149 research outputs found

    Atmospheric boundary-layer structure observed during a haze event due to forest-fire smoke

    Get PDF
    During a haze event in Baltimore, U.S.A. from July 6 to 8, 2002, smoke from forest fires in the QuĂ©bec region (Canada), degraded air quality and impacted upon local climate, decreasing solar radiation and air temperature. The smoke particles in and above the atmospheric boundary layer (ABL) served as a tracer and provided a unique opportunity to investigate the ABL structure, especially entrainment. Elastic backscatter lidar measurements taken during the haze event distinctly reveal the downward sweeps (or wisps) of smoke-laden air from the free atmosphere into the ABL. Visualisations of mechanisms such as dry convection, the entrainment process, detrainment, coherent entrainment structures, and mixing inside the ABL, are presented. Thermals overshooting at the ABL top are shown to create disturbances in the form of gravity waves in the free atmosphere aloft, as evidenced by a corresponding ripple structure at the bottom of the smoke layer. Lidar data, aerosol groundbased measurements and supporting meteorological data are used to link free atmosphere, mixed-layer and ground-level aerosols. During the peak period of the haze event (July 7, 2002), the correlation between time series of elastic backscatter lidar data within the mixed layer and the scattering coefficient from a nephelometer at ground level was found to be high (R ÂŒ 0.96 for z ÂŒ 324 m, and R ÂŒ 0.89 for z ÂŒ 504 m). Ground-level aerosol concentration was at a maximum about 2 h after the smoke layer intersected with the growing ABL, confirming that the wisps do not initially reach the ground

    Interactive metagenomic visualization in a Web browser

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>A critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables.</p> <p>Results</p> <p>Here we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools.</p> <p>Conclusions</p> <p>Krona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: <url>http://krona.sourceforge.net</url>.</p

    Streaming histogram sketching for rapid microbiome analytics

    Get PDF
    Background: The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time. Results: We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed ‘histosketch’ that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a ‘real life’ example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s. Conclusions: Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space

    Airborne Emissions from 1961 to 2004 of Benzo[a]pyrene from U.S. Vehicles per km of Travel Based on Tunnel Studies

    Get PDF
    We identified 13 historical measurements of polycyclic aromatic hydrocarbons (PAHs) in U.S. vehicular traffic tunnels that were either directly presented as tailpipe emission factors in ÎŒg per vehicle-kilometer or convertible to such a form. Tunnel measurements capture fleet cruise emissions. Emission factors for benzo[a]pyrene (BaP) for a tunnel fleet operating under cruise conditions were highest prior to the 1980s and fell from more than 30-ÎŒg per vehicle-km to approximately 2-ÎŒg/km in the 1990s, an approximately 15-fold decline. Total annual U.S. (cruise) emissions of BaP dropped by a lesser factor, because total annual km driven increased by a factor of 2.7 during the period. Other PAH compounds measured in tunnels over the 40-year period (e.g., benzo[ghi]perylene, coronene) showed comparable reduction factors in emissions. PAH declines were comparable to those measured in tunnels for carbon monoxide, volatile organic compounds, and particulate organic carbon. The historical PAH “source terms” determined from the data are relevant to quantifying the benefits of emissions control technology and can be used in epidemiological studies evaluating the health effects of exposure, such as those undertaken with breast cancer in New York State

    Compendium of 4,941 rumen metagenome-assembled genomes for rumen microbiome biology and enzyme discovery

    Get PDF
    The Rowett Institute and SRUC are core funded by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government. The Roslin Institute forms part of the Royal (Dick) School of Veterinary Studies, University of Edinburgh. This project was supported by the Biotechnology and Biological Sciences Research Council (BBSRC; BB/N016742/1, BB/N01720X/1), including institute strategic programme and national capability awards to The Roslin Institute (BBSRC: BB/P013759/1, BB/P013732/1, BB/J004235/1, BB/J004243/1); and by the Scottish Government as part of the 2016–2021 commission.Peer reviewedPublisher PD
    • 

    corecore