Simulation Of Secondary Organic Aerosol Research Articles

Combined Smog Chamber/Oxidation Flow Reactor Study on Aging of Secondary Organic Aerosol from Photooxidation of Aromatic Hydrocarbons.

Secondary organic aerosol (SOA) is a significant component of atmospheric fine particulate matter (PM2.5), and their physicochemical properties can be significantly changed in the aging process. In this study, we used a combination consisting of a smog chamber (SC) and oxidation flow reactor (OFR) to investigate the continuous aging process of gas-phase organic intermediates and SOA formed from the photooxidation of toluene, a typical aromatic hydrocarbon. Our results showed that as the OH exposure increased from 2.6 × 1011 to 6.3 × 1011 molecules cm-3 s (equivalent aging time of 2.01-4.85 days), the SOA mass concentration (2.9 ± 0.05-28.7 ± 0.6 μg cm-3) and corrected SOA yield (0.073-0.26) were significantly enhanced. As the aging process proceeds, organic acids and multiple oxygen-containing oxidation products are continuously produced from the photochemical aging process of gas-phase organic intermediates (mainly semi-volatile and intermediate volatility species, S/IVOCs). The multigeneration oxidation products then partition to the aerosol phase, while functionalization of SOA rather than fragmentation dominated in the photochemical aging process, resulting in much higher SOA yield after aging compared to that in the SC. Our study indicates that SOA yields as a function of OH exposure should be considered in air quality models to improve SOA simulation, and thus accurately assess the impact on SOA properties and regional air quality.

Contrasting molecular characteristics and formation mechanisms of biogenic and anthropogenic secondary organic aerosols at the summit and foot of Mt. Huang, East China

Secondary organic aerosol (SOA) exerts a considerable influence on atmospheric chemistry. However, little information about the vertical distribution of SOA in the alpine setting is available, which limited the simulation of SOA using chemical transport models. Here, a total of 15 biogenic and anthropogenic SOA tracers were measured in PM2.5 aerosols at both the summit (1840 m a.s.l.) and foot (480 m a.s.l.) of Mt. Huang during the winter of 2020 to explore their vertical distribution and formation mechanism. Most of the determined chemical species (e.g., BSOA and ASOA tracers, carbonaceous components, major inorganic ions) and gaseous pollutants at the foot of Mt. Huang were 1.7–3.2 times higher concentrations than those at the summit, suggesting the relatively more significant effect of anthropogenic emissions at the ground level. The ISORROPIA-II model showed that aerosol acidity increases as altitude decreases. Air mass trajectories, potential source contribution function (PSCF), and correlation analysis of BSOA tracers with temperature revealed that SOA at the foot of Mt. Huang was mostly derived from the local oxidation of volatile organic compounds (VOCs), while SOA at the summit was mainly influenced by long-distance transport. The robust correlations of BSOA tracers with anthropogenic pollutants (e.g., NH3, NO2, and SO2) (r = 0.54–0.91, p < 0.05) indicated that anthropogenic emissions could promote BSOA productions in the mountainous background atmosphere. Moreover, most of SOA tracers (r = 0.63–0.96, p < 0.01) and carbonaceous species (r = 0.58–0.81, p < 0.01) were correlated well with levoglucosan in all samples, suggesting that biomass burning played an important role in the mountain troposphere. This work demonstrated that daytime SOA at the summit of Mt. Huang was significantly influenced by the valley breeze in winter. Our results provide new insights into the vertical distributions and provenance of SOA in the free troposphere over East China.

Modeling of wintertime regional formation of secondary organic aerosols around Beijing: sensitivity analysis and anthropogenic contributions

Modeling of secondary organic aerosol (SOA) has remained a big challenge due to the various precursors and complex processes involved. In this study, the WRF-CAMx model was used to predict the ambient SOA concentrations in urban Beijing as well as the North China Plain (NCP) during a polluted period in winter. To identify the major uncertainties and improve the model performance, a series of model tests were performed to assess the sensitivity of model prediction to the key factors. Then the sources of SOA in Beijing were identified using the optimized model. Both the volatility basis set (VBS) approach and the two-product approach were used for SOA simulation. Although the modeled SOA was underpredicted compared with the SOA estimated through filter-based measurements, the VBS scheme produced higher SOA than the traditional two-product scheme. According to the sensitivity tests with the VBS scheme, the emissions of volatile organic compounds (VOC) and intermediate volatility organic compounds (IVOC) as well as the oxidant levels were the key factors that affected SOA prediction. Based on the optimized simulation scenario, the potential contributions from different anthropogenic sources and source areas were identified, with over 80% of SOA in urban Beijing from regional transport of SOA or its precursors from the surrounding areas during the polluted period. Residential emission in the North China Plain appeared as the dominant source of SOA in urban Beijing from the perspective of regional contribution.Graphical

