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184 results for “Organic Compounds”
Figure 1 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids
Figure 1: Chemotaxis (percent attracted) of Caenorhabditis elegans toward Stropharia rugosoannulata stain 1.2052 cultured on water agar supplemented with amino acids. Controls are phenylalanine or tyrosine alone and strain 1.2052 alone. The error bars indicate standard deviation. The statistical differences were analyzed using one-way ANOVA, *P<0.05, **P<0.01.
Volatile organic compounds (BVOCs and AVOCs) that were measured at the Eastern Mediterranean coast (Ramat Hanadiv, Israel)
<p>Volatile organic compounds (BVOCs and AVOCs), which were measured at the Eastern Mediterranean coast (Ramat Hanadiv, Israel) in 2015 using a PTR-ToF-MS, and have been published. The publication is available at: <a href="https://acp.copernicus.org/articles/20/12741/2020/acp-20-12741-2020.html" target="_new" rel="noreferrer">https://acp.copernicus.org/articles/20/12741/2020/acp-20-12741-2020.html</a></p>
Can metal organic frameworks outperform adsorptive removal of harmful phenolic compound 2-chlorophenol by activated carbon?
<p>Dataset supporting publication. High resolution images, and full data set as produced in manuscript figures.</p> <p><strong>Preprint</strong>: <a href="https://doi.org/10.26434/chemrxiv.10320752.v1">https://doi.org/10.26434/chemrxiv.10320752.v1 </a></p> <p><strong>Published article:</strong> <a href="https://doi.org/10.1016/j.cherd.2020.03.017">https://doi.org/10.1016/j.cherd.2020.03.017 </a></p> <p><strong>Abstract:</strong> Removal of persistent organic compounds from aqueous solutions is generally achieved using adsorbent like activated carbon (AC) but it suffers from limited adsorption capacity due to low surface area. This paper describes a pioneering work on the adsorption of an organic pollutant, 2-chlorophenol (2-CP) by two MOFs with high surface area and water stability; MIL-101 and its amino-derivative, MIL-101-NH<sub>2</sub>. Although MOFs have higher surface area than AC, the latter was proven better having the highest equilibrium 2-CP uptake (345 mg.g<sup>-1</sup>), followed by MIL-101 (121 mg.g<sup>-1</sup>) and MIL-101-NH<sub>2</sub> (84 mg.g<sup>-1</sup>). Used MIL-101 could be easily regenerated multiple times by washing with ethanol and even showed improved adsorption capacity after each washing cycle. These results can open the doors to meticulous adsorbent selection for treating 2-CP-contaminated water. </p>
Data from: Effect of altitude on volatile organic and phenolic compounds of artemisia brevifolia wall ex Dc. from the Western Himalayas
Open the record for dataset details and reuse information.
Environmental fate of combustion-derived organic compounds in arid, urban soils in central Arizona-Phoenix
In this research we wanted to ask, what is the magnitude, distribution, and fate of non-point carbon pollution in a low-density, urban area? To answer this question, the goal of the project is to: 1) characterize and quantify combustion-derived carbon compounds in soils near roadways across the Phoenix valley, 2) explore the dynamic fate of Polycyclic Aromatic Hydrocarbons (PAHs) in soils, and 3) assess the importance of microbial community structure in PAH storage and dynamics. We collected 63 soil samples near highways across the Phoenix valley to characterize and quantify PAH compounds using extraction methods with Ultrasound Sonication and analyses by Gas Chromatography-Mass Spectrometry (GC-MS). Additionally, we measured a suite of soil properties and processes to explore the role of abiotic and biotic factors on the retention of PAHs in urban soil. PAH concentrations in arid Phoenix soils ranged from 52 ug/kg dry soil to 8,296 ug/kg (mean 926 ug/kg), nearly an order of magnitude lower on average than expected based on data from other cities (Figure 1, Table 1). The project findings show the extent of these pollutants, an EPA-priority group of hazardous compounds, in urban soils. Although the most likely sources for PAH content in roadway soils are vehicle emissions, they were not correlated with traffic density (r2 = 0.024; p = 0.26) or highway age (r2 = 0.044; p = 0.13) across all sites. However, PAH concentrations were significantly correlated to soil organic matter (r2 = 0.36; p less than 0.001). These results suggest that PAH concentrations in roadway soils of desert cities may be controlled by factors associated with carbon retention, such as soil organic matter, rather than source or rate of deposition
