scholarly journals Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis

2014 ◽  
Vol 14 (17) ◽  
pp. 9061-9076 ◽  
Author(s):  
C. Fountoukis ◽  
A. G. Megaritis ◽  
K. Skyllakou ◽  
P. E. Charalampidis ◽  
C. Pilinis ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Biomass Burning ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Quality Model ◽  
Average Mass

Abstract. A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.

scholarly journals Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis

2014 ◽  
Vol 14 (6) ◽  
pp. 7597-7635 ◽  
Author(s):  
C. Fountoukis ◽  
A. G. Megaritis ◽  
K. Skyllakou ◽  
P. E. Charalampidis ◽  
C. Pilinis ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Biomass Burning ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Average Mass ◽  
Different Seasons ◽  
Transformation Of Organic Matter

Abstract. A detailed three-dimensional regional chemical transport model (PMCAMx) was applied over Europe focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging with the model reproducing two thirds of the data (daily average mass concentrations) within a factor of two. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA in most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion) and therefore biomass burning OA is most likely underestimated in the emission inventory. The model performs well at all sites when the PMF-estimated low volatility OOA is compared against the OA with C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3 respectively.

scholarly journals Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

2021 ◽  
Vol 21 (22) ◽  
pp. 17115-17132
Author(s):  
Ksakousti Skyllakou ◽  
Pablo Garcia Rivera ◽  
Brian Dinkelacker ◽  
Eleni Karnezi ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Road Transport ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Quality Model ◽  
So2 Emissions ◽  
The Us

Abstract. Significant reductions in emissions of SO2, NOx, volatile organic compounds (VOCs), and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx), for 1990, 2001, and 2010. The use of the Particle Source Apportionment Algorithm (PSAT) allows us to link the concentration reductions to the sources of the corresponding primary and secondary PM. The reductions in SO2 emissions (64 %, mainly from electric-generating units) during these 20 years have dominated the reductions in PM2.5, leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction in EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of 3. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual average PM2.5 concentrations above 20 µg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010 in order to understand whether the model represents reasonably well the corresponding processes caused by the changes in emissions.

scholarly journals Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

2021 ◽  
Author(s):  
Ksakousti Skyllakou ◽  
Pablo Garcia Rivera ◽  
Brian Dinkelacker ◽  
Eleni Karnezi ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Road Transport ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Quality Model ◽  
So2 Emissions ◽  
The Us

Abstract. Significant reductions of emissions of SO2, NOx, volatile organic compounds (VOCs) and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx) with the Particle Source Apportionment Algorithm (PSAT). Results for 1990, 2001 and 2010 are presented. The reductions in SO2 emissions (64 %, mainly from electric generating units) during these 20 years have dominated the reductions in PM2.5 leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction of EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of three. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual-average PM2.5 concentrations above 20 μg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010, in order to understand if the model represents reasonably well the corresponding processes caused by the changes in emissions.

scholarly journals Simulation of the chemical evolution of biomass burning organic aerosol

2019 ◽  
Vol 19 (8) ◽  
pp. 5403-5415 ◽  
Author(s):  
Georgia N. Theodoritsi ◽  
Spyros N. Pandis
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Early Summer ◽  
Oxidation Products ◽  
Winter Period ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Aerosol Mass ◽  
Photochemical Aging

Abstract. The chemical transport model PMCAMx was extended to investigate the effects of partitioning and photochemical aging of biomass burning emissions on organic aerosol (OA) concentrations. A source-resolved version of the model, PMCAMx-SR, was developed in which biomass burning emissions and their oxidation products are represented separately from the other OA components. The volatility distribution and chemical aging of biomass burning OA (BBOA) were simulated based on recent laboratory measurements. PMCAMx-SR was applied to Europe during an early summer period (1–29 May 2008) and a winter period (25 February–22 March 2009). During the early summer, the contribution of biomass burning (both primary and secondary species) to total OA levels over continental Europe was estimated to be approximately 16 %. During winter the contribution was nearly 47 %, due to both extensive residential wood combustion but also wildfires in Portugal and Spain. The intermediate volatility compounds (IVOCs) with effective saturation concentration values of 105 and 106 µg m−3 are predicted to contribute around one third of the BBOA during the summer and 15 % during the winter by forming secondary OA (SOA). The uncertain emissions of these compounds and their SOA formation potential require additional attention. Evaluation of PMCAMx-SR predictions against aerosol mass spectrometer measurements in several sites around Europe suggests reasonably good performance for OA (fractional bias less than 35 % and fractional error less than 50 %). The performance was weaker during the winter suggesting uncertainties in residential heating emissions and the simulation of the resulting BBOA in this season.

