scholarly journals Using GECKO-A to derive mechanistic understanding of SOA formation from the ubiquitous but understudied camphene

2020 ◽  
Author(s):  
Isaac Kwadjo Afreh ◽  
Bernard Aumont ◽  
Marie Camredon ◽  
Kelley Claire Barsanti
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Measurement Model ◽  
Oxidation Products ◽  
Chemical Mechanism ◽  
Mechanistic Study ◽  
Phase Reaction ◽  
Particle Phase ◽  
Atmospheric Conditions ◽  
Model Simulations

Abstract. Camphene, a dominant monoterpene emitted from both biogenic and pyrogenic sources, has been significantly understudied, particularly in regard to secondary organic aerosol (SOA) formation. When camphene represents a significant fraction of emissions, the lack of model parameterizations for camphene can result in inadequate representation of gas-phase chemistry and underprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α-pinene and limonene; and to predict SOA mass formation and composition based on gas/particle partitioning theory. The model simulations represented observed trends in published gas-phase reaction pathways and SOA yields well under chamber-relevant photooxidation and dark ozonolysis conditions. For photooxidation conditions, 70 % of the simulated α-pinene oxidation products remained in the gas phase compared to 50 % for limonene; supporting model predictions and observations of limonene having higher SOA yields than α-pinene under equivalent conditions. The top 10 simulated particle-phase products in the α-pinene and limonene simulations represented 37–50 % of the SOA mass formed and 6–27 % of the hydrocarbon mass reacted. To facilitate comparison of camphene with α-pinene and limonene, model simulations were run under idealized atmospheric conditions, wherein the gas-phase oxidant levels were controlled. Metrics for comparison included: gas-phase reactivity profiles, time-evolution of SOA mass and yields, and physicochemical property distributions of gas- and particle-phase products. The controlled-reactivity simulations demonstrated that: (1) in the early stages of oxidation, camphene is predicted to form very low volatility products, lower than α-pinene and limonene, which condense at low mass loadings; and (2) the final simulated SOA yield for camphene (46 %) was relatively high, in between α-pinene (25 %) and limonene (74 %). A 50 / 50 (α-pinene / limonene) mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions, and published SOA parameterizations for α-pinene and limonene. Using the 50 / 50 surrogate mixture to represent camphene increased predicted SOA mass by 43–50 % for black spruce and by 56–108 % for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation provides an opportunity for future measurement-model comparisons and lays the foundation for developing chemical mechanism and SOA parameterizations for camphene that are suitable for air quality modeling.

scholarly journals Using GECKO-A to derive mechanistic understanding of secondary organic aerosol formation from the ubiquitous but understudied camphene

2021 ◽  
Vol 21 (14) ◽  
pp. 11467-11487
Author(s):  
Isaac Kwadjo Afreh ◽  
Bernard Aumont ◽  
Marie Camredon ◽  
Kelley Claire Barsanti
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Mechanistic Study ◽  
Phase Reaction ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Model Simulations ◽  
Chemical Mechanisms

Abstract. Camphene, a dominant monoterpene emitted from both biogenic and pyrogenic sources, has been significantly understudied, particularly in regard to secondary organic aerosol (SOA) formation. When camphene represents a significant fraction of emissions, the lack of model parameterizations for camphene can result in inadequate representation of gas-phase chemistry and underprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α-pinene and limonene, as well as to predict SOA mass formation and composition based on gas/particle partitioning theory. The model simulations represented observed trends in published gas-phase reaction pathways and SOA yields well under chamber-relevant photooxidation and dark ozonolysis conditions. For photooxidation conditions, 70 % of the simulated α-pinene oxidation products remained in the gas phase compared to 50 % for limonene, supporting model predictions and observations of limonene having higher SOA yields than α-pinene under equivalent conditions. The top 10 simulated particle-phase products in the α-pinene and limonene simulations represented 37 %–50 % of the SOA mass formed and 6 %–27 % of the hydrocarbon mass reacted. To facilitate comparison of camphene with α-pinene and limonene, model simulations were run under idealized atmospheric conditions, wherein the gas-phase oxidant levels were controlled, and peroxy radicals reacted equally with HO2 and NO. Metrics for comparison included gas-phase reactivity profiles, time-evolution of SOA mass and yields, and physicochemical property distributions of gas- and particle-phase products. The controlled-reactivity simulations demonstrated that (1) in the early stages of oxidation, camphene is predicted to form very low-volatility products, lower than α-pinene and limonene, which condense at low mass loadings; and (2) the final simulated SOA yield for camphene (46 %) was relatively high, in between α-pinene (25 %) and limonene (74 %). A 50 % α-pinene + 50 % limonene mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions and published SOA parameterizations for α-pinene and limonene. Using the 50/50 surrogate mixture to represent camphene increased predicted SOA mass by 43 %–50 % for black spruce and by 56 %–108 % for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation highlights opportunities for future measurement–model comparisons and lays a foundation for developing chemical mechanisms and SOA parameterizations for camphene that are suitable for air quality modeling.

