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Abstract. Emissions from natural sources are driven by various external stimuli such as sunlight, temperature, and soil moisture. Once biogenic volatile organic compounds (BVOCs) are emitted into the atmosphere, they rapidly react with atmospheric oxidants, which has significant impacts on ozone and aerosol budgets. However, diurnal, seasonal, and interannual variability in these species are poorly captured in emissions models due to a lack of long-term, chemically speciated measurements. Therefore, increasing the monitoring of these emissions will improve the modeling of ozone and secondary organic aerosol concentrations. Using 2 years of speciated hourly BVOC data collected at the Virginia Forest Research Lab (VFRL) in Fluvanna County, Virginia, USA, we examine how minor changes in the composition of monoterpenes between seasons are found to have profound impacts on ozone and OH reactivity. The concentrations of a range of BVOCs in the summer were found to have two different diurnal profiles, which, we demonstrate, appear to be driven by light-dependent versus light-independent emissions. Factor analysis was used to separate the two observed diurnal profiles and determine the contribution from each emission type. Highly reactive BVOCs were found to have a large influence on atmospheric reactivity in the summer, particularly during the daytime. These findings reveal the need to monitor species with high atmospheric reactivity, even though they have low concentrations, to more accurately capture their emission trends in models.
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In-Canopy Biogenic Volatile Organic Compounds Mixing Ratios at the Virginia Forest Lab
{"Abstract":["Two years (September 15th, 2019-September 14th, 2021) of biogenic volatile organic compound concentration data from within the canopy of a forest in Fluvanna County, Virginia. An associated manuscript is published in atmospheric chemistry and physics titled - "Measurement Report: Variability in the composition of biogenic volatile organic compounds in a southeastern US forest and their role in atmospheric reactivity". The doi for this manuscript is: 10.5194/acp-2021-416.\n\nThe original version of this data set did not correct for when the data was sampled vs. when it was analyzed. The most recent version has been updated to reflect this and additional detail has been provided. Additionally, the calibration method for methacrolein and methyl vinyl ketone has been updated in this version of the data set. Given these changes, we ask that you use the most recent version.\n\nAdditional manuscripts associated with this data include: 'Minor contributions of daytime monoterpenes are major contributors to atmospheric reactivity' which discusses diurnal and seasonal variability found within the data and 'An autonomous remotely operated gas chromatograph for chemically resolved monitoring of atmospheric volatile organic compounds' which outlines the instrument developed for data collection and compound integration.\n\nThis will be the final update of this data set. Data collection is ongoing indefinitely, but future additions to the data set will be migrated to Dryad. Please email with any questions you may have regarding data collection or the data set."]}
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- Award ID(s):
- 1837882
- PAR ID:
- 10399091
- Publisher / Repository:
- Mendeley
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Abstract. Despite the significant contribution of biogenic volatileorganic compounds (BVOCs) to organic aerosol formation and ozone productionand loss, there are few long-term, year-round, ongoing measurements oftheir volume mixing ratios and quantification of their impacts onatmospheric reactivity. To address this gap, we present 1 year of hourlymeasurements of chemically resolved BVOCs between 15 September 2019 and15 September 2020, collected at a research tower in Central Virginiain a mixed forest representative of ecosystems in the Southeastern US.Mixing ratios of isoprene, isoprene oxidation products, monoterpenes, andsesquiterpenes are described and examined for their impact on the hydroxyradical (OH), ozone, and nitrate reactivity. Mixing ratios of isoprene rangefrom negligible in the winter to typical summertime 24 h averages of 4–6 ppb, while monoterpenes have more stable mixing ratios in the range of tenths of a part per billion up to ∼2 ppb year-round. Sesquiterpenes aretypically observed at mixing ratios of <10 ppt, but this representsa lower bound in their abundance. In the growing season, isoprene dominatesOH reactivity but is less important for ozone and nitrate reactivity.Monoterpenes are the most important BVOCs for ozone and nitrate reactivitythroughout the year and for OH reactivity outside of the growing season. Tobetter understand the impact of this compound class on OH, ozone, andnitrate reactivity, the role of individual monoterpenes is examined. Despitethe dominant contribution of α-pinene to total monoterpene mass, theaverage reaction rate of the monoterpene mixture with atmospheric oxidantsis between 25 % and 30 % faster than α-pinene due to thecontribution of more reactive but less abundant compounds. A majority ofreactivity comes from α-pinene and limonene (the most significantlow-mixing-ratio, high-reactivity isomer), highlighting the importance ofboth mixing ratio and structure in assessing atmospheric impacts ofemissions.more » « less
