell; +6 Authors

    A wind turbine's power curve relates its power production to the wind speed it experiences. The typical shape of a power curve is well known and has been studied extensively; however, the power curves of individual turbine models can vary widely from one another. This is due to both the technical features of the turbine (power density, cut-in and cut-out speeds, limits on rotational speed and aerodynamic efficiency), and environmental factors (turbulence intensity, air density, wind shear and wind veer). Data on individual power curves are often proprietary and only available through commercial databases. We therefore develop an open-source model which can generate the power curve of any turbine, adapted to the specific conditions of any site. This can employ one of six parametric models advanced in the literature, and accounts for the eleven variables mentioned above. The model is described, the impact of each technical and environmental feature is examined, and it is then validated against the manufacturer power curves of 91 turbine models. Versions of the model are made available in MATLAB, R and Python code for the community. preprint submitted to Renewable Energy

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    Renewable Energy
    Article . 2020 . Peer-reviewed
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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
      Renewable Energy
      Article . 2020 . Peer-reviewed
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      Article . 2020
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      Article . 2019
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    Authors: Carla S. Santos; Bruna Carbas; Ana Castanho; Marta W. Vasconcelos; +3 Authors

    Pea is one of the most produced and consumed pulse crops around the world. The study of genetic variability within pea germplasm is an important tool to identify outstanding accessions with optimal functional and nutritional qualities. In the present study, a collection of 105 pea accessions was analysed for physicochemical properties, pasting viscosity, and basic composition parameters. While pasting viscosities were negatively correlated to hydration capacity, cooking time, and basic composition, a positive correlation was found between the hydration capacity and the basic composition parameters. Basic composition (protein, fibre, fat, and resistant starch) parameters were further evaluated regarding seed trait morphology, namely, seed shape, colour, and surface. Allelic characterisation at the r and rb genetic loci was performed in a subgroup of 32 accessions (3 phenotyped as smooth and 29 as rough seeded), revealing that none of the initially classified rough-seeded accessions were rb mutants, 19 were r mutants, and 13 were neither r nor rb. Despite their initial phenotypic classification, the 13 accessions genetically classified as smooth behaved differently (p < 0.05) to the 19 r mutants in terms of physicochemical properties, pasting viscosity, and basic composition parameters. Using multivariate analysis of the most discriminatory parameters for the food-related traits studied, the best-performing accessions at functional and nutritional levels were identified for future plant breeding to improve field pea production and consumption.

    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/ Foods; LAReferencia ...arrow_drop_down
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    Europe PubMed Central
    Article . 2019
    Data sources: PubMed Central
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    Foods
    Article . 2019
    Data sources: Ciência-UCP
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    Foods
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    ZENODO
    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/ Foods; LAReferencia ...arrow_drop_down
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      Europe PubMed Central
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      Foods
      Article . 2019
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    Authors: Cynthia H. Whaley; Rashed Mahmood; Knut von Salzen; Barbara Winter; +52 Authors

    While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models. Assessments from the Russian ship-based campaign were performed with the support of RFBR project no. 20-55-12001 and according to the development program of the Interdisciplinary Scientific and Educational School of M.V. Lomonosov Moscow State University “Future Planet and Global Environmental Change”. Development of the methodology for aethalometric data treatment was supported by RSF project no. 19-77-30004. The BC observations on R/V Mirai were supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (Arctic Challenge for Sustainability (ArCS) project). Contributions by SMHI were funded by the Swedish Environmental Protection Agency under contract NV-03174-20 and the Swedish Climate and Clean Air Research program (SCAC) as well as partly by the Swedish National Space Board (NORD-SLCP, grant agreement ID: 94/16) and the EU Horizon 2020 project Integrated Arctic Observing System (INTAROS, grant agreement ID: 727890). Work on ACE-FTS analysis was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Julia Schmale received funding from the Swiss National Science Foundation (project no. 200021_188478). Duncan Watson-Parris received funding from NERC projects NE/P013406/1 (A-CURE) and NE/S005390/1 (ACRUISE) as well as funding from the European Union's Horizon 2020 research and innovation program iMIRACLI under Marie Skłodowska-Curie grant agreement no. 860100. LATMOS has been supported by the EU iCUPE (Integrating and Comprehensive Understanding on Polar Environments) project (grant agreement no. 689443) under the European Network for Observing our Changing Planet (ERA-Planet), as well as access to IDRIS HPC resources (GENCI allocation A009017141) and the IPSL mesoscale computing center (CICLAD: Calcul Intensif pour le CLimat, l’Atmosphère et la Dynamique) for model simulations. Naga Oshima was supported by the Japan Society for the Promotion of Science KAKENHI (grant nos. JP18H03363, JP18H05292, and JP21H03582), the Environment Research and Technology Development Fund (grant nos. JPMEERF20202003 and JPMEERF20205001) of the Environmental Restoration and Conservation Agency of Japan, the Arctic Challenge for Sustainability II (ArCS II) under program grant no. JPMXD1420318865, and a grant for the Global Environmental Research Coordination System from the Ministry of the Environment, Japan (MLIT1753). The research with GISS-E2.1 has been supported by the Aarhus University Interdisciplinary Centre for Climate Change (iClimate) OH fund (no. 2020-0162731), the FREYA project funded by the Nordic Council of Ministers (grant agreement nos. MST-227-00036 and MFVM-2019-13476), and the EVAM-SLCF funded by the Danish Environmental Agency (grant agreement no. MST-112-00298). Jesper Christensen (for DEHM model) received funding from the Danish Environmental Protection Agency (DANCEA funds for Environmental Support to the Arctic Region project; grant no. 2019-7975). Maria Sand has been supported by the Research Council of Norway (grant 315195, ACCEPT). Peer Reviewed "Article signat per més de 50 autors/es: Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons "

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    Recolector de Ciencia Abierta, RECOLECTA
    Article . 2022 . Peer-reviewed
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2022 . Peer-reviewed
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      Recolector de Ciencia Abierta, RECOLECTA
      Article . 2022 . Peer-reviewed
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2022 . Peer-reviewed
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    Authors: Docampo, P; Stefik, M; Guldin, S; Gunning, R; +6 Authors

    AbstractA new self‐assembly platform for the fast and straightforward synthesis of bicontinuous, mesoporous TiO2 films is presented, based on the triblock terpolymer poly(isoprene‐b‐styrene‐b‐ethylene oxide). This new materials route allows the co‐assembly of the metal oxide as a fully interconnected minority phase, which results in a highly porous photoanode with strong advantages over the state‐of‐the‐art nanoparticle‐based photoanodes employed in solid‐state dye‐sensitized solar cells. Devices fabricated through this triblock terpolymer route exhibit a high availability of sub‐bandgap states distributed in a narrow and low enough energy band, which maximizes photoinduced charge generation from a state‐of‐the‐art organic dye, C220. As a consequence, the co‐assembled mesoporous metal oxide system outperformed the conventional nanoparticle‐based electrodes fabricated and tested under the same conditions, exhibiting solar power‐conversion efficiencies of over 5%.

    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/ Advanced Energy Mate...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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    Authors: K. P. Wyche; P. S. Monks; K. L. Smallbone; J. F. Hamilton; +8 Authors

    Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.

    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/ Atmospheric Chemistr...arrow_drop_down
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    https://www.atmos-chem-phys.ne...
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      https://www.atmos-chem-phys.ne...
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    Authors: Almut Arneth; Guy Schurgers; J. Lathière; T. Duhl; +4 Authors

    Abstract. Due to its effects on the atmospheric lifetime of methane, the burdens of tropospheric ozone and growth of secondary organic aerosol, isoprene is central among the biogenic compounds that need to be taken into account for assessment of anthropogenic air pollution-climate change interactions. Lack of process-understanding regarding leaf isoprene production as well as of suitable observations to constrain and evaluate regional or global simulation results add large uncertainties to past, present and future emissions estimates. Focusing on contemporary climate conditions, we compare three global isoprene models that differ in their representation of vegetation and isoprene emission algorithm. We specifically aim to investigate the between- and within model variation that is introduced by varying some of the models' main features, and to determine which spatial and/or temporal features are robust between models and different experimental set-ups. In their individual standard configurations, the models broadly agree with respect to the chief isoprene sources and emission seasonality, with maximum monthly emission rates around 20–25 Tg C, when averaged by 30-degree latitudinal bands. They also indicate relatively small (approximately 5 to 10 % around the mean) interannual variability of total global emissions. The models are sensitive to changes in one or more of their main model components and drivers (e.g., underlying vegetation fields, climate input) which can yield increases or decreases in total annual emissions of cumulatively by more than 30 %. Varying drivers also strongly alters the seasonal emission pattern. The variable response needs to be interpreted in view of the vegetation emission capacities, as well as diverging absolute and regional distribution of light, radiation and temperature, but the direction of the simulated emission changes was not as uniform as anticipated. Our results highlight the need for modellers to evaluate their implementations of isoprene emission models carefully when performing simulations that use non-standard emission model configurations.