scholarly journals Chemical aging of <i>m</i>-xylene secondary organic aerosol: laboratory chamber study

2011 ◽  
Vol 11 (9) ◽  
pp. 24969-25010 ◽  
Author(s):  
C. L. Loza ◽  
P. S. Chhabra ◽  
L. D. Yee ◽  
J. S. Craven ◽  
R. C. Flagan ◽  
...  
Keyword(s):  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Ionization Mass ◽  
Phase Reaction ◽  
Particle Phase ◽  
Chemical Aging ◽  
Volatile Products ◽  
Fragmentation Chemistry

Abstract. Secondary organic aerosol (SOA) can reside in the atmosphere for a week or more. While its initial formation from the gas-phase oxidation of volatile organic compounds tends to take place in the first few hours after emission, SOA can continue to evolve chemically over its atmospheric lifetime. Simulating this chemical aging over an extended time in the laboratory has proven to be challenging. We present here a procedure for studying SOA aging in laboratory chambers that is applied to achieve 36 h of oxidation. The formation and evolution of SOA from the photooxidation of m-xylene under low-NOx conditions and in the presence of either neutral or acidic seed particles is studied. In SOA aging, increasing molecular functionalization leads to less volatile products and an increase in SOA mass, whereas gas-phase or particle-phase fragmentation chemistry results in more volatile products and a loss of SOA. The challenge is to discern from measured chamber variables the extent to which these processes are important for a given SOA system. In the experiments conducted, m-xylene SOA mass increased over the initial 12-h of photooxidation and decreased beyond that time. The oxidation of the SOA, as manifested in the O:C elemental ratio and fraction of organic ion detected at m/z 44 measured by the Aerodyne aerosol mass spectrometer, decreased during the first 5 h of reaction, reached a minimum, and then increased continuously until the 36 h termination. This behavior is consistent with an initial period in which, as the mass of SOA increases, products of higher volatility partition to the aerosol phase, followed by an aging period in which gas- and particle-phase reaction products become increasingly more oxidized. After about 12–13 h, the SOA mass reaches a maximum and decreases, suggesting the existence of fragmentation chemistry. When irradiation is stopped 12.4 h into one experiment, and OH generation ceases, no loss of SOA is observed, indicating that the loss of SOA is either light- or OH-induced. Chemical ionization mass spectrometry measurements of low-volatility m-xylene oxidation products exhibit behavior indicative of continuous photooxidation chemistry. A condensed chemical mechanism of m-xylene oxidation under low-NOx conditions is capable of reproducing the general behavior of gas-phase evolution observed here. Moreover, order of magnitude analysis of the mechanism suggests that gas-phase OH reaction of low volatility SOA precursors is the dominant pathway of aging in the m-xylene system although OH reaction with particle surfaces cannot be ruled out.

scholarly journals Kinetic modeling of formation and evaporation of secondary organic aerosol from NO<sub>3</sub> oxidation of pure and mixed monoterpenes

