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Title: New SOA Treatments Within the Energy Exascale Earth System Model (E3SM): Strong Production and Sinks Govern Atmospheric SOA Distributions and Radiative Forcing

Abstract

Secondary organic aerosols (SOA) are large contributors to fine particle mass loading and number concentration and interact with clouds and radiation. Several processes affect the formation, chemical transformation, and removal of SOA in the atmosphere. For computational efficiency, global models use simplified SOA treatments, which often do not capture the dynamics of SOA formation. Here we test more complex SOA treatments within the global Energy Exascale Earth System Model (E3SM) to investigate how simulated SOA spatial distributions respond to some of the important but uncertain processes affecting SOA formation, removal, and lifetime. We evaluate model predictions with a suite of surface, aircraft, and satellite observations that span the globe and the full troposphere. Simulations indicate that both a strong production (achieved here by multigenerational aging of SOA precursors that includes moderate functionalization) and a strong sink of SOA (especially in the middle upper troposphere, achieved here by adding particle-phase photolysis) are needed to reproduce the vertical distribution of organic aerosol (OA) measured during several aircraft field campaigns; without this sink, the simulated middle upper tropospheric OA is too large. Our results show that variations in SOA chemistry formulations change SOA wet removal lifetime by a factor of 3 due tomore » changes in horizontal and vertical distributions of SOA. In all the SOA chemistry formulations tested here, an efficient chemical sink, that is, particle-phase photolysis, was needed to reproduce the aircraft measurements of OA at high altitudes. Globally, SOA removal rates by photolysis are equal to the wet removal sink, and photolysis decreases SOA lifetimes from 10 to ~3 days. A recent review of multiple field studies found no increase in net OA formation over and downwind biomass burning regions, so we also tested an alternative, empirical SOA treatment that increases primary organic aerosol (POA) emissions near source region and converts POA to SOA with an aging time scale of 1 day. Although this empirical treatment performs surprisingly well in simulating OA loadings near the surface, it overestimates OA loadings in the middle and upper troposphere compared to aircraft measurements, likely due to strong convective transport to high altitudes where wet removal is weak. The default improved model formulation (multigenerational aging with moderate fragmentation and photolysis) performs much better than the empirical treatment in these regions. Differences in SOA treatments greatly affect the SOA direct radiative effect, which ranges from -0.65 (moderate fragmentation and photolysis) to -2 W m-2 (moderate fragmentation without photolysis). Notably, most SOA formulations predict similar global indirect forcing of SOA calculated as the difference in cloud forcing between present-day and preindustrial simulations.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [2]; ORCiD logo [2];  [4]; ORCiD logo [5]; ORCiD logo [5]; ORCiD logo [6]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [9]; ORCiD logo [10]; ORCiD logo [11]
  1. Pacific Northwest National Laboratory Richland WA USA, Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Jiangsu Provincial Collaborative Innovation Center of Climate Change Nanjing University Nanjing China
  2. Pacific Northwest National Laboratory Richland WA USA
  3. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing China
  4. TOFWERK Thun Switzerland
  5. Cooperative Institute for Research in Environmental Sciences (CIRES) &, Department of Chemistry University of Colorado Boulder Boulder CO USA
  6. Department of Environmental Toxicology University of California Davis CA USA
  7. Los Alamos National Laboratory Earth Systems Observations (EES‐14) Los Alamos NM USA
  8. Lawrence Livermore National Laboratory Livermore CA USA
  9. John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA
  10. Particle Chemistry, Biogeochemistry and Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany
  11. Particle Chemistry, Biogeochemistry and Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany, Leibniz Institute for Tropospheric Research (TROPOS) Leipzig Germany
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES); National Aeronautics and Space Administration (NASA)
OSTI Identifier:
1734410
Alternate Identifier(s):
OSTI ID: 1755166; OSTI ID: 1786720; OSTI ID: 1885107
Report Number(s):
PNNL-SA-156400; LLNL-JRNL-823088
Journal ID: ISSN 1942-2466; e2020MS002266
Grant/Contract Number:  
AC05-76RL01830; NNX15AH33A; 80NSSC19K0124; SC0014620; AC52‐07NA27344; AC52-07NA27344; AC06‐76RL01830
Resource Type:
Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Name: Journal of Advances in Modeling Earth Systems Journal Volume: 12 Journal Issue: 12; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; secondary organic aerosol; photolytic removal; fragmentation reaction