scholarly journals Sources and production of organic aerosol in Mexico City: insights from the combination of a chemical transport model (PMCAMx-2008) and measurements during MILAGRO

2011 ◽  
Vol 11 (11) ◽  
pp. 5153-5168 ◽  
Author(s):  
A. P. Tsimpidi ◽  
V. A. Karydis ◽  
M. Zavala ◽  
W. Lei ◽  
N. Bei ◽  
...  
Keyword(s):  
Mexico City ◽  
Biomass Burning ◽  
Urban Areas ◽  
Transport Model ◽  
Three Dimensional ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Basis Set ◽  
Chemical Transport Model ◽  
Aerosol Mass

Abstract. Urban areas are large sources of organic aerosols and their precursors. Nevertheless, the contributions of primary (POA) and secondary organic aerosol (SOA) to the observed particulate matter levels have been difficult to quantify. In this study the three-dimensional chemical transport model PMCAMx-2008 is used to investigate the temporal and geographic variability of organic aerosol in the Mexico City Metropolitan Area (MCMA) during the MILAGRO campaign that took place in the spring of 2006. The organic module of PMCAMx-2008 includes the recently developed volatility basis-set framework in which both primary and secondary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA emission inventory is modified and the POA emissions are distributed by volatility based on dilution experiments. The model predictions are compared with observations from four different types of sites, an urban (T0), a suburban (T1), a rural (T2), and an elevated site in Pico de Tres Padres (PTP). The performance of the model in reproducing organic mass concentrations in these sites is encouraging. The average predicted PM1 organic aerosol (OA) concentration in T0, T1, and T2 is 18 μg m−3, 11.7 μg m−3, and 10.5 μg m−3 respectively, while the corresponding measured values are 17.2 μg m−3, 11 μg m−3, and 9 μg m−3. The average predicted locally-emitted primary OA concentrations, 4.4 μg m−3 at T0, 1.2 μg m−3 at T1 and 1.7 μg m−3 at PTP, are in reasonably good agreement with the corresponding PMF analysis estimates based on the Aerosol Mass Spectrometer (AMS) observations of 4.5, 1.3, and 2.9 μg m−3 respectively. The model reproduces reasonably well the average oxygenated OA (OOA) levels in T0 (7.5 μg m−3 predicted versus 7.5 μg m−3 measured), in T1 (6.3 μg m−3 predicted versus 4.6 μg m−3 measured) and in PTP (6.6 μg m−3 predicted versus 5.9 μg m−3 measured). The rest of the OA mass (6.1 μg m−3 and 4.2 μg m−3 in T0 and T1 respectively) is assumed to originate from biomass burning activities and is introduced to the model as part of the boundary conditions. Inside Mexico City (at T0), the locally-produced OA is predicted to be on average 60 % locally-emitted primary (POA), 6 % semi-volatile (S-SOA) and intermediate volatile (I-SOA) organic aerosol, and 34 % traditional SOA from the oxidation of VOCs (V-SOA). The average contributions of the OA components to the locally-produced OA for the entire modelling domain are predicted to be 32 % POA, 10 % S-SOA and I-SOA, and 58 % V-SOA. The long range transport from biomass burning activities and other sources in Mexico is predicted to contribute on average almost as much as the local sources during the MILAGRO period.

scholarly journals Simulation of the evolution of biomass burning organic aerosol with different volatility basis set schemes in PMCAMx-SRv1.0

2020 ◽  
Author(s):  
Georgia N. Theodoritsi ◽  
Giancarlo Ciarelli ◽  
Spyros N. Pandis
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Basis Set ◽  
Base Case ◽  
Chemical Transport Model ◽  
Alternative Scheme ◽  
Average Maximum ◽  
The Impact

Abstract. A source-resolved three-dimensional chemical transport model, PMCAMx-SR, was applied in the continental U.S. to investigate the contribution of the various components (primary and secondary) of biomass burning organic aerosol (bbOA) to organic aerosol levels. Two different schemes based on the volatility basis set were used for the simulation of the bbOA during different seasons. The first is the default scheme of PMCAMx-SR and the second is a recently developed scheme based on laboratory experiments of the bbOA evolution. The simulations with the alternative bbOA scheme predict much higher total bbOA concentrations when compared with the base case ones. This is mainly due to the high emissions of intermediate volatility organic compounds (IVOCs) assumed in the alternative scheme. The oxidation of these compounds is predicted to be a significant source of secondary organic aerosol. The impact of the other parameters that differ in the two schemes is low to negligible. The monthly average maximum predicted concentrations of the alternative bbOA scheme were approximately an order of magnitude higher than those of the default scheme during all seasons. The performance of the two schemes was evaluated against observed total organic aerosol concentrations from several measurement sites across the US. The results were mixed. The default scheme performed better during July and September while the alternative scheme performed a little better during April. These results illustrate the uncertainty of the corresponding predictions, the need to quantify the emissions and reactions of IVOCs from specific biomass sources, and to better constrain the total (primary and secondary) bbOA levels.