2020 ◽  
Vol 20 (24) ◽  
pp. 15513-15535
Author(s):  
Thomas Berkemeier ◽  
Masayuki Takeuchi ◽  
Gamze Eris ◽  
Nga L. Ng
Keyword(s):  
Kinetic Model ◽  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Phase Reaction ◽  
Particle Phase ◽  
Environmental Chamber ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. Organic aerosol constitutes a major fraction of the global aerosol burden and is predominantly formed as secondary organic aerosol (SOA). Environmental chambers have been used extensively to study aerosol formation and evolution under controlled conditions similar to the atmosphere, but quantitative prediction of the outcome of these experiments is generally not achieved, which signifies our lack in understanding of these results and limits their portability to large-scale models. In general, kinetic models employing state-of-the-art explicit chemical mechanisms fail to describe the mass concentration and composition of SOA obtained from chamber experiments. Specifically, chemical reactions including the nitrate radical (NO3) are a source of major uncertainty for assessing the chemical and physical properties of oxidation products. Here, we introduce a kinetic model that treats gas-phase chemistry, gas–particle partitioning, particle-phase oligomerization, and chamber vapor wall loss and use it to describe the oxidation of the monoterpenes α-pinene and limonene with NO3. The model can reproduce aerosol mass and nitration degrees in experiments using either pure precursors or their mixtures and infers volatility distributions of products, branching ratios of reactive intermediates and particle-phase reaction rates. The gas-phase chemistry in the model is based on the Master Chemical Mechanism (MCM) but trades speciation of single compounds for the overall ability of quantitatively describing SOA formation by using a lumped chemical mechanism. The complex branching into a multitude of individual products in MCM is replaced in this model with product volatility distributions and detailed peroxy (RO2) and alkoxy (RO) radical chemistry as well as amended by a particle-phase oligomerization scheme. The kinetic parameters obtained in this study are constrained by a set of SOA formation and evaporation experiments conducted in the Georgia Tech Environmental Chamber (GTEC) facility. For both precursors, we present volatility distributions of nitrated and non-nitrated reaction products that are obtained by fitting the kinetic model systematically to the experimental data using a global optimization method, the Monte Carlo genetic algorithm (MCGA). The results presented here provide new mechanistic insight into the processes leading to formation and evaporation of SOA. Most notably, the model suggests that the observed slow evaporation of SOA could be due to reversible oligomerization reactions in the particle phase. However, the observed non-linear behavior of precursor mixtures points towards a complex interplay of reversible oligomerization and kinetic limitations of mass transport in the particle phase, which is explored in a model sensitivity study. The methodologies described in this work provide a basis for quantitative analysis of multi-source data from environmental chamber experiments but also show that a large data pool is needed to fully resolve uncertainties in model parameters.

scholarly journals Kinetic modelling of formation and evaporation of SOA from NO<sub>3</sub> oxidation of pure and mixed monoterpenes

2020 ◽  
Author(s):  
Thomas Berkemeier ◽  
Masayuki Takeuchi ◽  
Gamze Eris ◽  
Nga L. Ng
Keyword(s):  
Kinetic Model ◽  
Gas Phase ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Phase Reaction ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Environmental Chamber ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. Organic aerosol constitutes a major fraction of the global aerosol burden and is predominantly formed as secondary organic aerosol (SOA). Environmental chambers have been used extensively to study aerosol formation and evolution under controlled conditions similar to the atmosphere, but quantitative prediction of the outcome of these experiments is generally not achieved, which signifies our lack in understanding of these results and limits their portability to large scale models. In general, kinetic models employing state-of-the-art explicit chemical mechanisms fail to describe the mass concentration and composition of SOA obtained from chamber experiments. Specifically, chemical reactions involving nitrate radical (NO3) oxidation of volatile organic compounds (VOCs) are a source of major uncertainty for assessing the chemical and physical properties of oxidation products. Here, we introduce a kinetic model that treats gas-phase chemistry, gas-particle partitioning, particle-phase oligomerization, and chamber wall loss and use it to describe the oxidation of the monoterpenes α-pinene and limonene with NO3. The model can reproduce aerosol mass and nitration degrees in experiments using either pure precursors or their mixtures and infers volatility distributions of products, branching ratios of reactive intermediates as well as particle-phase reaction rates. The gas-phase chemistry in the model is based on the Master Chemical Mechanism (MCM), but trades speciation of single compounds for the overall ability of quantitatively describing SOA formation by using a lumped chemical mechanism. The complex branching into a multitude of individual products in MCM is replaced in this model with product volatility distributions, detailed peroxy (RO2) and alkoxy (RO) radical chemistry and amended by a particle-phase oligomerization scheme. The kinetic parameters obtained in this study are constrained by a set of SOA formation and evaporation experiments conducted in the Georgia Tech Environmental Chamber (GTEC) facility. For both precursors, we present volatility distributions of nitrated and non-nitrated reaction products that are obtained by fitting the kinetic model systematically to the experimental data using a global optimization method, the Monte Carlo Genetic Algorithm (MCGA). The results presented here provide new mechanistic insight into the processes leading to formation and evaporation of SOA. Most notably, much of the non-linear behavior of precursor mixtures can be understood by RO2 fate and reversible oligomerization reactions in the particle phase, but some effects could be accredited to kinetic limitations of mass transport in the particle phase. The methodologies described in this work provide a basis for quantitative analysis of multi-source data from environmental chamber experiments with manageable computational effort.

