scholarly journals RH-dependent organic aerosol thermodynamics via an efficient reduced-complexity model

2019 ◽  
Author(s):  
Kyle Gorkowski ◽  
Thomas C. Preston ◽  
Andreas Zuend
Keyword(s):  
Relative Humidity ◽  
Molar Mass ◽  
Cloud Condensation Nuclei ◽  
Organic Aerosol ◽  
Basis Set ◽  
Organic Mixture ◽  
Alpha Pinene ◽  
Ideal Mixing ◽  
Wide Range ◽  
Reduced Complexity

Abstract. Water plays an essential role in aerosol chemistry, gas-particle partitioning, and particle viscosity, but it is typically omitted in thermodynamic models describing the mixing within organic aerosol phases and the partitioning of semivolatile organics. In this study, we introduce the Binary Activity Thermodynamics (BAT) model, a water-sensitive, reduced-complexity model treating the non-ideal mixing of water and organics. The BAT model can process different levels of physicochemical mixture information enabling its application in the thermodynamic aerosol treatment within chemical transport models, the evaluation of humidity effects in environmental chamber studies, and the analysis of field observations. It is capable of using organic structure information including O:C, H:C, molar mass, and vapor pressure, which can be derived from identified compounds or estimated from bulk aerosol properties. A key feature of the BAT model is predicting the extent of liquid-liquid phase separation occurring within aqueous mixtures containing hydrophobic organics. This is crucial to simulating the abrupt change in water uptake behavior of moderately hygroscopic organics at high relative humidity, which is essential for capturing the correct behavior of organic aerosols serving as cloud condensation nuclei. For gas-particle partitioning predictions, we complement a Volatility Basis Set (VBS) approach with the BAT model to account for non-ideality and liquid-liquid equilibrium effects. To improve the computational efficiency of this approach, we trained two neural networks; the first for the prediction of aerosol water content at given relative humidity, and the second for the partitioning of semivolatile components. The integrated VBS + BAT model is benchmarked against high-fidelity molecular-level gas-particle equilibrium calculations based on the AIOMFAC model. Organic aerosol systems derived from alpha-pinene or isoprene oxidation are used for comparison. Predicted organic mass concentrations agree within less than a 5 % error in the isoprene case, which is a significant improvement over a traditional VBS implementation. In the case of the alpha-pinene system, the error is less than 2 % up to a relative humidity of 94 %, with larger errors past that point. The goal of the BAT model is to represent the bulk O:C and molar mass dependencies of a wide range of water-organic mixtures to a reasonable degree of accuracy. In this context, we discuss that the reduced-complexity effort may be poor at representing a specific binary water-organic mixture perfectly. However, the averaging effects of our reduced-complexity model become more representative when the mixture diversity increases in terms of organic functionality and number of components.

scholarly journals Relative-humidity-dependent organic aerosol thermodynamics via an efficient reduced-complexity model

2019 ◽  
Vol 19 (21) ◽  
pp. 13383-13407 ◽  
Author(s):  
Kyle Gorkowski ◽  
Thomas C. Preston ◽  
Andreas Zuend
Keyword(s):  
Relative Humidity ◽  
Molar Mass ◽  
Cloud Condensation Nuclei ◽  
Organic Aerosol ◽  
Basis Set ◽  
Aqueous Mixtures ◽  
Organic Mixture ◽  
Organic Mixtures ◽  
Wide Range ◽  
Reduced Complexity

