126 research outputs found

    Source attribution of air pollution by spatial scale separation using high spatial density networks of low cost air quality sensors

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    To carry out detailed source attribution for air quality assessment it is necessary to distinguish pollutant contributions that arise from local emissions from those attributable to non-local or regional emission sources. Frequently this requires the use of complex models and inversion methods, prior knowledge or assumptions regarding the pollution environment. In this paper we demonstrate how high spatial density and fast response measurements from low-cost sensor networks may facilitate this separation. A purely measurement-based approach to extract underlying pollution levels (baselines) from the measurements is presented exploiting the different relative frequencies of local and background pollution variations. This paper shows that if high spatial and temporal coverage of air quality measurements are available, the different contributions to the total pollution levels, namely the regional signal as well as near and far field local sources, can be quantified. The advantage of using high spatial resolution observations, as can be provided by low-cost sensor networks, lies in the fact that no prior assumptions about pollution levels at individual deployment sites are required. The methodology we present here, utilising measurements of carbon monoxide (CO), has wide applicability, including additional gas phase species and measurements obtained using reference networks. While similar studies have been performed, this is the first study using networks at this density, or using low cost sensor networks.The authors thank EPSRC (EP/E001912/1) for funding for the Message project. IH thanks the German National Academic Foundation for funding of MPhil degree.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S1352231015300583#

    The binding of Varp to VAMP7 traps VAMP7 in a closed, fusogenically inactive conformation.

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    SNAREs provide energy and specificity to membrane fusion events. Fusogenic trans-SNARE complexes are assembled from glutamine-contributing SNAREs (Q-SNAREs) embedded in one membrane and an arginine-contributing SNARE (R-SNARE) embedded in the other. Regulation of membrane fusion events is crucial for intracellular trafficking. We identify the endosomal protein Varp as an R-SNARE-binding regulator of SNARE complex formation. Varp colocalizes with and binds to VAMP7, an R-SNARE that is involved in both endocytic and secretory pathways. We present the structure of the second ankyrin repeat domain of mammalian Varp in complex with the cytosolic portion of VAMP7. The VAMP7-SNARE motif is trapped between Varp and the VAMP7 longin domain, and hence Varp kinetically inhibits the ability of VAMP7 to form SNARE complexes. This inhibition will be increased when Varp can also bind to other proteins present on the same membrane as VAMP7, such as Rab32-GTP

    Measurement of D-s(+) and D-s(*+) production in B meson decays and from continuum e(+)e(-) annihilation at √s=10.6 GeV

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    This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APSNew measurements of Ds+ and Ds*+ meson production rates from B decays and from qq̅ continuum events near the ΄(4S) resonance are presented. Using 20.8 fb-1 of data on the ΄(4S) resonance and 2.6 fb-1 off-resonance, we find the inclusive branching fractions B(B⃗Ds+X)=(10.93±0.19±0.58±2.73)% and B(B⃗Ds*+X)=(7.9±0.8±0.7±2.0)%, where the first error is statistical, the second is systematic, and the third is due to the Ds+→φπ+ branching fraction uncertainty. The production cross sections σ(e+e-→Ds+X)×B(Ds+→φπ+)=7.55±0.20±0.34pb and σ(e+e-→Ds*±X)×B(Ds+→φπ+)=5.8±0.7±0.5pb are measured at center-of-mass energies about 40 MeV below the ΄(4S) mass. The branching fractions ÎŁB(B⃗Ds(*)+D(*))=(5.07±0.14±0.30±1.27)% and ÎŁB(B⃗Ds*+D(*))=(4.1±0.2±0.4±1.0)% are determined from the Ds(*)+ momentum spectra. The mass difference m(Ds+)-m(D+)=98.4±0.1±0.3MeV/c2 is also measured.This work was supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the Swiss NSF, A. P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Street Canyon Atmospheric Composition: Coupling Dynamics and Chemistry

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    Street Canyon Atmospheric Composition: Coupling Dynamics and ChemistryPreviously curated at: http://cedadocs.ceda.ac.uk/345/ Event type: conference. The publish date on this item was its original completed date. This item was not refereed before the publication Main files in this record: RSC_poster_09_final[1].pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Miss Vivien Bright. Transferred to CEDA document repository community on Zenodo on 2022-11-2
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