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Abstract Biogenic hydrocarbons are emitted into the Earth's atmosphere by terrestrial vegetation as by‐products of photosynthesis. Isoprene is one such hydrocarbon and is the second most abundant volatile organic compound emitted into the atmosphere (after methane). Reaction with ozone represents an important atmospheric sink for isoprene removal, forming carbonyl oxides (Criegee intermediates) with extended conjugation. In this manuscript, we argue that the extended conjugation of these Criegee intermediates enables electronic excitation of these compounds, on timescales that are competitive with their slow unimolecular decay and bimolecular chemistry. We show that the complexation of methacrolein oxide with water enhances the absorption cross section of the otherwise dark S1state, potentially revealing a new avenue for forming lower volatility compounds via tropospherically relevant photochemistry.more » « less
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Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated biogenic volatile organic compound (BVOC) measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA, for the year 2020 with emissions estimated by the Model of Emissions of Gases and Aerosols from Nature version 3.2 (MEGANv3.2). The emissions were subjected to oxidation in a 0-D box model (F0AM v4.3) to generate time series of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability in regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using an LDF =0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions–chemistry model constrained by regional concentrations of NOX and O3.more » « less
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{"Abstract":["The intended use of this archive is to facilitate meta-analysis of the Data Observation Network for Earth (DataONE, [1]). <\/p>\n\nDataONE is a distributed infrastructure that provides information about earth observation data. This dataset was derived from the DataONE network using Preston [2] between 17 October 2018 and 6 November 2018, resolving 335,213 urls at an average retrieval rate of about 5 seconds per url, or 720 files per hour, resulting in a data gzip compressed tar archive of 837.3 MB . <\/p>\n\nThe archive associates 325,757 unique metadata urls [3] to 202,063 unique ecological metadata files [4]. Also, the DataONE search index was captured to establish provenance of how the dataset descriptors were found and acquired. During the creation of the snapshot (or crawl), 15,389 urls [5], or 4.7% of urls, did not successfully resolve. <\/p>\n\nTo facilitate discovery, the record of the Preston snapshot crawl is included in the preston-ls-* files . There files are derived from the rdf/nquad file with hash://sha256/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f . This file can also be found in the data.tar.gz at data/8c/67/e0/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f/data . For more information about concepts and format, please see [2]. <\/p>\n\nTo extract all EML files from the included Preston archive, first extract the hashes assocated with EML files using:<\/p>\n\ncat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep "hash://" | sort | uniq > eml-hashes.txt<\/p>\n\nextract data.tar.gz using:<\/p>\n\n~/preston-archive$$ tar xzf data.tar.gz <\/p>\n\nthen use Preston to extract each hash using something like:<\/p>\n\n~/preston-archive$$ preston get hash://sha256/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa\n<eml:eml xmlns:eml="eml://ecoinformatics.org/eml-2.1.1" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:stmml="http://www.xml-cml.org/schema/stmml_1.1" packageId="doi:10.18739/A24P9Q" system="https://arcticdata.io" scope="system" xsi:schemaLocation="eml://ecoinformatics.org/eml-2.1.1 ~/development/eml/eml.xsd">\n <dataset>\n <alternateIdentifier>urn:x-wmo:md:org.aoncadis.www::d76bc3b5-7b19-11e4-8526-00c0f03d5b7c</alternateIdentifier>\n <alternateIdentifier>d76bc3b5-7b19-11e4-8526-00c0f03d5b7c</alternateIdentifier>\n <title>Airglow Image Data 2011 4 of 5</title>\n...<\/p>\n\nAlternatively, without using Preston, you can extract the data using the naming convention:<\/p>\n\ndata/[x]/[y]/[z]/[hash]/data<\/p>\n\nwhere x is the first 2 characters of the hash, y the second 2 characters, z the third 2 characters, and hash the full sha256 content hash of the EML file.<\/p>\n\nFor example, the hash hash://sha256/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa can be found in the file: data/00/00/2d/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa/data . For more information, see [2].<\/p>\n\nThe intended use of this archive is to facilitate meta-analysis of the DataONE dataset network. <\/p>\n\n[1] DataONE, https://www.dataone.org\n[2] https://preston.guoda.bio, https://doi.org/10.5281/zenodo.1410543 . DataONE was crawled via Preston with "preston update -u https://dataone.org".\n[3] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep -v "hash://" | sort | uniq | wc -l\n[4] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep "hash://" | sort | uniq | wc -l\n[5] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep -v "hash://" | sort | uniq | wc -l<\/p>\n\nThis work is funded in part by grant NSF OAC 1839201 from the National Science Foundation.<\/p>"]}more » « less
