Simulating secondary organic aerosol formation using the volatility basis-set approach in a chemical transport model

Lane, Timothy E.; Donahue, Neil M.; Pandis, Spyros Ν.

doi:10.1016/j.atmosenv.2008.06.026

Cited by 306 publications

(355 citation statements)

References 87 publications

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“…3370 A. P. : an efficient module to compute volatility and oxygen content approach, semi-volatile primary emissions, chemical aging, and SOA formation were unified within a common framework that is ideally suited for regional and global chemical modeling. Since 2006, many regional (Lane et al, 2008;Murphy and Pandis, 2009;Tsimpidi et al, , 2011Ahmadov et al, 2012;Athanasopoulou et al, 2013;Koo et al, 2014;Fountoukis et al, 2014;Ciarelli et al, 2017;Gao et al, 2017) and global (Pye and Seinfeld, 2010;Jathar et al, 2011;Jo et al, 2013;Tsimpidi et al, 2014;Hodzic et al, 2016) modeling studies have used the VBS to account for the semi-volatile nature and chemical aging of organic compounds, demonstrating improvements in reproducing the OA budget and its chemical resolution.…”

Section: Introductionmentioning

confidence: 99%

ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model

et al. 2018

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Abstract. A new module, ORACLE 2-D, simulating organic aerosol formation and evolution in the atmosphere has been developed and evaluated. The module calculates the concentrations of surrogate organic species in two-dimensional space defined by volatility and oxygen-to-carbon ratio. It is implemented into the EMAC global chemistry-climate model, and a comprehensive evaluation of its performance is conducted using an aerosol mass spectrometer (AMS) factor analysis dataset derived from almost all major field campaigns that took place globally during the period 2001-2010. ORACLE 2-D uses a simple photochemical aging scheme that efficiently simulates the net effects of fragmentation and functionalization of the organic compounds. The module predicts not only the mass concentration of organic aerosol (OA) components, but also their oxidation state (in terms of O : C), which allows for their classification into primary OA (POA, chemically unprocessed), fresh secondary OA (SOA, low oxygen content), and aged SOA (highly oxygenated). The explicit simulation of chemical OA conversion from freshly emitted compounds to a highly oxygenated state during photochemical aging enables the tracking of hygroscopicity changes in OA that result from these reactions. OR-ACLE 2-D can thus compute the ability of OA particles to act as cloud condensation nuclei and serves as a tool to quantify the climatic impact of OA.

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Section: Introductionmentioning

confidence: 99%

ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model

et al. 2018

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“…Most box (0-D) and large-scale (3-D) models represent SOA production from the gas-phase oxidation of certain VOCs (large alkanes, aromatics, isoprene and terpenes) to yield 2-4 low-volatility products that partition into the particle phase (Odum et al, 1996;Carlton et al, 2010;Lane et al, 2008). Laboratory chamber data provide the basic information on which these SOA formation models are built.…”

Section: Introductionmentioning

confidence: 99%

“…Pye and Seinfeld (2010) represented the same pathway through a single-step reaction that reduced the volatility of the vapors by 2 orders of magnitude. Lane et al (2008) and Baek et al (2011) modeled ageing of semi-volatile SOA vapors by assuming that each reaction with the OH radical resulted in progressively lower volatility products. While such schemes have the potential to improve model-measurement comparisons, they have at least three major drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

et al. 2015

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Abstract. Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multigenerational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air quality model. In the SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory smog chamber data for each precursor/compound class. SOM was installed in the UCD/CIT model, which simulated air quality over 2-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-tocarbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of organic aerosol.

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“…We investigate here the fundamental aspects of this growth mechanism and we contrast it to the irreversible diffusion-limited condensation case. These two approaches have been used in regional and global chemical transport models to describe the formation of SOA (Lane et al 2008;Spracklen et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Diffusion-Limited Versus Quasi-Equilibrium Aerosol Growth

Zhang

Pandis

Seinfeld

2012

Aerosol Science and Technology

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Condensation of gas-phase material onto particulate matter is the predominant route by which atmospheric aerosols evolve. The traditional approach to representing formation of secondary organic aerosols (SOAs) is to assume instantaneous partitioning equilibrium of semivolatile organic compounds between gas and particle phases. Growth occurs as the vapor concentration of the species increases owing to gas-phase chemistry. The fundamental mathematical basis of such a condensation growth mechanism (quasi-equilibrium growth) has been lacking. Analytical solutions for the evolution of an organic aerosol size distribution undergoing quasi-equilibrium growth and irreversible diffusion-limited growth are obtained for open and closed systems. The quasiequilibrium growth emerges as a limiting case for semivolatile species condensation when the rate of change of the ambient vapor concentration is slow compared with the rate of establishment of local gas-aerosol equilibrium. The results suggest that the growth mechanism in a particular situation might be inferred from the characteristics of the evolving size distribution. In certain conditions, a bimodal size distribution can occur during the condensation of a single species on an initially unimodal distribution.

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Simulating secondary organic aerosol formation using the volatility basis-set approach in a chemical transport model

Cited by 306 publications

References 87 publications

ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model

ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model

Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

Diffusion-Limited Versus Quasi-Equilibrium Aerosol Growth

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