Process-Level Modeling Can Simultaneously Explain Secondary Organic Aerosol Evolution in Chambers and Flow Reactors

Secondary organic aerosol (SOA) data gathered in environmental chambers (ECs) have been used extensively to develop parameters to represent SOA formation and evolution. The EC-based parameters are usually constrained to less than one day of photochemical aging but extrapolated to predict SOA aging over much longer timescales in atmospheric models. Recently, SOA has been increasingly studied in oxidation flow reactors (OFRs) over aging timescales of one to multiple days. However, these OFR data have been rarely used to validate or update the EC-based parameters. The simultaneous use of EC and OFR data is challenging because the processes relevant to SOA formation and evolution proceed over very different timescales, and both reactor types exhibit distinct experimental artifacts. In this work, we show that a kinetic SOA chemistry and microphysics model that accounts for various processes, including wall losses, aerosol phase state, heterogeneous oxidation, oligomerization, and new particle formation, can simultaneously explain SOA evolution in EC and OFR experiments, using a single consistent set of SOA parameters. With α-pinene as an example, we first developed parameters by fitting the model output to the measured SOA mass concentration and oxygen-to-carbon (O:C) ratio from an EC experiment (<1 day of aging). We then used these parameters to simulate SOA formation in OFR experiments and found that the model overestimated SOA formation (by a factor of 3–16) over photochemical ages ranging from 0.4 to 13 days, when excluding the abovementioned processes. By comprehensively accounting for these processes, the model was able to explain the observed evolution in SOA mass, composition (i.e., O:C), and size distribution in the OFR experiments. This work suggests that EC and OFR SOA data can be modeled consistently, and a synergistic use of EC and OFR data can aid in developing more refined SOA parameters for use in atmospheric models

Vapors Are Lost to Walls, Not to Particles on the Wall: Artifact-Corrected Parameters from Chamber Experiments and Implications for Global Secondary Organic Aerosol

Atmospheric models of secondary organic aerosol (OA) (SOA) typically rely on parameters derived from environmental chambers. Chambers are subject to experimental artifacts, including losses of (1) particles to the walls (PWL), (2) vapors to the particles on the wall (V2PWL), and (3) vapors to the wall directly (VWL). We present a method for deriving artifact-corrected SOA parameters and translating these to volatility basis set (VBS) parameters for use in chemical transport models (CTMs). Our process involves combining a box model that accounts for chamber artifacts (Statistical Oxidation Model with a TwO-Moment Aerosol Sectional model (SOM-TOMAS)) with a pseudo-atmospheric simulation to develop VBS parameters that are fit across a range of OA mass concentrations. We found that VWL led to the highest percentage change in chamber SOA mass yields (high NOx: 36–680%; low NOx: 55–250%), followed by PWL (high NOx: 8–39%; low NOx: 10–37%), while the effects of V2PWL are negligible. In contrast to earlier work that assumed that V2PWL was a meaningful loss pathway, we show that V2PWL is an unimportant SOA loss pathway and can be ignored when analyzing chamber data. Using our updated VBS parameters, we found that not accounting for VWL may lead surface-level OA to be underestimated by 24% (0.25 μg m−3) as a global average or up to 130% (9.0 μg m–3) in regions of high biogenic or anthropogenic activity. Finally, we found that accurately accounting for PWL and VWL improves model-measurement agreement for fine mode aerosol mass concentrations (PM2.5) in the GEOS-Chem model

Secondary Organic Aerosol Formation from Volatile Chemical Product Emissions: Model Parameters and Contributions to Anthropogenic Aerosol

Volatile chemical products (VCP) are an increasingly important source of hydrocarbon and oxygenated volatile organic compound (OVOC) emissions to the atmosphere, and these emissions are likely to play an important role as anthropogenic precursors for secondary organic aerosol (SOA). While the SOA from VCP hydrocarbons is often accounted for in models, the formation, evolution, and properties of SOA from VCP OVOCs remain uncertain. We use environmental chamber data and a kinetic model to develop SOA parameters for 10 OVOCs representing glycols, glycol ethers, esters, oxygenated aromatics, and amines. Model simulations suggest that the SOA mass yields for these OVOCs are of the same magnitude as widely studied SOA precursors (e.g., long-chain alkanes, monoterpenes, and single-ring aromatics), and these yields exhibit a linear correlation with the carbon number of the precursor. When combined with emissions inventories for two megacities in the United States (US) and a US-wide inventory, we find that VCP VOCs react with OH to form 0.8–2.5× as much SOA, by mass, as mobile sources. Hydrocarbons (terpenes, branched and cyclic alkanes) and OVOCs (terpenoids, glycols, glycol ethers) make up 60–75 and 25–40% of the SOA arising from VCP use, respectively. This work contributes to the growing body of knowledge focused on studying VCP VOC contributions to urban air pollution

Trends of Full-Volatility Organic Emissions in China from 2005 to 2019 and Their Organic Aerosol Formation Potentials

Emissions of organic compounds have strong influences on the environment. Most previous emission inventories only cover the emissions of particulate organic carbon and nonmethane volatile organic compounds (NMVOC) but neglect the semivolatile and intermediate volatile organic compounds (S/IVOC), which considerably contribute to the organic aerosol (OA) burden. Herein, we developed a full-volatility emission inventory of organic compounds in China from 2005 to 2019 and analyzed the OA formation potential (OAFP) of each volatility bin and source using a two-dimensional volatility basis set (2D-VBS) box model. The emissions of low/extremely low/ultralow VOC (xLVOC) decreased substantially during 2005–2019, while the emissions of SVOC showed significant decline after 2014, mainly because of reduced residential biomass consumption. IVOC and VOC emission amounts in 2019 were similar to those in 2005; however, the major sources of emissions changed substantially. Emissions from volatile chemical products (VCP) increased significantly and became the dominant source of IVOC and VOC emissions. The S/IVOC from VCP contributed 1322 kt of OAFP in 2019, higher than the total anthropogenic xLVOC emissions. Considering the high of S/IVOC, future air pollution control policies should prioritize VCP, residential biomass burning, and diesel vehicles

