Parameterization of size of organic and secondary inorganic aerosol for efficient representation of global aerosol optical properties

Abstract

Abstract. Accurate representation of aerosol optical properties is essential for the modeling and remote sensing of atmospheric aerosols. Although aerosol optical properties are strongly dependent upon the aerosol size distribution, the use of detailed aerosol microphysics schemes in global atmospheric models is inhibited by associated computational demands. Computationally efficient parameterizations for aerosol size are needed. In this study, airborne measurements over the United States (DISCOVER-AQ) and South Korea (KORUS-AQ) are interpreted with a global chemical transport model (GEOS-Chem) to investigate the variation in aerosol size when organic matter (OM) and sulfate–nitrate–ammonium (SNA) are the dominant aerosol components. The airborne measurements exhibit a strong correlation (r=0.83) between dry aerosol size and the sum of OM and SNA mass concentration (MSNAOM). A global microphysical simulation (GEOS-Chem-TOMAS) indicates that MSNAOM and the ratio between the two components (OM/SNA) are the major indicators for SNA and OM dry aerosol size. A parameterization of the dry effective radius (Reff) for SNA and OM aerosol is designed to represent the airborne measurements (R2=0.74; slope = 1.00) and the GEOS-Chem-TOMAS simulation (R2=0.72; slope = 0.81). When applied in the GEOS-Chem high-performance model, this parameterization improves the agreement between the simulated aerosol optical depth (AOD) and the ground-measured AOD from the Aerosol Robotic Network (AERONET; R2 from 0.68 to 0.73 and slope from 0.75 to 0.96). Thus, this parameterization offers a computationally efficient method to represent aerosol size dynamically.

Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter

“…78,79 GEOS-Chem total column AOD is calculated at ambient T, P, and RH with RH dependent aerosol size distributions and optical properties 34,63 and updated parameterized size for inorganic and organic aerosols. 35 We artificially increase simulated AOD by 0.04 globally when calculating geophysical PM 2.5 to address a poorly understood underestimate versus AERONET downwind of sources. Speciated η is calculated by simulated surface concentrations of each species over the total column AOD of each species.…”

“…Despite large spatial gradients of ground-level PM 2.5 , variations of the simulated surface to column relationship are modulated by the covariation extent between total column AOD and surface PM 2.5 , which depends on various factors including vertical distribution, composition- and size-dependent properties including hygroscopicity and extinction cross section, and local meteorological conditions such as relative humidity (RH) and boundary layer (BL) dynamics. − While the total column abundance of aerosol is proportional to surface concentration especially for urban and industrial regions, − vertical stratification resulting from offsetting effects between near-surface emissions versus regional transport − and enhanced aerosol formation over the residual layer at night − further complicates the spatial distribution of the surface to column ratio. With distinct optical and hygroscopic properties among aerosol components, − fine-scale separation of anthropogenic pollution from biomass burning and windblown dust would better represent local mass extinction efficiency and thus the PM 2.5 to AOD relationship. In addition, various studies have identified the importance of meteorological conditions on shaping aerosol vertical profiles. , Regional transport and atmospheric stability not only change elevated concentrations but also modify aerosol composition with more aged contributions aloft, whose extinction is further enhanced by hygroscopic growth with higher RH in the upper BL. − Over mountainous regions, varied concentrations and composition are particularly pronounced due to heterogeneous sources, terrain induced local recirculation by mountain-valley breezes, and day-night shifting residence between the BL and free troposphere. , The vertical stratification of concentration and composition induces a mismatch between surface and elevated extinction, which could exaggerate or reduce the spatial heterogeneity of the simulated surface to column ratio.…”

Global Spatial Variation in the PM2.5 to AOD Relationship Strongly Influenced by Aerosol Composition

“…Emissions from stacks are distributed vertically (Bieser et al, 2011). Diel variation of anthropogenic emissions is included (Li et al, 2023). Resolution-dependent soil NOx, sea salt, biogenic VOC, and natural dust emissions are calculated offline at native meteorological resolution to produce consistent emissions across resolutions (Weng et al, 2020;Meng et al, 2021).…”

“…We estimate organic matter (OM) from primary organic carbon using an OM/OC parameterization (Philip et al, 2014;Canagaratna et al, 2015). For secondary aerosol components, the concentration at 2 m above the surface is used to calculate PM2.5, following Li et al (2023). A 50% reduction of the surface nitrate concentration is applied to account for the longpersisting bias in surface nitrate simulated by GEOS-Chem (Heald et al, 2012;Zhang et al, 2012;Zhai et al, 2021;Miao et al, 2020;Travis et al, 2022) and other models (Zakoura and Pandis, 2018;Shimadera et al, 2014).…”

“…Global RH-dependent aerosol optical properties are based on the Global Aerosol Data Set (GADS) (Kopke P., 1997), as originally implemented by Martin et al (2003), with updates for SNA and OM dry size (Zhu et al, 2023), hygroscopicity (Latimer and Martin, 2019), mineral dust size distribution (Zhang et al, 2013), and absorbing brown carbon (Hammer et al, 2016). We artificially increase simulated AOD by 0.04 globally to address a poorly understood systematic bias.…”