Abstract. Water plays an essential role in aerosol chemistry, gas–particle partitioning, and particle viscosity, but it is typically omitted in thermodynamic models describing the mixing within organic aerosol phases and the partitioning of semivolatile organics. In this study, we introduce the Binary Activity Thermodynamics (BAT) model, a water-sensitive reduced-complexity model treating the nonideal mixing of water and organics. The BAT model can process different levels of physicochemical mixture information enabling its application in the thermodynamic aerosol treatment within chemical transport models, the evaluation of humidity effects in environmental chamber studies, and the analysis of field observations. It is capable of using organic structure information including O:C, H:C, molar mass, and vapor pressure, which can be derived from identified compounds or estimated from bulk aerosol properties. A key feature of the BAT model is predicting the extent of liquid–liquid phase separation occurring within aqueous mixtures containing hydrophobic organics. This is crucial to simulating the abrupt change in water uptake behavior of moderately hygroscopic organics at high relative humidity, which is essential for capturing the correct behavior of organic aerosols serving as cloud condensation nuclei. For gas–particle partitioning predictions, we complement a volatility basis set (VBS) approach with the BAT model to account for nonideality and liquid–liquid equilibrium effects. To improve the computational efficiency of this approach, we trained two neural networks; the first for the prediction of aerosol water content at given relative humidity, and the second for the partitioning of semivolatile components. The integrated VBS + BAT model is benchmarked against high-fidelity molecular-level gas–particle equilibrium calculations based on the AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficient) model. Organic aerosol systems derived from α-pinene or isoprene oxidation are used for comparison. Predicted organic mass concentrations agree within less than a 5 % error in the isoprene case, which is a significant improvement over a traditional VBS implementation. In the case of the α-pinene system, the error is less than 2 % up to a relative humidity of 94 %, with larger errors past that point. The goal of the BAT model is to represent the bulk O:C and molar mass dependencies of a wide range of water–organic mixtures to a reasonable degree of accuracy. In this context, we discuss that the reduced-complexity effort may be poor at representing a specific binary water–organic mixture perfectly. However, the averaging effects of our reduced-complexity model become more representative when the mixture diversity increases in terms of organic functionality and number of components.

scholarly journals The sensitivity of secondary organic aerosol component partitioning to the predictions of component properties – Part 1: A systematic evaluation of some available estimation techniques

2010 ◽  
Vol 10 (21) ◽  
pp. 10255-10272 ◽  
Author(s):  
G. McFiggans ◽  
D. O. Topping ◽  
M. H. Barley
Keyword(s):  
Molar Mass ◽  
Estimation Method ◽  
Organic Aerosol ◽  
Systematic Evaluation ◽  
Complex Behaviour ◽  
Organic Mixture ◽  
Number Of Components ◽  
Activity Coefficient Model ◽  
Highly Sensitive ◽  
Volatile Organic

Abstract. A large number of calculations of the absorptive partitioning of organic compounds have been made using a number of methods to predict the component vapour pressures, p0, and activity coefficients, γi, required in the calculations. The sensitivities of the predictions in terms of the condensed component masses, volatility, O:C ratio, molar mass and functionality distributions to the choice of p0 and γi models and to the number of components to represent the organic mixture have been systematically compared. The condensed component mass was found to be highly sensitive to the vapour pressure model, and less sensitive to both the activity coefficient model and the number of components used to represent the mixture although the sensitivity to the change in property estimation method increased substantially with increased simplification in the treatment of the organic mixture. This was a general finding and was also clearly evident in terms of the predicted component functionality, O:C ratio, molar mass and volatility distributions of the condensed organic components. Within the limitations of the study, this clearly demonstrates the requirement for more accurate representation of the p0 and γi of the semi-volatile organic proxy components used in simplified models as the degree of simplification increases. This presents an interesting paradox, since such reduction in complexity necessarily leads to divergence from the complex behaviour of real multicomponent atmospheric aerosol.

scholarly journals Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

2017 ◽  
Vol 10 (6) ◽  
pp. 2333-2363 ◽  
Author(s):  
Khairunnisa Yahya ◽  
Timothy Glotfelty ◽  
Kai Wang ◽  
Yang Zhang ◽  
Athanasios Nenes
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Cloud Condensation Nuclei ◽  
Surface Ozone ◽  
Cloud Droplet ◽  
Organic Aerosol ◽  
Basis Set ◽  
Aerosol Formation ◽  
Radiation Processes ◽  
Aerosol Activation

