Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns
<p>Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are major contributors to fine particulate matter. Predicting concentrations of these species is complicated by the cascade of processes that control their abundance, including emissions, chemistry, thermodynamic partitionin...
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Copernicus Publications
2025-01-01
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| Series: | Atmospheric Chemistry and Physics |
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| author | O. G. Norman C. L. Heald C. L. Heald C. L. Heald S. Bililign P. Campuzano-Jost H. Coe H. Coe M. N. Fiddler J. R. Green J. L. Jimenez K. Kaiser J. Liao J. Liao A. M. Middlebrook B. A. Nault B. A. Nault B. A. Nault J. B. Nowak J. Schneider A. Welti |
| author_facet | O. G. Norman C. L. Heald C. L. Heald C. L. Heald S. Bililign P. Campuzano-Jost H. Coe H. Coe M. N. Fiddler J. R. Green J. L. Jimenez K. Kaiser J. Liao J. Liao A. M. Middlebrook B. A. Nault B. A. Nault B. A. Nault J. B. Nowak J. Schneider A. Welti |
| author_sort | O. G. Norman |
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| description | <p>Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are major contributors to fine particulate matter. Predicting concentrations of these species is complicated by the cascade of processes that control their abundance, including emissions, chemistry, thermodynamic partitioning, and removal. In this study, we use 11 flight campaigns to evaluate the GEOS-Chem model performance for SNA. Across all the campaigns, the model performance is best for sulfate (<span class="inline-formula"><i>R</i><sup>2</sup></span> <span class="inline-formula">=</span> 0.51; normalized mean bias (NMB) <span class="inline-formula">=</span> 0.11) and worst for nitrate (<span class="inline-formula"><i>R</i><sup>2</sup>=0.22</span>; NMB <span class="inline-formula">=</span> 1.76), indicating substantive model deficiencies in the nitrate simulation. Thermodynamic partitioning reproduces the total particulate nitrate well (<span class="inline-formula"><i>R</i><sup>2</sup>=0.79</span>; NMB <span class="inline-formula">=</span> 0.09), but actual partitioning (i.e., <span class="inline-formula"><i>ε</i></span>(NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup><mo>)</mo><mo>=</mo></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="3b35b7ceb952b67a7d90687e397a043a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00001.svg" width="22pt" height="16pt" src="acp-25-771-2025-ie00001.png"/></svg:svg></span></span> NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="78ed0f7e81615226176402cdd6a1afd5"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00002.svg" width="9pt" height="16pt" src="acp-25-771-2025-ie00002.png"/></svg:svg></span></span> <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M11" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="165b352473919034209a9d51d0eaf41d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00003.svg" width="8pt" height="14pt" src="acp-25-771-2025-ie00003.png"/></svg:svg></span></span> TNO<span class="inline-formula"><sub>3</sub></span>) is challenging to assess given the limited sets of full gas- and particle-phase observations needed for ISORROPIA II. In particular, ammonia observations are not often included in aircraft<span id="page772"/> campaigns, and more routine measurements would help constrain sources of SNA model bias. Model performance is sensitive to changes in emissions and dry and wet deposition, with modest improvements associated with the inclusion of different chemical loss and production pathways (i.e., acid uptake on dust, N<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>5</sub></span> uptake, and NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="9f81e901bf06635e082f559a787da68a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00004.svg" width="9pt" height="16pt" src="acp-25-771-2025-ie00004.png"/></svg:svg></span></span> photolysis). However, these sensitivity tests show only modest reduction in the nitrate bias, with no improvement to the model skill (i.e., <span class="inline-formula"><i>R</i><sup>2</sup></span>), implying that more work is needed to improve the description of loss and production of nitrate and SNA as a whole.</p> |
| format | Article |
| id | doaj-art-693a93d6981149afb98c3fe41393434f |
| institution | Kabale University |
| issn | 1680-7316 1680-7324 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj-art-693a93d6981149afb98c3fe41393434f2025-01-21T10:08:14ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242025-01-012577179510.5194/acp-25-771-2025Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaignsO. G. Norman0C. L. Heald1C. L. Heald2C. L. Heald3S. Bililign4P. Campuzano-Jost5H. Coe6H. Coe7M. N. Fiddler8J. R. Green9J. L. Jimenez10K. Kaiser11J. Liao12J. Liao13A. M. Middlebrook14B. A. Nault15B. A. Nault16B. A. Nault17J. B. Nowak18J. Schneider19A. Welti20Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USADepartment of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USADepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USAnow at: Department of Environmental Systems Science, ETH Zurich, Zurich, SwitzerlandDepartment of Physics, North Carolina Agricultural and Technical State University, Greensboro, NC, USADepartment of Chemistry and Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado, Boulder, CO, USADepartment of Earth and Environmental Sciences, University of Manchester, Oxford Road, Manchester, M13 1QD, UKNational Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester, M13 1QD, UKDepartment of Chemistry, North Carolina Agricultural and Technical State University, Greensboro, NC, USADepartment of Environmental Sciences & Engineering, University of North Carolina, Chapel Hill, NC, USADepartment of Chemistry and Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado, Boulder, CO, USAParticle Chemistry Department, Max Planck Institute for Chemistry, Mainz, GermanyNASA Goddard Space Flight Center, Greenbelt, MD, USAGoddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, College Park, MD, USANOAA Chemical Sciences Laboratory, Boulder, CO, USADepartment of Chemistry and Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado, Boulder, CO, USADepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA, USANASA Langley Research Center, Hampton, VA, USAParticle Chemistry Department, Max Planck Institute for Chemistry, Mainz, GermanyFinnish Meteorological Institute, Helsinki, Finland<p>Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are major contributors to fine particulate matter. Predicting concentrations of these species is complicated by the cascade of processes that control their abundance, including emissions, chemistry, thermodynamic partitioning, and removal. In this study, we use 11 flight campaigns to evaluate the GEOS-Chem model performance for SNA. Across all the campaigns, the model performance is best for sulfate (<span class="inline-formula"><i>R</i><sup>2</sup></span> <span class="inline-formula">=</span> 0.51; normalized mean bias (NMB) <span class="inline-formula">=</span> 0.11) and worst for nitrate (<span class="inline-formula"><i>R</i><sup>2</sup>=0.22</span>; NMB <span class="inline-formula">=</span> 1.76), indicating substantive model deficiencies in the nitrate simulation. Thermodynamic partitioning reproduces the total particulate nitrate well (<span class="inline-formula"><i>R</i><sup>2</sup>=0.79</span>; NMB <span class="inline-formula">=</span> 0.09), but actual partitioning (i.e., <span class="inline-formula"><i>ε</i></span>(NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup><mo>)</mo><mo>=</mo></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="3b35b7ceb952b67a7d90687e397a043a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00001.svg" width="22pt" height="16pt" src="acp-25-771-2025-ie00001.png"/></svg:svg></span></span> NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="78ed0f7e81615226176402cdd6a1afd5"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00002.svg" width="9pt" height="16pt" src="acp-25-771-2025-ie00002.png"/></svg:svg></span></span> <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M11" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="165b352473919034209a9d51d0eaf41d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00003.svg" width="8pt" height="14pt" src="acp-25-771-2025-ie00003.png"/></svg:svg></span></span> TNO<span class="inline-formula"><sub>3</sub></span>) is challenging to assess given the limited sets of full gas- and particle-phase observations needed for ISORROPIA II. In particular, ammonia observations are not often included in aircraft<span id="page772"/> campaigns, and more routine measurements would help constrain sources of SNA model bias. Model performance is sensitive to changes in emissions and dry and wet deposition, with modest improvements associated with the inclusion of different chemical loss and production pathways (i.e., acid uptake on dust, N<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>5</sub></span> uptake, and NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="9f81e901bf06635e082f559a787da68a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-771-2025-ie00004.svg" width="9pt" height="16pt" src="acp-25-771-2025-ie00004.png"/></svg:svg></span></span> photolysis). However, these sensitivity tests show only modest reduction in the nitrate bias, with no improvement to the model skill (i.e., <span class="inline-formula"><i>R</i><sup>2</sup></span>), implying that more work is needed to improve the description of loss and production of nitrate and SNA as a whole.</p>https://acp.copernicus.org/articles/25/771/2025/acp-25-771-2025.pdf |
| spellingShingle | O. G. Norman C. L. Heald C. L. Heald C. L. Heald S. Bililign P. Campuzano-Jost H. Coe H. Coe M. N. Fiddler J. R. Green J. L. Jimenez K. Kaiser J. Liao J. Liao A. M. Middlebrook B. A. Nault B. A. Nault B. A. Nault J. B. Nowak J. Schneider A. Welti Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns Atmospheric Chemistry and Physics |
| title | Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns |
| title_full | Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns |
| title_fullStr | Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns |
| title_full_unstemmed | Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns |
| title_short | Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns |
| title_sort | exploring the processes controlling secondary inorganic aerosol evaluating the global geos chem simulation using a suite of aircraft campaigns |
| url | https://acp.copernicus.org/articles/25/771/2025/acp-25-771-2025.pdf |
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