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    Atmospheric Chemistry and Physics (ACP)
    Article . Preprint
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    https://doi.org/10.5194/acpd-1...
    Preprint . 2011
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    Article . 2011
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      Atmospheric Chemistry and Physics (ACP)
      Article . Preprint
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      https://doi.org/10.5194/acpd-1...
      Preprint . 2011
      License: CC BY
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      Article . 2011
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    Authors: Telmo Morato; Kristina Øie Kvile; Gerald H. Taranto; Fernando Tempera; +6 Authors

    Abstract. This work aims at characterising the seamount physiography and biology in the OSPAR Convention limits (North-East Atlantic Ocean) and Mediterranean Sea. We first inferred potential abundance, location and morphological characteristics of seamounts, and secondly, summarized the existing biological, geological and oceanographic in-situ research, identifying examples of well-studied seamounts. Our study showed that the seamount population in the OSPAR area (North-East Atlantic) and in Mediterranean Sea is large with around 1061 and 202 seamount-like features, respectively. Similarly, seamounts occupy large areas of about 1 116 000 km2 in the OSPAR region and of about 184 000 km2 in the Mediterranean Sea, which is much larger than previously thought. The presence of seamounts in the North-East Atlantic has been known since the late 19th Century but overall knowledge regarding seamount ecology and geology is still relatively poor. Only 37 seamounts in the OSPAR area (3.5% of all seamounts in the region), 22 in the Mediterranean Sea (9.2% of all seamounts in the region) and 25 in the North-East Atlantic south of the OSPAR have in-situ information. Seamounts mapped in both areas are in general very heterogeneous, showing diverse geophysical characteristics. These differences will likely affect the biological diversity and production of resident and associated organisms.

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    Biogeosciences
    Article . 2013 . Peer-reviewed
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    Biogeosciences
    Article . 2013
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    https://doi.org/10.5194/bgd-9-...
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      Biogeosciences
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      https://doi.org/10.5194/bgd-9-...
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    Authors: W. J. F. Acton; S. Schallhart; B. Langford; A. Valach; +11 Authors

    This paper reports the fluxes and mixing ratios of biogenically emitted volatile organic compounds (BVOCs) 4aEuro-m above a mixed oak and hornbeam forest in northern Italy. Fluxes of methanol, acetaldehyde, isoprene, methyl vinyl ketoneaEuro-+aEuro-methacrolein, methyl ethyl ketone and monoterpenes were obtained using both a proton-transfer-reaction mass spectrometer (PTR-MS) and a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) together with the methods of virtual disjunct eddy covariance (using PTR-MS) and eddy covariance (using PTR-ToF-MS). Isoprene was the dominant emitted compound with a mean daytime flux of 1.9aEuro-mgaEuro-m(-2)aEuro-h(-1). Mixing ratios, recorded 4aEuro-m above the canopy, were dominated by methanol with a mean value of 6.2aEuro-ppbv over the 28-day measurement period. Comparison of isoprene fluxes calculated using the PTR-MS and PTR-ToF-MS showed very good agreement while comparison of the monoterpene fluxes suggested a slight over estimation of the flux by the PTR-MS. A basal isoprene emission rate for the forest of 1.7aEuro-mgaEuro-m(-2)aEuro-h(-1) was calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) isoprene emission algorithms (Guenther et al., 2006). A detailed tree-species distribution map for the site enabled the leaf-level emission of isoprene and monoterpenes recorded using gas-chromatography mass spectrometry (GC-MS) to be scaled up to produce a bottom-up canopy-scale flux. This was compared with the top-down canopy-scale flux obtained by measurements. For monoterpenes, the two estimates were closely correlated and this correlation improved when the plant-species composition in the individual flux footprint was taken into account. However, the bottom-up approach significantly underestimated the isoprene flux, compared with the top-down measurements, suggesting that the leaf-level measurements were not representative of actual emission rates. Peer reviewed

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    NERC Open Research Archive
    Article . 2016 . Peer-reviewed
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    Atmospheric Chemistry and Physics (ACP)
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    https://doi.org/10.5194/acpd-1...
    Other literature type . Preprint . 2015
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      https://doi.org/10.5194/acpd-1...
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    Authors: Guldin, Stefan; Docampo, Pablo; Stefik, Morgan; Kamita, Gen; +3 Authors

    AbstractMorphology control on the 10 nm length scale in mesoporous TiO2 films is crucial for the manufacture of high‐performance dye‐sensitized solar cells. While the combination of block‐copolymer self‐assembly with sol–gel chemistry yields good results for very thin films, the shrinkage during the film manufacture typically prevents the build‐up of sufficiently thick layers to enable optimum solar cell operation. Here, a study on the temporal evolution of block‐copolymer‐directed mesoporous TiO2 films during annealing and calcination is presented. The in‐situ investigation of the shrinkage process enables the establishment of a simple and fast protocol for the fabrication of thicker films. When used as photoanodes in solid‐state dye‐sensitized solar cells, the mesoporous networks exhibit significantly enhanced transport and collection rates compared to the state‐of‐the‐art nanoparticle‐based devices. As a consequence of the increased film thickness, power conversion efficiencies above 4% are reached.

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