Abstract. Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem) version 3.7.1. The existing Volatility Basis Set (VBS) treatments for organic aerosol (OA) formation in WRF/Chem are improved by considering the following: the secondary OA (SOA) formation from semi-volatile primary organic aerosol (POA), a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010) are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex) campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05) and the VBS SOA module with semivolatile POA treatment, 25 % fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07) used, CB05 gives the best performance for surface ozone and PM2. 5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA) compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC) predictions (normalized mean biases from −40.8 % to a range of −34.6 to −27.7 %), with large differences between CB05–CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation parameterization based on the Fountoukis and Nenes (2005) series reduces the large negative CDNC bias associated with the default Abdul Razzak and Ghan (2000) parameterization from −35.4 % to a range of −0.8 to 7.1 %. However, it increases the errors due to overpredictions of CDNC, mainly over the northeastern US. This work indicates a need to improve other aerosol–cloud–radiation processes in the model, such as the spatial distribution of aerosol optical depth and cloud condensation nuclei, in order to further improve CDNC predictions.

scholarly journals Volatility of organic aerosol and its components in the megacity of Paris

2016 ◽  
Vol 16 (4) ◽  
pp. 2013-2023 ◽  
Author(s):  
Andrea Paciga ◽  
Eleni Karnezi ◽  
Evangelia Kostenidou ◽  
Lea Hildebrandt ◽  
Magda Psichoudaki ◽  
...  
Keyword(s):  
Organic Aerosol ◽  
Basis Set ◽  
Transfer Model ◽  
Collaborative Project ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Combining Data ◽  
Wide Range ◽  
Order Of Magnitude ◽  
Effective Saturation

Abstract. Using a mass transfer model and the volatility basis set, we estimate the volatility distribution for the organic aerosol (OA) components during summer and winter in Paris, France as part of the collaborative project MEGAPOLI. The concentrations of the OA components as a function of temperature were measured combining data from a thermodenuder and an aerosol mass spectrometer (AMS) with Positive Matrix Factorization (PMF) analysis. The hydrocarbon-like organic aerosol (HOA) had similar volatility distributions for the summer and winter campaigns with half of the material in the saturation concentration bin of 10 µg m−3 and another 35–40 % consisting of low and extremely low volatility organic compounds (LVOCs with effective saturation concentrations C* of 10−3–0.1 µg m−3 and ELVOCs C* less or equal than 10−4 µg m−3, respectively). The winter cooking OA (COA) was more than an order of magnitude less volatile than the summer COA. The low-volatility oxygenated OA (LV-OOA) factor detected in the summer had the lowest volatility of all the derived factors and consisted almost exclusively of ELVOCs. The volatility for the semi-volatile oxygenated OA (SV-OOA) was significantly higher than that of the LV-OOA, containing both semi-volatile organic components (SVOCs with C* in the 1–100 µg m−3 range) and LVOCs. The oxygenated OA (OOA) factor in winter consisted of SVOCs (45 %), LVOCs (25 %) and ELVOCs (30 %). The volatility of marine OA (MOA) was higher than that of the other factors containing around 60 % SVOCs. The biomass burning OA (BBOA) factor contained components with a wide range of volatilities with significant contributions from both SVOCs (50 %) and LVOCs (30 %). Finally, combining the bulk average O : C ratios and volatility distributions of the various factors, our results are placed into the two-dimensional volatility basis set (2D-VBS) framework. The OA factors cover a broad spectrum of volatilities with no direct link between the average volatility and average O : C of the OA components.

scholarly journals The sensitivity of secondary organic aerosol component partitioning to the predictions of component properties – Part 1: A systematic evaluation of some available estimation techniques

2010 ◽  
Vol 10 (6) ◽  
pp. 15379-15415 ◽  
Author(s):  
G. McFiggans ◽  
D. O. Topping ◽  
M. H. Barley
Keyword(s):  
Molar Mass ◽  
Estimation Method ◽  
Organic Aerosol ◽  
Systematic Evaluation ◽  
Complex Behaviour ◽  
Organic Mixture ◽  
Number Of Components ◽  
Activity Coefficient Model ◽  
Highly Sensitive ◽  
Volatile Organic

