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 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 Chemical Transport Model Simulations of Organic Aerosol in Southern California: Model Evaluation and Gasoline and Diesel Source Contributions

2016 ◽  
Author(s):  
Shantanu H. Jathar ◽  
Matthew Woody ◽  
Havala O. T. Pye ◽  
Kirk R. Baker ◽  
Allen L. Robinson
Keyword(s):  
Particulate Matter ◽  
Southern California ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Production Model ◽  
Anthropogenic Sources ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Mobile Sources

Abstract. Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we use experimentally derived inputs and parameterizations to predict concentrations and properties of organic aerosol (OA) from mobile sources in southern California using a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ). The updated model includes secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOC). Compared to the treatment of OA in the traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted OA mass concentrations but it did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), and ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performs similar to a recently released research version of CMAQ. Mobile sources are predicted to contribute about 30–40 % of the OA in southern California (half of which is SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA is attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing less than 5 % to the total OA. Gasoline sources are predicted to contribute about thirteen times more OA than diesel sources; this difference is driven by differences in SOA production. Model predictions highlight the need to better constrain multi-generational oxidation reactions in chemical transport models.

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 Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

2017 ◽  
Vol 17 (6) ◽  
pp. 4305-4318 ◽  
Author(s):  
Shantanu H. Jathar ◽  
Matthew Woody ◽  
Havala O. T. Pye ◽  
Kirk R. Baker ◽  
Allen L. Robinson
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Southern California ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Production Model ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Mobile Sources

Abstract. Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30–40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2021 ◽  
Vol 14 (3) ◽  
pp. 1681-1697
Author(s):  
Jianhui Jiang ◽  
Imad El Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
The Balkans ◽  
Wall Loss

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

scholarly journals Contributions of local and regional sources to fine PM in the megacity of Paris

2013 ◽  
Vol 13 (10) ◽  
pp. 25769-25799 ◽  
Author(s):  
K. Skyllakou ◽  
B. N. Murphy ◽  
A. G. Megaritis ◽  
C. Fountoukis ◽  
S. N. Pandis
Keyword(s):  
Particulate Matter ◽  
Long Range ◽  
Transport Model ◽  
Organic Aerosol ◽  
Photochemical Activity ◽  
Chemical Transport Model ◽  
Regional Sources ◽  
Range Transport ◽  
Local Sources ◽  
Local Emissions

Abstract. The Particulate Matter Source Apportionment Technology (PSAT) is used together with PMCAMx, a regional chemical transport model, to estimate how local emissions and pollutant transport affect primary and secondary particulate matter mass concentration levels in Paris. During the summer and the winter periods examined, only 13% of the PM2.5 is predicted to be due to local Paris emissions, with 36% coming from mid range (50–500 km from the center of the Paris) sources and 51% from long range transport (more than 500 km from Paris). The local emissions contribution to predicted elemental carbon (EC) is significant, with almost 60% of the EC originating from local sources during both summer and winter. Approximately 50% of the predicted fresh primary organic aerosol (POA) originated from local sources and another 45% from areas 100–500 km from the receptor region during summer. Regional sources dominated the secondary PM components. During summer more than 70% of the predicted sulfate originated from SO2 emitted more than 500 km away from the center of the Paris. Also more than 45% of secondary organic aerosol (SOA) was due to the oxidation of VOC precursors that were emitted 100–500 km from the center of the Paris. The model predicts more contribution from long range secondary PM sources during winter because the timescale for its production is longer due to the slower photochemical activity. PSAT results for contributions of local and regional sources were compared with observation-based estimates from field campaigns that took place during the MEGAPOLI project. PSAT predictions are in general consistent (within 20%) with these estimates for OA and sulfate. The only exception is that PSAT predicts higher local EC contribution during the summer compared to that estimated from observations.

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 A simplified parameterization of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) for global chemistry and climate models: a case study with GEOS-Chem v11-02-rc

2019 ◽  
Vol 12 (7) ◽  
pp. 2983-3000 ◽  
Author(s):  
Duseong S. Jo ◽  
Alma Hodzic ◽  
Louisa K. Emmons ◽  
Eloise A. Marais ◽  
Zhe Peng ◽  
...  
Keyword(s):  
Climate Models ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Computational Cost ◽  
Organic Aerosol ◽  
Basis Set ◽  
Chemical Transport Model ◽  
Computationally Efficient ◽  
So2 Emissions ◽  
Emission Changes

Abstract. Secondary organic aerosol derived from isoprene epoxydiols (IEPOX-SOA) is thought to contribute the dominant fraction of total isoprene SOA, but the current volatility-based lumped SOA parameterizations are not appropriate to represent the reactive uptake of IEPOX onto acidified aerosols. A full explicit modeling of this chemistry is however computationally expensive owing to the many species and reactions tracked, which makes it difficult to include it in chemistry–climate models for long-term studies. Here we present three simplified parameterizations (version 1.0) for IEPOX-SOA simulation, based on an approximate analytical/fitting solution of the IEPOX-SOA yield and formation timescale. The yield and timescale can then be directly calculated using the global model fields of oxidants, NO, aerosol pH and other key properties, and dry deposition rates. The advantage of the proposed parameterizations is that they do not require the simulation of the intermediates while retaining the key physicochemical dependencies. We have implemented the new parameterizations into the GEOS-Chem v11-02-rc chemical transport model, which has two empirical treatments for isoprene SOA (the volatility-basis-set, VBS, approach and a fixed 3 % yield parameterization), and compared all of them to the case with detailed fully explicit chemistry. The best parameterization (PAR3) captures the global tropospheric burden of IEPOX-SOA and its spatiotemporal distribution (R2=0.94) vs. those simulated by the full chemistry, while being more computationally efficient (∼5 times faster), and accurately captures the response to changes in NOx and SO2 emissions. On the other hand, the constant 3 % yield that is now the default in GEOS-Chem deviates strongly (R2=0.66), as does the VBS (R2=0.47, 49 % underestimation), with neither parameterization capturing the response to emission changes. With the advent of new mass spectrometry instrumentation, many detailed SOA mechanisms are being developed, which will challenge global and especially climate models with their computational cost. The methods developed in this study can be applied to other SOA pathways, which can allow including accurate SOA simulations in climate and global modeling studies in the future.

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