scholarly journals Simulation of the chemical evolution of biomass burning organic aerosol

2018 ◽  
Author(s):  
Georgia N. Theodoritsi ◽  
Spyros N. Pandis
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Early Summer ◽  
Oxidation Products ◽  
Winter Period ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Aerosol Mass ◽  
Photochemical Aging

Abstract. The chemical transport model PMCAMx was extended to investigate the effects of partitioning and photochemical aging of biomass burning emissions on organic aerosol (OA) concentrations. A source-resolved version of the model, PMCAMx-SR, was developed in which biomass burning organic aerosol (bbOA) and its oxidation products are represented separately from the other OA components. The volatility distribution of bbOA and its chemical aging were simulated based on recent laboratory measurements. PMCAMx-SR was applied to Europe during an early summer (1–29 May 2008) and a winter period (25 February–22 March 2009). During the early summer, the contribution of biomass burning (both primary and secondary species) to total OA levels over continental Europe was estimated to be approximately 16 %. During winter the same contribution was nearly 47 % due to both extensive residential wood combustion, but also wildfires in Portugal and Spain. The intermediate volatility compounds (IVOCs) with effective saturation concentration values of 105 and 106 μg m−3 are predicted to contribute around one third of the bbOA during the summer and 15 % during the winter by forming secondary OA. The uncertain emissions of these compounds and their SOA formation potential require additional attention. Evaluation of PMCAMx-SR predictions against aerosol mass spectrometer measurements in several sites around Europe suggests reasonably good performance for OA (fractional bias less than 35 % and fractional error less than 50 %). The performance was weaker during the winter suggesting uncertainties in the residential heating emissions and the simulation of the resulting bbOA in this season.

scholarly journals Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle-component-based factor analysis

2012 ◽  
Vol 12 (2) ◽  
pp. 5939-6018
Author(s):  
C. A. Stroud ◽  
M. D. Moran ◽  
P. A. Makar ◽  
S. Gong ◽  
W. Gong ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Point Sources ◽  
Urban Site ◽  
Stable Model ◽  
Chemical Transport Model ◽  
The Us ◽  
Model Predictions

Abstract. Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in southern Ontario (ON), Canada, were used to evaluate Environment Canada's regional chemical transport model predictions of primary organic aerosol (POA). Environment Canada's operational numerical weather prediction model and the 2006 Canadian and 2005 US national emissions inventories were used as input to the chemical transport model (named AURAMS). Particle-component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two rural sites (Harrow and Bear Creek, ON) to derive hydrocarbon-like organic aerosol (HOA) factors. Co-located carbon monoxide (CO), PM2.5 black carbon (BC), and PM1 SO4 measurements were also used for evaluation and interpretation, permitting a detailed diagnostic model evaluation. At the urban site, good agreement was observed for the comparison of daytime campaign PM1 POA and HOA mean values: 1.1 μg m−3 vs. 1.2 μg m−3, respectively. However, a POA overprediction was evident on calm nights due to an overly-stable model surface layer. Biases in model POA predictions trended from positive to negative with increasing HOA values. This trend has several possible explanations, including (1) underweighting of urban locations in particulate matter (PM) spatial surrogate fields, (2) overly-coarse model grid spacing for resolving urban-scale sources, and (3) lack of a model particle POA evaporation process during dilution of vehicular POA tail-pipe emissions to urban scales. Furthermore, a trend in POA bias was observed at the urban site as a function of the BC/HOA ratio, suggesting a possible association of POA underprediction for diesel combustion sources. For several time periods, POA overprediction was also observed for sulphate-rich plumes, suggesting that our model POA fractions for the PM2.5 chemical speciation profiles may be too high for these point sources. At the rural Harrow site, significant underpredictions in PM1 POA concentration were found compared to observed HOA concentration and were associated, based on back-trajectory analysis, with (1) transport from the Detroit/Windsor urban complex, (2) longer-range transport from the US Midwest, and (3) biomass burning. Daytime CO concentrations were significantly overpredicted at Windsor but were unbiased at Harrow. Collectively, these biases provide support for a hypothesis that combines a current underweighting of PM spatial surrogate fields for urban locations with insufficient model vertical mixing for sources close to the urban measurement sites. The magnitude of the area POA emissions sources in the US and Canadian inventories (e.g., food cooking, road and soil dust, waste disposal burning) suggests that more effort should be placed at reducing uncertainties in these sectors, especially spatial and temporal surrogates.