Abstract. A large number of calculations of the absorptive partitioning of organic compounds have been made using a number of methods to predict the component vapour pressures, p0, and activity coefficients, γi, required in the calculations. The sensitivities of the predictions in terms of the condensed component masses, volatility, O:C ratio, molar mass and functionality distributions to the choice of p0 and γi models and to the number of components to represent the organic mixture have been systematically compared. The condensed component mass was found to be highly sensitive to the vapour pressure model, and less sensitive to both the activity coefficient model and the number of components used to represent the mixture although the sensitivity to the change in property estimation method increased substantially with increased simplification in the treatment of the organic mixture. This was a general finding and was also clearly evident in terms of the predicted component functionality, O:C ratio, molar mass and volatility distributions of the condensed organic components. Within the limitations of the study, this clearly demonstrates the requirement for more accurate representation of the p0 and γi of the semi-volatile organic proxy components used in simplified models as the degree of simplification increases. This presents an interesting paradox, since such reduction in complexity necessarily leads to divergence from the complex behaviour of real multicomponent atmospheric aerosol.

scholarly journals New representation of water activity based on a single solute specific constant to parameterize the hygroscopic growth of aerosols in atmospheric models

2012 ◽  
Vol 12 (12) ◽  
pp. 5429-5446 ◽  
Author(s):  
S. Metzger ◽  
B. Steil ◽  
L. Xu ◽  
J. E. Penner ◽  
J. Lelieveld
Keyword(s):  
Relative Humidity ◽  
Water Activity ◽  
Atmospheric Chemistry ◽  
Reference Model ◽  
Climate Modeling ◽  
Cloud Condensation Nuclei ◽  
Hygroscopic Growth ◽  
Wide Range ◽  
Kohler Theory ◽  
Key Factor

Abstract. Water activity is a key factor in aerosol thermodynamics and hygroscopic growth. We introduce a new representation of water activity (aw), which is empirically related to the solute molality (μs) through a single solute specific constant, νi. Our approach is widely applicable, considers the Kelvin effect and covers ideal solutions at high relative humidity (RH), including cloud condensation nuclei (CCN) activation. It also encompasses concentrated solutions with high ionic strength at low RH such as the relative humidity of deliquescence (RHD). The constant νi can thus be used to parameterize the aerosol hygroscopic growth over a wide range of particle sizes, from nanometer nucleation mode to micrometer coarse mode particles. In contrast to other aw-representations, our νi factor corrects the solute molality both linearly and in exponent form x · ax. We present four representations of our basic aw-parameterization at different levels of complexity for different aw-ranges, e.g. up to 0.95, 0.98 or 1. νi is constant over the selected aw-range, and in its most comprehensive form, the parameterization describes the entire aw range (0–1). In this work we focus on single solute solutions. νi can be pre-determined with a root-finding method from our water activity representation using an aw−μs data pair, e.g. at solute saturation using RHD and solubility measurements. Our aw and supersaturation (Köhler-theory) results compare well with the thermodynamic reference model E-AIM for the key compounds NaCl and (NH4)2SO4 relevant for CCN modeling and calibration studies. Envisaged applications include regional and global atmospheric chemistry and climate modeling.

scholarly journals Modeling the gas-particle partitioning of secondary organic aerosol: the importance of liquid-liquid phase separation

2012 ◽  
Vol 12 (9) ◽  
pp. 3857-3882 ◽  
Author(s):  
A. Zuend ◽  
J. H. Seinfeld
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Relative Humidity ◽  
Organic Compounds ◽  
Organic Aerosol ◽  
Liquid Phase Separation ◽  
Organic Loading ◽  
Computational Costs ◽  
Ideal Mixing ◽  
Liquid Liquid Phase Separation