Kinetic and mechanistic study of the gas-phase reaction of CxF2x+1CH CH2 (x=1, 2, 3, 4 and 6) with O3 under atmospheric conditions

Chemosphere ◽  
2018 ◽  
Vol 201 ◽  
pp. 318-327
Author(s):  
A. Soto ◽  
B. Ballesteros ◽  
E. Jiménez ◽  
M. Antiñolo ◽  
E. Martínez ◽  
...  
Keyword(s):  
Gas Phase ◽  
Mechanistic Study ◽  
Phase Reaction ◽  
Atmospheric Conditions ◽  
Gas Phase Reaction

scholarly journals Evaluation of the chemical composition of gas- and particle-phase products of aromatic oxidation

2020 ◽  
Vol 20 (16) ◽  
pp. 9783-9803
Author(s):  
Archit Mehra ◽  
Yuwei Wang ◽  
Jordan E. Krechmer ◽  
Andrew Lambe ◽  
Francesca Majluf ◽  
...  
Keyword(s):  
Gas Phase ◽  
Mass Spectrometer ◽  
Urban Areas ◽  
Minor Component ◽  
Proton Transfer Reaction ◽  
Chemical Mechanism ◽  
Particle Phase ◽  
Experimental Conditions ◽  
Radical Oxidation ◽  
Product Ions

Abstract. Aromatic volatile organic compounds (VOCs) are key anthropogenic pollutants emitted to the atmosphere and are important for both ozone and secondary organic aerosol (SOA) formation in urban areas. Recent studies have indicated that aromatic hydrocarbons may follow previously unknown oxidation chemistry pathways, including autoxidation that can lead to the formation of highly oxidised products. In this study we evaluate the gas- and particle-phase ions measured by online mass spectrometry during the hydroxyl radical oxidation of substituted C9-aromatic isomers (1,3,5-trimethylbenzene, 1,2,4-trimethylbenzene, propylbenzene and isopropylbenzene) and a substituted polyaromatic hydrocarbon (1-methylnaphthalene) under low- and medium-NOx conditions. A time-of-flight chemical ionisation mass spectrometer (ToF-CIMS) with iodide–anion ionisation was used with a filter inlet for gases and aerosols (FIGAERO) for the detection of products in the particle phase, while a Vocus proton-transfer-reaction mass spectrometer (Vocus-PTR-MS) was used for the detection of products in the gas phase. The signal of product ions observed in the mass spectra were compared for the different precursors and experimental conditions. The majority of mass spectral product signal in both the gas and particle phases comes from ions which are common to all precursors, though signal distributions are distinct for different VOCs. Gas- and particle-phase composition are distinct from one another. Ions corresponding to products contained in the near-explicit gas phase Master Chemical Mechanism (MCM version 3.3.1) are utilised as a benchmark of current scientific understanding, and a comparison of these with observations shows that the MCM is missing a range of highly oxidised products from its mechanism. In the particle phase, the bulk of the product signal from all precursors comes from ring scission ions, a large proportion of which are more oxidised than previously reported and have undergone further oxidation to form highly oxygenated organic molecules (HOMs). Under the perturbation of OH oxidation with increased NOx, the contribution of HOM-ion signals to the particle-phase signal remains elevated for more substituted aromatic precursors. Up to 43 % of product signal comes from ring-retaining ions including HOMs; this is most important for the more substituted aromatics. Unique products are a minor component in these systems, and many of the dominant ions have ion formulae concurrent with other systems, highlighting the challenges in utilising marker ions for SOA.

