An overlooked oxidation mechanism of toluene: computational predictions and experimental validations.

Secondary organic aerosols (SOAs) influence the Earth's climate and threaten human health. Aromatic hydrocarbons (AHs) are major precursors for SOA formation in the urban atmosphere. However, the revealed oxidation mechanism dramatically underestimates the contribution of AHs to SOA formation, strongly suggesting the importance of seeking additional oxidation pathways for SOA formation. Using toluene, the most abundant AHs, as a model system and the combination of quantum chemical method and field observations based on advanced mass spectrometry, we herein demonstrate that the second-generation oxidation of AHs can form novel epoxides (TEPOX) with high yield. Such TEPOX can further react with H2SO4 or HNO3 in the aerosol phase to form less-volatile compounds including novel non-aromatic and ring-retaining organosulfates or organonitrates through reactive uptakes, providing new candidates of AH-derived organosulfates or organonitrates for future ambient observation. With the newly revealed mechanism, the chemistry-aerosol box modeling revealed that the SOA yield of toluene oxidation can reach up to 0.35, much higher than 0.088 based on the original mechanism under the conditions of pH = 2 and 0.1 ppbv NO. This study opens a route for the formation of reactive uptake SOA precursors from AHs and significantly fills the current knowledge gap for SOA formation in the urban atmosphere.

Molecular rearrangement of bicyclic peroxy radicals is a key route to aerosol from aromatics.

The oxidation of aromatics contributes significantly to the formation of atmospheric aerosol. Using toluene as an example, we demonstrate the existence of a molecular rearrangement channel in the oxidation mechanism. Based on both flow reactor experiments and quantum chemical calculations, we show that the bicyclic peroxy radicals (BPRs) formed in OH-initiated aromatic oxidation are much less stable than previously thought, and in the case of the toluene derived ipso-BPRs, lead to aerosol-forming low-volatility products with up to 9 oxygen atoms on sub-second timescales. Similar results are predicted for ipso-BPRs formed from many other aromatic compounds. This reaction class is likely a key route for atmospheric aerosol formation, and including the molecular rearrangement of BPRs may be vital for accurate chemical modeling of the atmosphere.

A modelling study of OH, NO3 and H2SO4 in 2007-2018 at SMEAR II, Finland: analysis of long-term trends.

Major atmospheric oxidants (OH, O3 and NO3) dominate the atmospheric oxidation capacity, while H2SO4 is considered as a main driver for new particle formation. Although numerous studies have investigated the long-term trend of ozone in Europe, the trends of OH, NO3 and H2SO4 at specific sites are to a large extent unknown. The one-dimensional model SOSAA has been applied in several studies at the SMEAR II station and has been validated by measurements in several projects. Here, we applied the SOSAA model for the years 2007-2018 to simulate the atmospheric chemical components, especially the atmospheric oxidants OH and NO3, as well as H2SO4 at SMEAR II. The simulations were evaluated with observations from several shorter and longer campaigns at SMEAR II. Our results show that daily OH increased by 2.39% per year and NO3 decreased by 3.41% per year, with different trends of these oxidants during day and night. On the contrary, daytime sulfuric acid concentrations decreased by 2.78% per year, which correlated with the observed decreasing concentration of newly formed particles in the size range of 3-25 nm with 1.4% per year at SMEAR II during the years 1997-2012. Additionally, we compared our simulated OH, NO3 and H2SO4 concentrations with proxies, which are commonly applied in case a limited number of parameters are measured and no detailed model simulations are available.

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

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/m2. 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/m2. Hence, while HOM SOA contributes to climate cooling, NPF can result in climate warming over the Boreal forest.

Robust metric for quantifying the importance of stochastic effects on nanoparticle growth.

Comprehensive representation of nanoparticle dynamics is necessary for understanding nucleation and growth phenomena. This is critical in atmospheric physics, as airborne particles formed from vapors have significant but highly uncertain effects on climate. While the vapor-particle mass exchange driving particle growth can be described by a macroscopic, continuous substance for large enough particles, the growth dynamics of the smallest nanoparticles involve stochastic fluctuations in particle size due to discrete molecular collision and decay processes. To date, there have been no generalizable methods for quantifying the particle size regime where the discrete effects become negligible and condensation models can be applied. By discrete simulations of sub-10 nm particle populations, we demonstrate the importance of stochastic effects in the nanometer size range. We derive a novel, theory-based, simple and robust metric for identifying the exact sizes where these effects cannot be omitted for arbitrary molecular systems. The presented metric, based on examining the second- and first-order derivatives of the particle size distribution function, is directly applicable to experimental size distribution data. This tool enables quantifying the onset of condensational growth without prior information on the properties of the vapors and particles, thus allowing robust experimental resolving of nanoparticle formation physics.