Abstract. The partitioning of semivolatile organic compounds between the gas phase and aerosol particles is an important source of secondary organic aerosol (SOA). Gas-particle partitioning of organic and inorganic species is influenced by the physical state and water content of aerosols, and therefore ambient relative humidity (RH), as well as temperature and organic loading levels. We introduce a novel combination of the thermodynamic models AIOMFAC (for liquid mixture non-ideality) and EVAPORATION (for pure compound vapor pressures) with oxidation product information from the Master Chemical Mechanism (MCM) for the computation of gas-particle partitioning of organic compounds and water. The presence and impact of a liquid-liquid phase separation in the condensed phase is calculated as a function of variations in relative humidity, organic loading levels, and associated changes in aerosol composition. We show that a complex system of water, ammonium sulfate, and SOA from the ozonolysis of α-pinene exhibits liquid-liquid phase separation over a wide range of relative humidities (simulated from 30% to 99% RH). Since fully coupled phase separation and gas-particle partitioning calculations are computationally expensive, several simplified model approaches are tested with regard to computational costs and accuracy of predictions compared to the benchmark calculation. It is shown that forcing a liquid one-phase aerosol with or without consideration of non-ideal mixing bears the potential for vastly incorrect partitioning predictions. Assuming an ideal mixture leads to substantial overestimation of the particulate organic mass, by more than 100% at RH values of 80% and by more than 200% at RH values of 95%. Moreover, the simplified one-phase cases stress two key points for accurate gas-particle partitioning calculations: (1) non-ideality in the condensed phase needs to be considered and (2) liquid-liquid phase separation is a consequence of considerable deviations from ideal mixing in solutions containing inorganic ions and organics that cannot be ignored. Computationally much more efficient calculations relying on the assumption of a complete organic/electrolyte phase separation below a certain RH successfully reproduce gas-particle partitioning in systems in which the average oxygen-to-carbon (O:C) ratio is lower than ~0.6, as in the case of α-pinene SOA, and bear the potential for implementation in atmospheric chemical transport models and chemistry-climate models. A full equilibrium calculation is the method of choice for accurate offline (box model) computations, where high computational costs are acceptable. Such a calculation enables the most detailed predictions of phase compositions and provides necessary information on whether assuming a complete organic/electrolyte phase separation is a good approximation for a given aerosol system. Based on the group-contribution concept of AIOMFAC and O:C ratios as a proxy for polarity and hygroscopicity of organic mixtures, the results from the α-pinene system are also discussed from a more general point of view.

scholarly journals Ozonolysis of α-pinene: parameterization of secondary organic aerosol mass fraction

2007 ◽  
Vol 7 (1) ◽  
pp. 1941-1967 ◽  
Author(s):  
R. K. Pathak ◽  
A. A. Presto ◽  
T. E. Lane ◽  
C. O. Stanier ◽  
N. M. Donahue ◽  
...  
Keyword(s):  
Mass Fraction ◽  
Organic Aerosol ◽  
Basis Set ◽  
Smog Chamber ◽  
Equilibrium Partitioning ◽  
Research Teams ◽  
Aerosol Mass ◽  
Wide Range ◽  
Mass Fractions ◽  
Dry Conditions

Abstract. Existing parameterizations tend to underpredict the α-pinene aerosol mass fraction (AMF) by a factor of 2–5 at low organic aerosol concentrations (<5 μg m−3). A wide range of smog chamber results obtained at various conditions (low/high NOx, presence/absence of UV radiation, dry/humid conditions, and temperatures ranging from 15–40°C) collected by various research teams during the last decade are used to derive new parameterizations of the SOA formation from α-pinene ozonolysis. Parameterizations are developed by fitting experimental data to a basis set of saturation concentrations (from 10−2 to 104 μg m−3) using an absorptive equilibrium partitioning model. Separate parameterizations for α-pinene SOA mass fractions are developed for: 1) Low NOx, dark, and dry conditions, 2) Low NOx, UV, and dry conditions, 3) Low NOx, dark, and high RH conditions, 4) High NOx, dark, and dry conditions, 5) High NOx, UV, and dry conditions. According to the proposed parameterizations the α-pinene SOA mass fractions in an atmosphere with 5 μg m−3 of organic aerosol range from 0.032 to 0.1 for reacted α-pinene concentrations in the 1 ppt to 5 ppb range.

scholarly journals Modeling Regional Air Quality and Climate: Improving Organic Aerosol and Aerosol Activation Processes in WRF/Chem version 3.7.1

