Characterization of Organic Aerosol across the Global Remote Troposphere: A comparison of ATom measurements and global chemistry models

Abstract

Abstract. The spatial distribution and properties of submicron organic aerosols (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very little data has been available, and where OA predictions from AeroCom Phase II global models span a factor of 400–1000, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC8 aircraft as part of the Atmospheric Tomography (ATom) mission during the northern hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the summer and over the regions influenced by the biomass burning from Africa (up to 10 μg sm−3). Lower concentrations (~ 0.1–0.3 μg sm−3) are observed in the northern mid- and high-latitudes and very low concentrations (

Investigation of factors controlling PM2.5 variability across the South Korean Peninsula during KORUS-AQ

“…The limitations in reproducing SOA production during the Stagnant period were discussed in detail by Choi et al and are related to incomplete knowledge of the photochemical pathways from which SOA is produced from myriad local gas-phase volatile organic compound (VOC) precursors under the clear skies and stagnant conditions of this period. This is further explored by Nault et al (2018) in an analysis of KORUS-AQ aerosol observations from the NASA DC-8 and is also consistent with previous studies (e.g., Heald et al, 2010 ; Hodzic et al, 2016 , 2020 ; Schroder et al, 2018 ; Woody et al, 2016 ). The underprediction of observed aerosol concentrations during the Transport/Haze period has not been explored in detail, but a combination of factors has been suggested for the aerosol observations involving both transport and enhanced local aerosol production under the cloudy moist conditions during this period ( Kim et al, 2018 ; Peterson et al, 2019 ).…”

“…However, fully representing SOA production in chemical transport models is an ongoing challenge due to the wide variety of potential precursors in the VOC class and the myriad photochemical reaction pathways they undergo ( Hallquist et al, 2009 ; Shrivastava et al, 2017 ). This problem was discussed as it specifically applied to the KORUS-AQ Stagnant period ( Choi et al, 2019 ), with various aspects of the broader challenges explored in numerous prior studies (e.g., Heald et al, 2010 ; Hodzic et al, 2016 , 2020 ; Woody et al, 2016 ; Schroder et al, 2018 ). Here, the GEOS-Chem model underestimated total PM 2.5 during the Stagnant period in SMA, especially from May 20 th –May 22 nd when PM 2.5 exceeded the South Korean air quality standard ( Choi et al, 2019 ).…”

Estimates of Regional Source Contributions to the Asian Tropopause Aerosol Layer Using a Chemical Transport Model

“…We use a factor of 2.1 to convert primary organic carbon simulated by the model to organic aerosol (OA) in the ATAL region. A factor of 2.1 has been used in previous studies of OA using GEOS-Chem (Pai et al, 2019, and references therein), and is close to values obtained from aircraft observations (Hodzic et al, 2019;Schroder et al, 2018). We follow Kim et al (2015) in using the "Simple" scheme to simulate anthropogenic SOA, as the other schemes in GEOS-Chem greatly underestimate this component (e.g., Shah et al, 2019).…”

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

“…However, substantial uncertainties persist in our predictive and quantitative understanding of SOA. Global models that use simplified treatments of SOA often do not capture key features in SOA formation and evolution (e.g., Hodzic et al, 2020; Kelly et al, 2018; Myhre et al, 2009; Spracklen et al, 2011; Tsigaridis et al, 2014). Results from 34 global models included in the AEROCom‐II intercomparison depict variabilities in SOA annual chemical production by over an order of magnitude (20–120 Tg/yr), and estimates of global SOA lifetime span a wide range (2.4–14.8 days) (Heald et al, 2011; Hodzic et al, 2016; Kanakidou et al, 2005; Kelly et al, 2018; Tsigaridis et al, 2014; Shrivastava et al, 2015).…”