Emission factors and chemical profile of I/SVOCs emitted from household biomass stove in China

Household combustion of biomass straw for cooking or heating is one of the most important emission sources of intermediate volatility and semi-volatile organic compounds (I/SVOCs). However, there are limited studies on the emission factors (EFs) and speciation profiles of I/SVOCs from household stoves burning biomass straw. In this study, experiments were conducted in a typical Chinese stove to test the EFs and species of I/SVOCs in three commonly used straws. It was revealed that EFs of I/SVOCs emitted from the burning of corn straw, rice straw, and wheat straw were 6.7, 1.9, and 9.8 g/kg, respectively, which accounted for 48.3 %, 36.8 %, and 48.6 % of total organic compounds emitted. Particulate organic compounds were dominated by ketones, oxygenated aromatics, acids, esters, and nitrogen-containing compounds, whereas the gaseous phase was dominated by aldehydes, acids, and aromatics. Although I/SVOCs only accounted for 18.1–23.6 % of the gaseous emissions from burning of straw, they represented 64.8–72.9 % of the secondary organic aerosol formation potential (SOAFP). The EFs of 16 priority polycyclic aromatic hydrocarbons (PAHs) were 362.0, 262.5, and 1145.2 mg/kg for corn straw, rice straw, and wheat straw, respectively, among which 3-ring and 4-ring PAHs were the main components. Thus, the results of this study provide new reliable I/SVOCs data that are useful for the development of an accurate emission inventory of organic compounds, simulation of secondary organic aerosol (SOA) formation, and health risk assessment.

A core-shell box model for simulating viscosity dependent secondary organic aerosol (CSVA) and its application

Secondary organic aerosol (SOA) plays a key role in air pollution and global climate change. However, the understanding and modelling of SOA properties and evolution are still limited. In this paper, we developed a novel kinetic Core-Shell box model for Viscosity dependent SOA simulation (CSVA), which includes explicit gas-phase reactions (MCM), homogeneous nucleation by H2SO4-NH3-H2O, viscosity dependent mass transfer between gas and particle phases (organic and aqueous phases) and particle-phase reactions. The gas-particle mass transfer is represented by chainlike reactions analogizing to electrical resistance. The CSVA model is verified and applied to chamber experiments of toluene oxidation systems. The monomers and dimers of SOA are determined by coupling the high-resolution Orbitrap mass spectra and MCM mechanism. The majority of dimers are confirmed to be peroxyhemiacetals formed by reactions of hydroperoxides with aldehydes in the particle phase. The results show that CSVA can well capture the following processes: (1) relative humidity (RH) dependent nucleation of the H2SO4-NH3-H2O system, (2) particle size-dependent hygroscopic growth of inorganics (e.g., NaCl and (NH4)2SO4) and organics (levoglucosan and SOA), (3) NOx dependent SOA formation, (4) viscosity-induced evolution of particle size distribution, and (5) effect of RH on SOA formation. In particular, our model reproduces the phenomenon that the evolution of SOA particle size distribution from a one-peak mode into a two-peak mode is due to viscosity.

Variation characteristics of fine particulate matter and its components in diesel vehicle emission plumes

A rapid reaction occurs near the exhaust nozzle when vehicle emissions contact the air. Twenty diesel vehicles were studied using a new multipoint sampling system that is suitable for studying the exhaust plume near the exhaust nozzle. The variation characteristics of fine particle matter (PM2.5) and its components in diesel vehicle exhaust plumes were analyzed. The PM2.5 emissions gradually increased with increasing distance from the nozzle in the plume. Elemental carbon emissions remained basically unchanged, organic carbon and total carbon (TC) increased with increasing distance. The concentrations of SO42−, NO3− and NH4+ (SNA) directly emitted by the vehicles were very low but increased rapidly in the exhaust plume. The selective catalytic reduction (SCR) reduced 42.7% TC, 40% NO3− emissions, but increased 104% SO42− and 36% NH4+ emissions, respectively. In summary, the SCR reduced 29% primary PM2.5 emissions for the tested diesel vehicles. The NH4NO3 particle formation maybe more important in the plume, and there maybe other forms of formation of NH4+ (eg. NH4Cl). The generation of secondary organic carbon (SOC) plays a leading role in the generation of secondary PM2.5. The SCR enhanced the formation of SOC and SNA in the plume, but comprehensive analysis shows that the SCR more enhanced the SNA formation in the plume, which is mainly new particles formation process. The inconsistency between secondary organic aerosol (SOA) and primary organic aerosol definitions is one of the important reasons for the difference between SOA simulation and observation.