Data from: Bacterial phylogeny predicts volatile organic compound composition and olfactory response of an aphid parasitoid
There is increasing evidence that microorganisms emit a wide range of volatile compounds (mVOCs, microbial volatile organic compounds) that act as insect semiochemicals, and therefore play an important role in insect behaviour. Although it is generally believed that phylogenetically closely related microbes tend to have similar phenotypic characteristics and therefore may elicit similar responses in insects, currently little is known about whether the evolutionary history and phylogenetic relationships among microorganisms have an impact on insect-microbe interactions. In this study, we tested the hypothesis that phylogenetic relationships among 40 Bacillus strains isolated from diverse environmental sources predicted mVOC composition and the olfactory response of the generalist aphid parasitoid Aphidius colemani. Results revealed that phylogenetically closely related Bacillus strains emitted similar blends of mVOCs and elicited a comparable olfactory response of A. colemani in Y-tube olfactometer bioassays, varying between attraction and repellence. Analysis of the chemical composition of the mVOC blends showed that all Bacillus strains produced a highly similar set of volatiles, but often in different concentrations and ratios. Benzaldehyde was produced in relatively high concentrations by strains that repel A. colemani, while attractive mVOC blends contained relatively higher amounts of acetoin, 2,3-butanediol, 2,3-butanedione, eucalyptol and isoamylamine. Overall, these results indicate that bacterial phylogeny had a strong impact on mVOC compositions and as a result on the olfactory responses of insects.
Coherent spin dynamics of solitons in the organic spin chain compounds (o-DMTTF)2X (X = Cl, Br)
<p>Dataset of the paper</p> <p>https://doi.org/10.1103/PhysRevB.100.224414</p> <p> </p>
Accompanying Data - Nitrogenous Compound Utilization and Production of Volatile Organic Compounds among Commercial Wine Yeasts Highlight Strain-Specific Metabolic Diversity
<p>This repository contains all the data and some of the performed statistical analysis from all the measurements in the following paper: Scott Jr WT, Van Mastrigt O, Block DE, Notebaart RA, Smid EJ. Nitrogenous compound utilization and production of volatile organic compounds among commercial wine yeasts highlight strain-specific metabolic diversity. Microbiology spectrum. 2021 Aug 31;9(1):10-128.</p><p>Please cite: Scott Jr WT, Van Mastrigt O, Block DE, Notebaart RA, Smid EJ. Nitrogenous compound utilization and production of volatile organic compounds among commercial wine yeasts highlight strain-specific metabolic diversity. Microbiology spectrum. 2021 Aug 31;9(1):10-128.</p><p>Contact: Dr. William T. Scott (william.scott@wur.nl) or Dr. Eddy J. Smid (eddy.smid@wur.nl) for more information</p>
Organic compounds drive growth in phytoplankton taxa from different functional groups
<p>Phytoplankton are usually considered autotrophs, but an increasing number of studies shows that many taxa are able to also utilise organic carbon. Acquiring nutrients and energy from different sources might enable an efficient uptake of required substances and provide a strategy to deal with a varying resource availability, especially in highly dynamic ecosystems such as estuaries. In our study we investigated the effects of 31 organic carbon sources on the growth (proxied by differences in cell counts after 24 h exposure) of 17 phytoplankton strains from the Elbe estuary spanning four functional groups. All of our strains were able to make use of at least 1 and up to 26 organic compounds for growth. Pico-sized green algae such as <em>Mychonastes</em>, as well as the nano-sized green alga <em>Monoraphidium </em>in particular were positively affected by a high variety of substances. Reduced light availability, typically appearing in turbid estuaries and similar habitats, resulted in an overall poorer ability to utilise organic substances for growth, indicating that organic carbon acquisition was not primarily a strategy to deal with darkness. Our results give further evidence for mixotrophy being an ubiquitous ability of phytoplankton and highlight the importance to consider this trophic strategy in research.</p>
Supplementary Material for "Model-Free Analysis of Experimental Residual Diploar Couplings in Small Organic Compounds"
