ACS Publications. Most Trusted. Most Cited. Most Read
Historical Trends of Biogenic SOA Tracers in an Ice Core from Kamchatka Peninsula
My Activity

Figure 1Loading Img
    Letter

    Historical Trends of Biogenic SOA Tracers in an Ice Core from Kamchatka Peninsula
    Click to copy article linkArticle link copied!

    View Author Information
    Institute of Low Temperature Science, Hokkaido University, Sapporo 060-0819, Japan
    LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    § Biosphere-Atmosphere Interactions Group, Climate and Space Sciences and Engineering (CLaSP), University of Michigan, Ann Arbor, Michigan 48109-2143, United States
    *Phone: +86-10-8201-3200. E-mail: [email protected]
    Other Access OptionsSupporting Information (1)

    Environmental Science & Technology Letters

    Cite this: Environ. Sci. Technol. Lett. 2016, 3, 10, 351–358
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.estlett.6b00275
    Published August 30, 2016
    Copyright © 2016 American Chemical Society

    Abstract

    Click to copy section linkSection link copied!
    Abstract Image

    Biogenic secondary organic aerosol (SOA) is ubiquitous in the Earth’s atmosphere, influencing climate and air quality. However, the historical trend of biogenic SOA is not well known. Here, we report for the first time the major isoprene- and monoterpene-derived SOA tracers preserved in an ice core from the Kamchatka Peninsula. Significant variations are recorded during the past 300 years with lower concentrations in the early-to-middle 19th century and higher concentrations in the preindustrial period and the present day. We discovered that isoprene SOA tracers were more abundant in the preindustrial period than the present day, while monoterpene SOA tracers stay almost unchanged. The causes of the observed variability are complex, depending on atmospheric circulation, changes in emissions, and other factors such as tropospheric oxidative capacity. Our data presents an unprecedented opportunity to shed light on the formation, evolution, and fate of atmospheric aerosols and to constrain the uncertainties associated with modeling their atmospheric concentrations.

    Copyright © 2016 American Chemical Society

    Read this article

    To access this article, please review the available access options below.

    Get instant access

    Purchase Access

    Read this article for 48 hours. Check out below using your ACS ID or as a guest.

    Recommended

    Access through Your Institution

    You may have access to this article through your institution.

    Your institution does not have access to this content. Add or change your institution or let them know you’d like them to include access.

    Supporting Information

    Click to copy section linkSection link copied!

    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.estlett.6b00275.

    • Detailed methodology, four supplementary tables (Table S1−S4) and two supplementary figures (Figure S1−S2). (PDF)

    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

    Cited By

    Click to copy section linkSection link copied!
    Citation Statements
    Explore this article's citation statements on scite.ai

    This article is cited by 11 publications.

    1. Yunjiang Zhang, Jie Fang, Qingxiao Meng, Xinlei Ge, Hasna Chebaicheb, Olivier Favez, Jean-Eudes Petit. An Ensemble Machine Learning Approach for Predicting Sources of Organic Aerosols Measured by Aerosol Mass Spectrometry. ACS ES&T Air 2025, 2 (3) , 378-385. https://doi.org/10.1021/acsestair.4c00262
    2. Siobhán Johnson, Roseanne Smith, Elizabeth Thomas, Chiara Giorio. Method for Quantification of Fatty Acids in Ice Cores and Sea-Ice Cores Using Liquid Chromatography High-Resolution Mass Spectrometry. ACS Measurement Science Au 2024, Article ASAP.
    3. Emilia E. Bushrod, Elizabeth R. Thomas, Alexander Zherebker, Chiara Giorio. Novel Method to Quantify Trace Amounts of Isoprene and Monoterpene Secondary Organic Aerosol-Markers in Antarctic Ice. Environmental Science & Technology 2024, 58 (48) , 21177-21185. https://doi.org/10.1021/acs.est.4c09985
    4. Alexander L. Vogel, Anja Lauer, Ling Fang, Katarzyna Arturi, Franziska Bachmeier, Kaspar R. Daellenbach, Timon Käser, Athanasia Vlachou, Veronika Pospisilova, Urs Baltensperger, Imad El Haddad, Margit Schwikowski, Saša Bjelić. A Comprehensive Nontarget Analysis for the Molecular Reconstruction of Organic Aerosol Composition from Glacier Ice Cores. Environmental Science & Technology 2019, 53 (21) , 12565-12575. https://doi.org/10.1021/acs.est.9b03091
    5. Tianqu Cui, Hilary S. Green, Paul W. Selleck, Zhenfa Zhang, Rachel E. O’Brien, Avram Gold, Melita Keywood, Jesse H. Kroll, Jason D. Surratt. Chemical Characterization of Isoprene- and Monoterpene-Derived Secondary Organic Aerosol Tracers in Remote Marine Aerosols over a Quarter Century. ACS Earth and Space Chemistry 2019, 3 (6) , 935-946. https://doi.org/10.1021/acsearthspacechem.9b00061
    6. Johanna Schäfer, Anja Beschnitt, François Burgay, Thomas Singer, Margit Schwikowski, Thorsten Hoffmann. Method development and application for the analysis of chiral organic marker species in ice cores. Atmospheric Measurement Techniques 2025, 18 (2) , 421-430. https://doi.org/10.5194/amt-18-421-2025
    7. Anja Beschnitt, Margit Schwikowski, Thorsten Hoffmann. Towards comprehensive non-target screening using heart-cut two-dimensional liquid chromatography for the analysis of organic atmospheric tracers in ice cores. Journal of Chromatography A 2022, 1661 , 462706. https://doi.org/10.1016/j.chroma.2021.462706
    8. Amy C.F. King, Chiara Giorio, Eric Wolff, Elizabeth Thomas, Ornela Karroca, Marco Roverso, Margit Schwikowski, Andrea Tapparo, Andrea Gambaro, Markus Kalberer. A new method for the determination of primary and secondary terrestrial and marine biomarkers in ice cores using liquid chromatography high-resolution mass spectrometry. Talanta 2019, 194 , 233-242. https://doi.org/10.1016/j.talanta.2018.10.042
    9. Fahmida Parvin, Osamu Seki, Koji Fujita, Yoshinori Iizuka, Sumito Matoba, Takuto Ando, Ken Sawada. Assessment for paleoclimatic utility of biomass burning tracers in SE-Dome ice core, Greenland. Atmospheric Environment 2019, 196 , 86-94. https://doi.org/10.1016/j.atmosenv.2018.10.012
    10. Dušan Materić, Elke Ludewig, Kangming Xu, Thomas Röckmann, Rupert Holzinger. Brief communication: Analysis of organic matter in surface snow by PTR-MS – implications for dry deposition dynamics in the Alps. The Cryosphere 2019, 13 (1) , 297-307. https://doi.org/10.5194/tc-13-297-2019
    11. Chiara Giorio, Natalie Kehrwald, Carlo Barbante, Markus Kalberer, Amy C.F. King, Elizabeth R. Thomas, Eric W. Wolff, Piero Zennaro. Prospects for reconstructing paleoenvironmental conditions from organic compounds in polar snow and ice. Quaternary Science Reviews 2018, 183 , 1-22. https://doi.org/10.1016/j.quascirev.2018.01.007

    Environmental Science & Technology Letters

    Cite this: Environ. Sci. Technol. Lett. 2016, 3, 10, 351–358
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.estlett.6b00275
    Published August 30, 2016
    Copyright © 2016 American Chemical Society

    Article Views

    718

    Altmetric

    -

    Citations

    Learn about these metrics

    Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

    Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

    The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.