Trends of Full-Volatility Organic Emissions in China from 2005 to 2019 and Their Organic Aerosol Formation Potentials

Emissions of organic compounds have strong influences on the environment. Most previous emission inventories only cover the emissions of particulate organic carbon and nonmethane volatile organic compounds (NMVOC) but neglect the semivolatile and intermediate volatile organic compounds (S/IVOC), which considerably contribute to the organic aerosol (OA) burden. Herein, we developed a full-volatility emission inventory of organic compounds in China from 2005 to 2019 and analyzed the OA formation potential (OAFP) of each volatility bin and source using a two-dimensional volatility basis set (2D-VBS) box model. The emissions of low/extremely low/ultralow VOC (xLVOC) decreased substantially during 2005–2019, while the emissions of SVOC showed significant decline after 2014, mainly because of reduced residential biomass consumption. IVOC and VOC emission amounts in 2019 were similar to those in 2005; however, the major sources of emissions changed substantially. Emissions from volatile chemical products (VCP) increased significantly and became the dominant source of IVOC and VOC emissions. The S/IVOC from VCP contributed 1322 kt of OAFP in 2019, higher than the total anthropogenic xLVOC emissions. Considering the high of S/IVOC, future air pollution control policies should prioritize VCP, residential biomass burning, and diesel vehicles

Fostering a Holistic Understanding of the Full Volatility Spectrum of Organic Compounds from Benzene Series Precursors through Mechanistic Modeling

A comprehensive understanding of the full volatility spectrum of organic oxidation products from the benzene series precursors is important to quantify the air quality and climate effects of secondary organic aerosol (SOA) and new particle formation (NPF). However, current models fail to capture the full volatility spectrum due to the absence of important reaction pathways. Here, we develop a novel unified model framework, the integrated two-dimensional volatility basis set (I2D-VBS), to simulate the full volatility spectrum of products from benzene series precursors by simultaneously representing first-generational oxidation, multigenerational aging, autoxidation, dimerization, nitrate formation, etc. The model successfully reproduces the volatility and O/C distributions of oxygenated organic molecules (OOMs) as well as the concentrations and the O/C of SOA over wide-ranging experimental conditions. In typical urban environments, autoxidation and multigenerational oxidation are the two main pathways for the formation of OOMs and SOA with similar contributions, but autoxidation contributes more to low-volatility products. NOx can reduce about two-thirds of OOMs and SOA, and most of the extremely low-volatility products compared to clean conditions, by suppressing dimerization and autoxidation. The I2D-VBS facilitates a holistic understanding of full volatility product formation, which helps fill the large gap in the predictions of organic NPF, particle growth, and SOA formation

Heterogeneous Nucleation Drives Particle Size Segregation in Sequential Ozone and Nitrate Radical Oxidation of Catechol

Secondary organic aerosol formation via condensation of organic vapors onto existing aerosol transforms the chemical composition and size distribution of ambient aerosol, with implications for air quality and Earth’s radiative balance. Gas-to-particle conversion is generally thought to occur on a continuum between equilibrium-driven partitioning of semivolatile molecules to the pre-existing mass size distribution and kinetic-driven condensation of low volatility molecules to the pre-existing surface area size distribution. However, we offer experimental evidence in contrast to this framework. When catechol is sequentially oxidized by O3 and NO3 in the presence of (NH4)2SO4 seed particles with a single size mode, we observe a bimodal organic aerosol mass size distribution with two size modes of distinct chemical composition with nitrocatechol from NO3 oxidation preferentially condensing onto the large end of the pre-existing size distribution (∼750 nm). A size-resolved chemistry and microphysics model reproduces the evolution of the two distinct organic aerosol size modesheterogeneous nucleation to an independent, nitrocatechol-rich aerosol phase

Modeling the Formation of Organic Compounds across Full Volatility Ranges and Their Contribution to Nanoparticle Growth in a Polluted Atmosphere

Nanoparticle growth influences atmospheric particles’ climatic effects, and it is largely driven by low-volatility organic vapors. However, the magnitude and mechanism of organics’ contribution to nanoparticle growth in polluted environments remain unclear because current observations and models cannot capture organics across full volatility ranges or track their formation chemistry. Here, we develop a mechanistic model that characterizes the full volatility spectrum of organic vapors and their contributions to nanoparticle growth by coupling advanced organic oxidation modeling and kinetic gas-particle partitioning. The model is applied to Nanjing, a typical polluted city, and it effectively captures the volatility distribution of low-volatility organics (with saturation vapor concentrations 3), thus accurately reproducing growth rates (GRs), with a 4.91% normalized mean bias. Simulations indicate that as particles grow from 4 to 40 nm, the relative fractions of GRs attributable to organics increase from 59 to 86%, with the remaining contribution from H2SO4 and its clusters. Aromatics contribute much to condensable organic vapors (∼37%), especially low-volatility vapors (∼61%), thus contributing the most to GRs (32–46%) as 4–40 nm particles grow. Alkanes also contribute 19–35% of GRs, while biogenic volatile organic compounds contribute minimally (<13%). Our model helps assess the climatic impacts of particles and predict future changes