Citation Formats

Lou, Sijia, Shrivastava, Manish, Easter, Richard C., Yang, Yang, Ma, Po‐Lun, Wang, Hailong, Cubison, Michael J., Campuzano‐Jost, Pedro, Jimenez, Jose L., Zhang, Qi, Rasch, Philip J., Shilling, John E., Zelenyuk, Alla, Dubey, Manvendra, Cameron‐Smith, Philip, Martin, Scot T., Schneider, Johannes, and Schulz, Christiane. New SOA Treatments Within the Energy Exascale Earth System Model (E3SM): Strong Production and Sinks Govern Atmospheric SOA Distributions and Radiative Forcing. United States: N. p., 2020. Web. doi:10.1029/2020MS002266.
Lou, Sijia, Shrivastava, Manish, Easter, Richard C., Yang, Yang, Ma, Po‐Lun, Wang, Hailong, Cubison, Michael J., Campuzano‐Jost, Pedro, Jimenez, Jose L., Zhang, Qi, Rasch, Philip J., Shilling, John E., Zelenyuk, Alla, Dubey, Manvendra, Cameron‐Smith, Philip, Martin, Scot T., Schneider, Johannes, & Schulz, Christiane. New SOA Treatments Within the Energy Exascale Earth System Model (E3SM): Strong Production and Sinks Govern Atmospheric SOA Distributions and Radiative Forcing. United States. https://doi.org/10.1029/2020MS002266
Lou, Sijia, Shrivastava, Manish, Easter, Richard C., Yang, Yang, Ma, Po‐Lun, Wang, Hailong, Cubison, Michael J., Campuzano‐Jost, Pedro, Jimenez, Jose L., Zhang, Qi, Rasch, Philip J., Shilling, John E., Zelenyuk, Alla, Dubey, Manvendra, Cameron‐Smith, Philip, Martin, Scot T., Schneider, Johannes, and Schulz, Christiane. Mon . "New SOA Treatments Within the Energy Exascale Earth System Model (E3SM): Strong Production and Sinks Govern Atmospheric SOA Distributions and Radiative Forcing". United States. https://doi.org/10.1029/2020MS002266.
@article{osti_1734410,
title = {New SOA Treatments Within the Energy Exascale Earth System Model (E3SM): Strong Production and Sinks Govern Atmospheric SOA Distributions and Radiative Forcing},
author = {Lou, Sijia and Shrivastava, Manish and Easter, Richard C. and Yang, Yang and Ma, Po‐Lun and Wang, Hailong and Cubison, Michael J. and Campuzano‐Jost, Pedro and Jimenez, Jose L. and Zhang, Qi and Rasch, Philip J. and Shilling, John E. and Zelenyuk, Alla and Dubey, Manvendra and Cameron‐Smith, Philip and Martin, Scot T. and Schneider, Johannes and Schulz, Christiane},
abstractNote = {Secondary organic aerosols (SOA) are large contributors to fine particle mass loading and number concentration and interact with clouds and radiation. Several processes affect the formation, chemical transformation, and removal of SOA in the atmosphere. For computational efficiency, global models use simplified SOA treatments, which often do not capture the dynamics of SOA formation. Here we test more complex SOA treatments within the global Energy Exascale Earth System Model (E3SM) to investigate how simulated SOA spatial distributions respond to some of the important but uncertain processes affecting SOA formation, removal, and lifetime. We evaluate model predictions with a suite of surface, aircraft, and satellite observations that span the globe and the full troposphere. Simulations indicate that both a strong production (achieved here by multigenerational aging of SOA precursors that includes moderate functionalization) and a strong sink of SOA (especially in the middle upper troposphere, achieved here by adding particle-phase photolysis) are needed to reproduce the vertical distribution of organic aerosol (OA) measured during several aircraft field campaigns; without this sink, the simulated middle upper tropospheric OA is too large. Our results show that variations in SOA chemistry formulations change SOA wet removal lifetime by a factor of 3 due to changes in horizontal and vertical distributions of SOA. In all the SOA chemistry formulations tested here, an efficient chemical sink, that is, particle-phase photolysis, was needed to reproduce the aircraft measurements of OA at high altitudes. Globally, SOA removal rates by photolysis are equal to the wet removal sink, and photolysis decreases SOA lifetimes from 10 to ~3 days. A recent review of multiple field studies found no increase in net OA formation over and downwind biomass burning regions, so we also tested an alternative, empirical SOA treatment that increases primary organic aerosol (POA) emissions near source region and converts POA to SOA with an aging time scale of 1 day. Although this empirical treatment performs surprisingly well in simulating OA loadings near the surface, it overestimates OA loadings in the middle and upper troposphere compared to aircraft measurements, likely due to strong convective transport to high altitudes where wet removal is weak. The default improved model formulation (multigenerational aging with moderate fragmentation and photolysis) performs much better than the empirical treatment in these regions. Differences in SOA treatments greatly affect the SOA direct radiative effect, which ranges from -0.65 (moderate fragmentation and photolysis) to -2 W m-2 (moderate fragmentation without photolysis). Notably, most SOA formulations predict similar global indirect forcing of SOA calculated as the difference in cloud forcing between present-day and preindustrial simulations.},
doi = {10.1029/2020MS002266},
journal = {Journal of Advances in Modeling Earth Systems},
number = 12,
volume = 12,
place = {United States},
year = {2020},
month = {12}
}

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