ChemInform Abstract: A MECHANISTIC STUDY OF THE ION-MOLECULE GAS-PHASE REACTION: CH3+ + CH4 → CH3CH2+ + H2

1982 ◽  
Vol 13 (44) ◽  
Author(s):  
R. A. POIRIER ◽  
E. CONSTANTIN ◽  
J. CH. ABBE ◽  
M. R. PETERSON ◽  
I. G. CSIZMADIA
Keyword(s):  
Gas Phase ◽  
Mechanistic Study ◽  
Phase Reaction ◽  
Gas Phase Reaction

A mechanistic study of the ion—molecule gas-phase reaction: CH+3 + CH4 → CH3CH+2 + H2

1982 ◽  
Vol 88 (3-4) ◽  
pp. 343-355 ◽  
Author(s):  
Raymond A. Poirier ◽  
Emilia Constantin ◽  
Jean Ch. Abbé ◽  
Michael R. Peterson ◽  
Imre G. Csizmadia
Keyword(s):  
Gas Phase ◽  
Mechanistic Study ◽  
Phase Reaction ◽  
Gas Phase Reaction

scholarly journals Formation of Highly Oxygenated Low-Volatility Products from Cresol Oxidation

2016 ◽  
Author(s):  
Rebecca H. Schwantes ◽  
Katherine A. Schilling ◽  
Renee C. McVay ◽  
Hanna Lignell ◽  
Matthew M. Coggon ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Phase ◽  
Ring Opening ◽  
Chemical Ionization ◽  
First Generation ◽  
Direct Analysis ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Ionization Mass ◽  
Particle Phase

Abstract. Hydroxyl radical (OH) oxidation of toluene produces the ring-retaining products cresol and benzaldehyde, and the ring-opening products bicyclic intermediate compounds and epoxides. Here, first- and later-generation OH oxidation products from cresol and benzaldehyde are identified in laboratory chamber experiments. For benzaldehyde, first-generation ring-retaining products are identified, but later-generation products are not detected. For cresol, low-volatility (saturation mass concentration, C* ~ 3.5 × 104–7.7 × 10−3 μg m−3) first- and later-generation ring-retaining products are identified. Subsequent OH addition to the aromatic ring of o-cresol leads to compounds such as hydroxy, dihydroxy, and trihydroxy methyl benzoquinones and dihydroxy, trihydroxy, tetrahydroxy, and pentahydroxy toluenes. These products are detected in the gas phase by chemical ionization mass spectrometry (CIMS) and in the particle phase using offline direct analysis in real time mass spectrometry (DART-MS). Our data suggest that the yield of trihydroxy toluene from dihydroxy toluene is substantial. While an exact yield cannot be reported as authentic standards are unavailable, we find that a yield for trihydroxy toluene from dihydroxy toluene of ~ 0.7 (equal to the yield of dihydroxy toluene from o-cresol) is consistent with experimental results for o-cresol oxidation under low-NO conditions. These results suggest that even though the cresol pathway accounts for only ~ 20 % of the oxidation products of toluene, it is the source of a significant fraction (~ 20–40 %) of toluene secondary organic aerosol (SOA) due to the formation of low-volatility products.

scholarly journals Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets

2015 ◽  
Vol 15 (14) ◽  
pp. 8077-8100 ◽  
Author(s):  
K. P. Wyche ◽  
P. S. Monks ◽  
K. L. Smallbone ◽  
J. F. Hamilton ◽  
M. R. Alfarra ◽  
...  
Keyword(s):  
Phase Composition ◽  
Dimension Reduction ◽  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Ambient Air ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Holistic View

Abstract. Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.

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