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148 results for “Volatile organic compounds”
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>
Measurement report: Unexpected high volatile organic compounds emission from vehicles on the Tibetan Plateau Dataset
<p>This dataset includes various emission profiles and related data, specifically:</p> <ol> <li> <p><strong>Source Profile Data at Different Altitudes</strong>.</p> </li> <li> <p><strong>Emission Factor Data</strong>.</p> </li> <li> <p><strong>Emission Ratio Data</strong>.</p> </li> <li><strong>Source Profile Data from PMF Source Apportionment</strong>: Data obtained through Positive Matrix Factorization (PMF), revealing the composition of emission sources.</li> <li> <p><strong>Average Profiles of Gasoline Vapors</strong>: Derived from sealed housing evaporative determination (SHED) tests, with references 1-7.</p> </li> <li> <p><strong>Average Profiles of Gasoline Vehicle Exhaust</strong>: Based on dynamometer tests, with references 2, 8-13.</p> </li> <li> <p><strong>Average Profiles of Vehicular Emissions</strong>: Collected from low-altitude tunnel measurements, reflecting emissions in real-world driving scenarios, with references 14-24.</p> </li> </ol>
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China
<p>This dataset contains the input and output data of the multiple PMF for volatile organic compounds (VOCs) source apportionment in the suburbs of Tianjin, China, during the outbreak of COVID-19 period (November 2019 to March 2020).</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 181 functional studies containing 382 unique OBPs from 91 insect species for 622 individual VOC targets.</p>
Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China
<p>Ambient volatile organic compounds (VOCs) are crucial precursors for the formation of secondary organic aerosol (SOA) and ozone (O<sub>3</sub>). We have conducted in-situ observations and compiled a comprehensive dataset of ambient volatile organic compound (VOC) compositions and concentrations in Beijing, China, spanning the period from 2016 to 2020. The dataset covers a wide range of VOC species including 29 alkanes, 11 alkenes, 1 alkyne, 16 aromatics, 28 halohydrocarbons, 13 oxygenated VOCs (OVOCs), and 1 nitrogenous VOC (acetonitrile). The presentation and analysis of this dataset is available in a paper submitted to Earth System Science Data (Simon et al, in prep). The findings and analysis of this dataset have been documented in a paper that has been submitted to Earth System Science Data (Liu et al., in prep).</p> <p>If you use the dataset for related scientific research, please cite the corresponding reference:</p> <p> Liu et al (in prep); Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China; Earth System Science Data.</p>
Data from: Bacterial phylogeny predicts volatile organic compound composition and olfactory response of an aphid parasitoid
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Quantification of volatile organic compound emissions from unconventional oil and gas development
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Unwanted loss of volatile organic compounds (VOCs) during in situ chemical oxidation sample preservation: Mechanisms and solutions
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Data from: Volatile organic compounds of diverse origins and their changes associated with cultivar decay in a fungus-farming termite
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Data from: Allelopathic effects of volatile organic compounds released from Pinus halepensis needles and roots
The Mediterranean region is recognized as a global biodiversity hotspot. However, over the last decades, the cessation of traditional farming in the north part of Mediterranean basin has given way to strong afforestation leading to occurrence of abandoned agricultural lands colonized by pioneer expansionist species like Pinus halepensis. This pine species is known to synthesize a wide range of secondary metabolites and previous studies have demonstrated strong allelopathic potentialities of its needle and root leachates. Pinus halepensis is also recognized to release significant amounts of volatile organic compounds (VOC) with potential allelopathic effects that has never been investigated. In this context, the objectives of the present study were to improve our knowledge about the VOC released from P. halepensis needles and roots, determine if these VOC affect the seed germination and root growth of two herbaceous target species (Lactuca sativa and Linum strictum), and evaluate if soil microorganisms modulate the potential allelopathic effects of these VOC. Thirty terpenes were detected from both needle and root emissions with β-caryophyllene as the major volatile. Numerous terpenes, such as β-caryophyllene, -terpinene or -pinene showed higher headspace concentrations according to the gradient green needles < senescent needles < needle litter. Seed germination and root growth of the two target species were mainly reduced in presence of P. halepensis VOC. In strong contrast with the trend reported with needle leachates in literature, we observed an increasing inhibitory effect of P. halepensis VOC with the progress of needle physiological stages (i.e. green needle < senescent needle < needle litter). Surprisingly, several inhibitory effects observed on filter paper were also found or even amplified when natural soil was used as a substrate, highlighting that soil microorganisms do not necessarily limit the negative effects of VOC released by P. halepensis on herbaceous target species.
Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) as a tool for studying animal volatile organic compound (VOC) emissions
<p>1. Chemical sensing in vertebrates is crucial in their lives, and efforts are undertaken towards deciphering their chemical language. Volatile organic compounds (VOCs) is a group of chemicals believed to play an essential role in a wide variety of animal interactions. Therefore, understanding what animals sense themselves and untangling the ecological role of their volatile cues can be accomplished by analysing VOC emissions. A Proton-Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-TOF-MS) is an instrument that measures VOCs in real-time in an air sample. Since this technique acts as a hyper-sensitive 'nose' it has a similar potential in deciphering the chemical language of vertebrates.</p> <p>2. Here, we validate the use of PTR-TOF-MS as a tool to measure VOCs from vertebrates, which in turn will help resolve vertebrate interactions through VOCs. The instrument monitors and records the full spectrum of VOCs emitted by an individual with a high accuracy and low detection limit, including transient VOC emissions. We propose and test diverse measuring configurations that allow for measurement of VOC emissions from different vertebrates and their exudates: full body, specific parts of the body, urine and femoral pores. In addition, we test configurations for sudden and short-lasting processes as VOCs emitted during adder skin shedding as well as the emissions of skin secretions upon mechanical and physiological stimulation in amphibia. Our configurations work in tandem with Gas Chromatography Mass Spectrometry (GC-MS) to allow compound structure verification.</p> <p>3. We discuss the configurations and methodologies used and conclude with recommendations for further studies, such as the choice of chamber size and flow. We also report the results of the measurements on vertebrates —that are novel to science— and discuss their ecological meaning.</p> <p>4. We argue that PTR-TOF-MS has a high potential to resolve important unanswered questions in vertebrate chemical ecology with great adaptability to a wide range of experimental setups. If combined with a structure verification tool, such as GC-MS, the creative deployment of PTR-TOF-MS in various future study designs will lead to the identification of ecologically relevant VOCs.</p>
Data from: An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds
Chemical ecology is an ever‐expanding field with a growing interest in population‐ and community‐level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large‐scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large‐scale study of volatiles. A large‐scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid‐phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large‐scale in situ sampling and analysis of volatiles. The protocol for large‐scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.
Bacterial community richness shifts the balance between volatile organic compound-mediated microbe-pathogen and microbe-plant interactions
Even though bacteria are important in determining plant growth and health via volatile organic compounds (VOCs), it is unclear how these beneficial effects emerge in multi-species microbiomes. Here we studied this using a model plant-bacteria system, where we manipulated bacterial community richness and composition and determined the subsequent effects on VOC production and VOC-mediated pathogen suppression and plant growth-promotion. We assembled VOC-producing bacterial communities in different richness levels ranging from one to twelve strains using three soil-dwelling bacterial genera (Bacillus, Paenibacillus and Pseudomonas) and investigated how the composition and richness of bacterial community affect the production and functioning of VOCs. We found that VOC production correlated positively with pathogen suppression and plant growth-promotion and that all bacteria produced a diverse set of VOCs. However, while pathogen suppression was maximized at intermediate community richness levels when the relative amount and the number of VOCs were the highest, plant growth-promotion was maximized at low richness levels and was only affected by the relative amount of plant growth-promoting VOCs. The contrasting effects of richness could be explained by differences in the amount and number of produced VOCs and by opposing effects of community productivity and evenness on pathogen suppression and plant-growth promotion along the richness gradient. Together, these results suggest that the number of interacting bacterial species and the structure of the rhizosphere microbiome drive the balance between VOC-mediated microbe-pathogen and microbe-plant interactions potentially affecting plant disease outcomes in natural and agricultural ecosystems.
Fig. 2 in Variation in the amino acids, volatile organic compounds and terpenes profiles in induced polyploids and in Solanum tuberosum varieties
Fig. 2. Biplot of Principal Component Analysis based on VOCs and Amino acids from leaves of Solanum allotetraploids (a), autotetraploids (b) and cultivated varieties (c). Components were calculated using Euclidean distances. Amino acids are depicted in the three-letter code. a) Allotetraploids (4xAL2 and 4xAL4) and diploid S. tuberosum x S. kurtzianum parental interspecific hybrid (2xPIH). b) Autotetraploids (4xAuL1, 4xAuL2 and 4xAuL3) and diploid S. kurtzianum parental line (2xPL). c) S. tuberosum cultivated varieties (4xCalen, 4xInnovator and 4xPampeana).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.