Quantifying the effect of SVOC condensation on cloud droplet number in different airmass types

Abstract

<p>Clouds are made of droplets that arise from the activation of suitable aerosol particles (termed cloud condensation nuclei, CCN). In the activation process, water vapor saturation ratio exceeds a critial ratio enabling CCN runaway-growth to cloud droplet sizes. The number concentration of cloud droplets (CDNC) is highly dependent on the aerosol population properties (size distribution and composition), relative humidity, and the vertical wind component. While the activation of CCN consisting of non-volatile particulate matter is fairly well understood, the same process involving semi-volatile organic vapors (SVOCs) has received less attention despite their significant presence in ambient air. A recent cloud parcel modeling study shows substanial CDNC enhancement due to SVOC condensation (Topping <em>et al</em>., 2013). Surprisingly, the topic has not been widely investigated nor the results replicated with other cloud parcel models (CPM). Thus, in the current study we seek to quantify the CDNC enhancement by SVOC condensation using a recently developed CPM framework (Lowe <em>et al.</em>, 2020, <em>in prep</em>.). Moreover, the CPM initialization is performed, for the first time, with state-of-the art measurement data including measured SVOC data for multiple airmass types.</p><p>Here, the CPM, which uses spectral microphysics for the simulation of CCN activation and hydrometeor growth, also includes a SVOC condensation equation analogous to those of water vapor. Equilibrium initialization of the SVOC volatility basis set (VBS) partitioning coefficients is performed iteratively, and constrained by the organic to inorganic ratio in the particle phase determined by ambient measurements performed at the Chacaltaya Global Atmospheric Watch (GAW) Station located at 5240 m a.s.l. in the Bolivian Andes, in spring 2018. The uniquely comprehensive data set recorded, which tracks all of the relevant aerosol population characteristics in near real-time, reveals a high degree of variability in aerosol composition, size distribution and loading depending on the air mass origin. Lagrangian backward simulations during the measurement period at Chacaltaya GAW reveal at least 18 significantly different airmass origins (Aliaga <em>et al.</em>, 2020, <em>in prep.</em>). Such variability served multiple model initialization scenarios for individual case studies. We will show a suite of CDNC enhancements by SVOC condensation under different initialization scenarios actualized in data recorded at Chacaltaya GAW Station, including airmasses originating from the Amazon (biomass burning and biogenic VOCs), Andean plateau (volcanic activity), and La Paz/El Alto metropolitan areas (anthropogenic emissions).</p><p><strong>References:</strong></p><div>Topping, D., Connolly, P. and McFiggans, G., 2013. Cloud droplet number enhanced by co-condensation of organic vapours. <em>Nature Geoscience</em>, <em>6</em>(6), p.443.</div>