<p>NMR Spectra (CLIP-HSQC, perfectCLIP-HSQC, TSE-PSYCHEDELIC) of isopinocampheol in six alignment conditions.</p> <p>Simulation input (experimental RDC data in six alignment media, input geometries, keywords) and output files (simulation / geometry trajectories, alignment data, SECONDA analysis) for isopinocampheol runs with the TITANIA software.</p>
Raw data for "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability"
<p>This upload refers to work entitled "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability" and contains the unprocessed data obtained during experiments perform. </p>
Pre-Analysis Bioinformatics Files for The Microbiome and Volatile Organic Compounds Reflect the State of Decomposition in an Indoor Environment
<p>Data statistics before and after trimming, FastQC reports before and after trimming, MultiQC reports before and after trimming, commands for the Kraken2-Bracken analysis, and classification reports. Read the read.me file for file names and descriptions. </p>
Volatile organic compounds (VOIs) in seawater and sediment pore water collected in Funka Bay and Bering and Chukchi Seas
<p>The data of volatile organic compounds (VOIs) in seawater and sediment pore water collected in the Funka Bay, Hokkaido, Japan, and the Bering and Chukchi Seas. Funka Bay's samples were collected in 2018-2019. Bering and Chukchi Seas' samples were collected in July of 2017 and 2018. The article entitled "Marine sediment as a likely source of methyl and ethyl iodides in subpolar and polar seas" by Ooki et al. published by Communications Earth & Environment used these datasets. The datasets are also provided as supplementary data1-4 in the article. Details of datasets are described in the article. Please cite this article when you use these datasets.</p>
Insect Odorant Binding Protein Dataset of Binding Affinities against Volatile Organic Compounds
<p>This is an archival version of the initial iOBPdb dataset of insect odorant binding protein binding affinities against volatile organic compounds. It contains 215 functional studies containing 381 unique OBPs from 91 insect species.</p>
Data and code for theoretical analyses for the evolution of biogenic volatile organic compounds (BVOCs) emission strategy
<p>These are Python code for analysis and JSON data obtained by simulation with the lattice model.</p> <p>To visualize figures better, we have slightly modified the content of "LatticeModelVisualization.ipynb".</p>
Quantification of volatile organic compound emissions from unconventional oil and gas development
<p>Oil and gas (O&G) development in the U.S. has accelerated in the past two decades, aided by unconventional extraction techniques including hydraulic fracturing and horizontal drilling. Potential environmental and health impacts of volatile organic compounds (VOCs) originating from O&G activities in populated regions have raised concerns. In Broomfield, Colorado, six new O&G well pads were approved for development in 2017 and an air monitoring program was established in October 2018 to collect weekly and plume-triggered air samples. This study addresses the limited existing knowledge of activity-specific VOC emission rates from unconventional O&G development (UOGD), utilizing these observations and dispersion model simulations through emission inversion methods. Emissions are characterized from well drilling, hydraulic fracturing, coiled tubing/millout, flowback, and production operations.</p> <p>Substantial variations in average VOC emission rates, determined using weekly canister observations, are observed across different UOGD phases. Drilling and coiled tubing/millout operations exhibit the highest VOC emission rates, attributed to hydrocarbon release from shale formations and drilling mud. In contrast, hydraulic fracturing gives lower emission rates, consistent with injection of fluids into the well, minimizing the probability of subsurface hydrocarbon emissions. Diesel-powered engines are identified as the primary ethyne sources during hydraulic fracturing. Production was characterized by lower VOC emission rates than pre-production phases but remains an important emission category due to its long duration (decades). Internal variations of emission rates within each phase highlight the complexity of factors and activities influencing emission rates, including, for example, vertical vs. horizontal drilling and periodic maintenance activities. VOC emission rates associated with drilling mud volatilization and hydraulic fracturing suggest that previously published emission estimates (EPA (2022), and Hecobian et al. (2019)) underestimate VOC emission rates during these activities. Significantly lower emission rates during flowback compared to previous work (Hecobian et al., 2019) reveal how improved management practices, including tankless, closed-loop fluid handling systems have effectively reduced what used to be a dominant source of pre-production VOC emissions. Plume-triggered samples, capturing transient high-concentration plumes, reveal short-term VOC emission rates approximately ten times higher for drilling and flowback than determined from weekly samples. In the case of flowback, short-term emission pulses have been linked to periodic emptying of sand canisters used to trap fracking sand emerging from previously fracked wells.