2016 ◽  
Author(s):  
Khairunnisa Yahya ◽  
Timothy Glotfelty ◽  
Kai Wang ◽  
Yang Zhang ◽  
Athanasios Nenes
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Cloud Condensation Nuclei ◽  
Surface Ozone ◽  
Cloud Droplet ◽  
Organic Aerosol ◽  
Basis Set ◽  
Aerosol Formation ◽  
Radiation Processes ◽  
Aerosol Activation

Abstract. Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem) version 3.7.1. The existing Volatility Basis Set (VBS) treatments for organic aerosol (OA) formation in WRF/Chem is improved by considering the secondary OA (SOA) formation from semi-volatile primary organic aerosol (POA), a semi-empirical formulation for the enthalpy of vaporization of SOA, as well as functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Two-month long simulations (May to June 2010) are conducted over continental U.S. and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex) campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05) and the VBS SOA module with semivolatile POA treatment, 25% fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times of the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07) used, CB05 gives the best performance for surface ozone and PM2.5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., non-volatile POA vs. semivolatile POA) as compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC) predictions (NMBs from -40.8% to a range of -34.6% to -27.7%), with large differences between CB05/CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation parameterization based on the FN05 series reduces the large negative CDNC bias associated with the default ARG00 parameterization from -35.4% to a range of -0.8% to 7.1%, it, however, increases the errors due to overpredictions of CDNC, mainly over northeastern U.S. This work indicates a need to improve other aerosol-cloud-radiation processes in the model such as the spatial distribution of aerosol optical depth and cloud condensation nuclei in order to further improve CDNC predictions.

scholarly journals Volatility of organic aerosol and its components in the Megacity of Paris

2015 ◽  
Vol 15 (16) ◽  
pp. 22263-22289 ◽  
Author(s):  
A. Paciga ◽  
E. Karnezi ◽  
E. Kostenidou ◽  
L. Hildebrandt ◽  
M. Psichoudaki ◽  
...  
Keyword(s):  
Organic Aerosol ◽  
Basis Set ◽  
Transfer Model ◽  
Collaborative Project ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Combining Data ◽  
Wide Range ◽  
Volatile Organic ◽  
Order Of Magnitude

Abstract. Using a mass transfer model and the volatility basis set, we estimate the volatility distribution for the organic aerosol (OA) components during summer and winter in Paris, France as part of the collaborative project MEGAPOLI. The concentrations of the OA components as a function of temperature were measured combining data from a thermodenuder and an aerosol mass spectrometer (AMS) with Positive Matrix Factorization (PMF) analysis. The hydrocarbon-like organic aerosol (HOA) had similar volatility distributions for the summer and winter campaigns with half of the material in the saturation concentration bin of 10 μg m−3 and another 35–40 % consisting of low and extremely low volatility organic compounds (LVOCs and ELVOCs, respectively). The winter cooking OA (COA) was more than an order of magnitude less volatile than the summer COA. The low volatility oxygenated OA (LV-OOA) factor detected in the summer had the lowest volatility of all the derived factors and consisted almost exclusively of ELVOCs. The volatility for the semi-volatile oxygenated OA (SV-OOA) was significantly higher than that of the LV-OOA, containing both semi-volatile organic components (SVOCs) and LVOCs. The oxygenated OA (OOA) factor in winter consisted of SVOCs (45 %), LVOCs (25 %) and ELVOCs (30 %). The volatility of marine OA (MOA) was higher than that of the other factors containing around 60 % SVOCs. The biomass burning OA (BBOA) factor contained components with a wide range of volatilities with significant contributions from both SVOCs (50 %) and LVOCs (30 %). Finally, combining the O : C ratio and volatility distributions of the various factors, we incorporated our results into the two-dimensional volatility basis set (2D-VBS). Our results show that the factors cover a broad spectrum of volatilities with no direct link between the average volatility and average O : C of the OA components. Agreement between our findings and previous publications is encouraging for our understanding of the evolution of atmospheric OA.

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