The role of highly oxygenated organic molecules in the Boreal aerosol-cloud-climate system

Abstract

Over Boreal regions, monoterpenes emitted from the forest are the main precursors for secondary organic aerosol (SOA) formation and the primary driver of the growth of new aerosol particles to climatically important cloud condensation nuclei (CCN). Autoxidation of monoterpenes leads to rapid formation of Highly Oxygenated organic Molecules (HOM). We have developed the first model with near-explicit representation of atmospheric new particle formation (NPF) and HOM formation. The model can reproduce the observed NPF, HOM gas-phase composition and SOA formation over the Boreal forest. During the spring, HOM SOA formation increases the CCN concentration by~10 % and causes a direct aerosol radiative forcing of −0.10 W/m 2. In contrast, NPF reduces the number of CCN at updraft velocities < 0.2 m/s, and causes a direct aerosol radiative forcing of +0.15 W/m 2. Hence, while HOM SOA contributes to climate cooling, NPF can result in climate warming over the Boreal forest.

Aerosol mass yields of selected biogenic volatile organic compounds – a theoretical study with nearly explicit gas-phase chemistry

“…Kinetic PreProcessor (KPP) is used to generate a system of coupled differential equations to solve the gas-phase chemistry schemes (Damian et al, 2002). The peroxy radical autoxidation mechanism (PRAM; Roldin et al, 2019;Qi et al, 2018;Öström et al, 2017), formulated based on the oxidation of monoterpenes as described by Ehn et al (2014), was incorporated alongside MCMv3.3.1. PRAM explicitly describes the formation and evolution of peroxy radicals (RO 2 ) from the ozonolysis and OH oxidation of monoterpenes, driven by subsequent H shifts and O 2 additions.…”

“…The current version of PRAM based on experimental and theoretical studies considers HOM autoxidation for a fraction of the peroxy radicals formed during the ozonolysis of α-pinene and limonene and OH oxidation of α-pinene, β-pinene and limonene. This is achieved by assigning species specific molar yields for the formation of first RO 2 , which subsequently initiates the autoxidation chain (Roldin et al, 2019). Currently, in PRAM maximum first-generation RO 2 yields of 9 % for αpinene ozonolysis, 21.9 % for limonene ozonolysis, 2.5 % for α-pinene + OH, and 1 % for both limonene + OH and β-pinene + OH first-generation products are allowed to initiate autoxidation (Roldin et al, 2019).…”

“…This is achieved by assigning species specific molar yields for the formation of first RO 2 , which subsequently initiates the autoxidation chain (Roldin et al, 2019). Currently, in PRAM maximum first-generation RO 2 yields of 9 % for αpinene ozonolysis, 21.9 % for limonene ozonolysis, 2.5 % for α-pinene + OH, and 1 % for both limonene + OH and β-pinene + OH first-generation products are allowed to initiate autoxidation (Roldin et al, 2019). For β-pinene ozonolysis the molar yield of RO 2 is minor (< 0.1 %) (Roldin et al, 2019;Ehn et al, 2014) and hence not considered in this work.…”

“…Further we study the effect of varying temperature (258.15-313.15 K) and NO concentrations (0-5 ppb) on α-pinene oxidation mass yields. We use the master chemical mechanism (MCMv3.3.1) (Jenkin et al, 1997(Jenkin et al, , 2012(Jenkin et al, , 2015Saunders et al, 2003), a nearly explicit gas-phase chemical mechanism together with peroxy radical autoxidation mechanism (PRAM; Roldin et al, 2019) (PRAM + MCM). The aim is to understand the importance and contribution of peroxy radical autoxidation products to the SOA mass yields from terpenes.…”

PyCHAM: CHemistry with Aerosol Microphysics in Python

“…Allying PyCHAM with chamber measurements allows quantification of unknown parameters, such as branching ratios for oxidation schemes (Chen & Griffin, 2005). Although several box models have already been published (Pierce et al, 2008;Roldin et al, 2019Roldin et al, , 2014Sunol, Charan, & Seinfeld, 2018), PyCHAM is novel in its ease of accessibility and utility. To the best of our knowledge, PyBOX (Topping, Connolly, & Reid, 2018), which formed the basis of PyCHAM, and AtChem (Borońska et al, 2019), are the only other open source box models with graphical user interfaces.…”