</p>
volatile organic compounds that were measred at the Dead Sea - Israel (both terrestrial and coastal; Anthropogenic and biogenic)
<p>Multiple VOCs (biogenic and anthropogenic) were sampled by our research group at various terrestrial and coastal sites around the Dead Sea (Israel). Analysis was conducted by Prof. Donald Blake, and the data were included in a publication available at <a href="https://acp.copernicus.org/articles/19/7667/2019/" target="_new" rel="noreferrer">https://acp.copernicus.org/articles/19/7667/2019/</a>.</p>
Dataset on the characterization of the flavor of two red wine varieties using sensory descriptive analysis, volatile organic compounds quantitative analysis by GC-MS and odorant composition by GC-MS-O
<p>The dataset contains data that were collected on 2 sets of 8 French red wines from two grape varieties, Pinot Noir (PN) and Cabernet Franc (CF). It provides, for the 16 wines, (i) sensory descriptive data obtained with a trained panel, (ii) volatile organic compounds (VOC) quantification data obtained by Gas Chromatography–Mass Spectrometry (GC-MS) and (iii) odorant composition obtained by Gas Chromatography–Mass Spectrometry–Olfactometry (GC-MS-O).</p> <p> </p> <p>The dataset is a Microsoft Excel Worksheet containing 8 sheets.</p> <p>- Sheet 1: Information</p> <p>Gives information about the sheets contained in this .xlsx file</p> <p>- Sheet 2: Experimental_factors</p> <p>Each row represents a wine</p> <p>Each column corresponds to an experimental factors of the wines (Grape variety, Vintage and Protected Designation of Origin)</p> <p>- Sheet 3: List_sensory_descriptors</p> <p>Lists the 33 sensory descriptors used for the sensory descriptive analysis of the wines</p> <p>- Sheet 4: Sensory_descriptive_analysis</p> <p>Each row represents a wine</p> <p>Each column corresponds to a condition (2640 columns)</p> <p>Senso_(ortho or retro)_(Panelist1 to Panelist 16)_(1 to 33 Sensory descriptors)_(1 to 3 repetitions for ortho and 1 to 2 repetitions for retro)</p> <p>For the ortho (orthonasal) measurements, there is 16 panelists, 33 sensory descriptors and 3 repetitions = 1584 columns</p> <p>For the retro (retronasal) measurements, there is 16 panelists, 33 sensory descriptors and 2 repetitions = 1056 columns</p> <p>Each cell contains a sensory measurement for the corresponding condition in the corresponding wine</p> <p>- Sheet 5: List_VOC</p> <p>Lists the 45 VOC quantified in the wines with their corresponding CAS number</p> <p>VOC: Volatil Organic Compounds</p> <p>- Sheet 6: VOC_quantification</p> <p>Each row represents a wine</p> <p>Each column corresponds to a VOC (45 columns)</p> <p>Each cell contains the quantification of the corresponding VOC in the corresponding wine</p> <p>- Sheet 7: List_GC-MS-O</p> <p>Lists the 49 odor-active compounds identified with their corresponding CAS number and the 34 compounds identified by their apex indice</p> <p>- Sheet 8: GC-MS-O</p> <p>Each row represents a wine</p> <p>Each column corresponds to an odor-active compound identified by its CAS number or by its Apex indice if the compound was not identify (81 odor-active compounds) + the number of judges who smelled the compound and its description (by 8 judges) = 9 columns per odor-active compound for a total of 729 columns</p>
Technical note: Interferences of volatile organic compounds (VOC) on methane concentration measurements - Raw Data
<p>Technical note: Interferences of volatile organic compounds (VOC) on methane concentration measurements - Raw Data</p>
Can metal organic frameworks outperform adsorptive removal of harmful phenolic compound 2-chlorophenol by activated carbon?
<p>A more complete version of this dataset, along with publication details, is available from <a href="https://zenodo.org/record/2586955">https://zenodo.org/record/2586955</a></p>
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