scholarly journals Modelling of organic aerosols over Europe (2002–2007) using a volatility basis set (VBS) framework: application of different assumptions regarding the formation of secondary organic aerosol

2012 ◽  
Vol 12 (18) ◽  
pp. 8499-8527 ◽  
Author(s):  
R. Bergström ◽  
H. A. C. Denier van der Gon ◽  
A. S. H. Prévôt ◽  
K. E. Yttri ◽  
D. Simpson
Keyword(s):  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Organic Aerosol ◽  
Basis Set ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Fire Emissions ◽  
Model Studies ◽  
Primary Emissions

Abstract. A new organic aerosol module has been implemented into the EMEP chemical transport model. Four different volatility basis set (VBS) schemes have been tested in long-term simulations for Europe, covering the six years 2002–2007. Different assumptions regarding partitioning of primary organic aerosol and aging of primary semi-volatile and intermediate volatility organic carbon (S/IVOC) species and secondary organic aerosol (SOA) have been explored. Model results are compared to filter measurements, aerosol mass spectrometry (AMS) data and source apportionment studies, as well as to other model studies. The present study indicates that many different sources contribute significantly to organic aerosol in Europe. Biogenic and anthropogenic SOA, residential wood combustion and vegetation fire emissions may all contribute more than 10% each over substantial parts of Europe. This study shows smaller contributions from biogenic SOA to organic aerosol in Europe than earlier work, but relatively greater anthropogenic SOA. Simple VBS based organic aerosol models can give reasonably good results for summer conditions but more observational studies are needed to constrain the VBS parameterisations and to help improve emission inventories. The volatility distribution of primary emissions is one important issue for further work. Emissions of volatile organic compounds from biogenic sources are also highly uncertain and need further validation. We can not reproduce winter levels of organic aerosol in Europe, and there are many indications that the present emission inventories substantially underestimate emissions from residential wood combustion in large parts of Europe.

scholarly journals Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area

2010 ◽  
Vol 10 (2) ◽  
pp. 525-546 ◽  
Author(s):  
A. P. Tsimpidi ◽  
V. A. Karydis ◽  
M. Zavala ◽  
W. Lei ◽  
L. Molina ◽  
...  
Keyword(s):  
Mexico City ◽  
Metropolitan Area ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Basis Set ◽  
Aerosol Formation ◽  
Chemical Transport Model ◽  
Starting Point

Abstract. New primary and secondary organic aerosol modules have been added to PMCAMx, a three dimensional chemical transport model (CTM), for use with the SAPRC99 chemistry mechanism based on recent smog chamber studies. The new modelling framework is based on the volatility basis-set approach: both primary and secondary organic components are assumed to be semivolatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. This new framework with the use of the new volatility basis parameters for low-NOx and high-NOx conditions tends to predict 4–6 times higher anthropogenic SOA concentrations than those predicted with the older generation of models. The resulting PMCAMx-2008 was applied in Mexico City Metropolitan Area (MCMA) for approximately a week during April 2003 during a period of very low regional biomass burning impact. The emission inventory, which uses as a starting point the MCMA 2004 official inventory, is modified and the primary organic aerosol (POA) emissions are distributed by volatility based on dilution experiments. The predicted organic aerosol (OA) concentrations peak in the center of Mexico City, reaching values above 40 μg m−3. The model predictions are compared with the results of the Positive Matrix Factorization (PMF) analysis of the Aerosol Mass Spectrometry (AMS) observations. The model reproduces both Hydrocarbon-like Organic Aerosol (HOA) and Oxygenated Organic Aerosol (OOA) concentrations and diurnal profiles. The small OA underprediction during the rush-hour periods and overprediction in the afternoon suggest potential improvements to the description of fresh primary organic emissions and the formation of the oxygenated organic aerosols, respectively, although they may also be due to errors in the simulation of dispersion and vertical mixing. However, the AMS OOA data are not specific enough to prove that the model reproduces the organic aerosol observations for the right reasons. Other combinations of contributions of primary and secondary organic aerosol production rates may lead to similar results. The model results strongly suggest that, during the simulated period, transport of OA from outside the city was a significant contributor to the observed OA levels. Future simulations should use a larger domain in order to test whether the regional OA can be predicted with current SOA parameterizations. Sensitivity tests indicate that the predicted OA concentration is especially sensitive to the volatility distribution of the emissions in the lower volatility bins.

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