Simulation of secondary organic aerosol over the Yangtze River Delta region: The impacts from the emissions of intermediate volatility organic compounds and the SOA modeling framework

Secondary organic aerosols (SOA) are an important component of fine particulate matter (PM2.5). However, photochemical models often have difficulty capturing the observed magnitudes of SOA due to uncertainties in precursor emissions and modeling approach. In this study, we conducted a modeling study of SOA in the Yangtze River Delta (YRD) region of China to investigate the impact of emissions of intermediate-volatility organic compounds (IVOC) and the SOA modeling schemes. IVOC emissions, which are important SOA precursors but are missing from most emission inventories, are estimated for the YRD region based on two methods. First, scaling IVOC from emissions of primary organic aerosols (POA) estimates 730 Gg with on-road and industry sectors being the main contributors. Second, scaling IVOC emissions using emission factors and activity data estimates 313 Gg, 57% lower than the first method, with industry and off-road sectors being the major contributors. A photochemical model simulation of SOA for July 2018, conducted using standard emission inventories for the YRD region, significantly underestimates SOA by 61% at the Dianshan Lake monitoring site (DSL). A series of simulations with two different SOA modeling schemes found that with the traditional two-product modeling framework, IVOC emissions enhance simulated SOA concentrations by 8%–27% at DSL and 5%–26% over the YRD region in July 2018. Increasing SOA mass yields from IVOC by a factor of five leads to better agreement with observations at the DSL site. Switching to the 1.5-Dimension Volatility Basis Set (VBS) approach increases simulated SOA by 76% at DSL but reduced POA concentration by 72%, leading to an overall decrease of organic aerosol (OA) by 12%. Unlike the two-product scheme where POA is entirely inert, the VBS scheme includes POA in the OA chemistry. The SOA:OA ratio and the anthropogenic-to-biogenic SOA ratio (ASOA:BSOA) also vary systematically with SOA modeling schemes suggesting that detailed measurements of SOA composition could further constrain modeling methods.

A gridded emission inventory of semi-volatile and intermediate volatility organic compounds in China

An emission inventory of precursors is a prerequisite for the simulation of secondary organic aerosol (SOA), which could provide valuable information on the evolution of precursors, formation of SOA, and its influence on fine particle (PM2.5) abundance, oxidative capacity, and climate change. However, an emission inventory of semi-volatile and intermediate volatility organic compounds (S/IVOCs), the key precursor of SOA, particularly the gridded inventory that is appropriate for input into regional air quality models, remains limited in China, leading to an incomplete understanding of S/IVOCs sources and roles in SOA formation and the atmospheric environment. Therefore, a gridded emission inventory of S/IVOCs in China for 2016 was developed based on ample source-specific measured data on emission ratios of S/IVOCs to primary organic aerosols (POA) from literatures. The total emission of S/IVOCs was estimated to be 9.6 Tg, and industry and residential sectors were major sources of S/IVOCs, with contributions of 48.0% and 30.2%, respectively. The spatial variations suggested that S/IVOC emissions were mainly distributed in the highly industrialized and urbanized regions in China, such as Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Sichuan–Chongqing (SC) regions, though the contributions and temporal patterns varied between different regions. Furthermore, uncertainty of the emission inventory was estimated to be within the range of −66%–153%, which was mainly attributed to emission ratios of IVOCs/POA for industry, transportation, and power plants. The gridded emission inventory developed in this study can be used to estimate the emissions of S/IVOCs in different regions, and can be applied to different models for a better understanding of the environmental effects of S/IVOCs.

Chemical formation pathways of secondary organic aerosols in the Beijing-Tianjin-Hebei region in wintertime

A regional air quality model system (RAQMS) was developed by incorporating an aqueous reaction mechanism for secondary organic aerosol (SOA) formation and primary semi-volatile (SVOC) and intermediate volatile organic compounds (IVOC) precursors to investigate various chemical pathways for SOA formation in the Beijing-Tianjin-Hebei (BTH) region in wintertime. Model comparison against observations demonstrates that the model is able to well reproduce meteorological variables and major aerosol chemical components, and the model improves SOA simulation significantly by including primary S/IVOCs (SVOC + IVOC) and aqueous reactions into the model. SVOC and IVOC emissions were relatively higher over the regions from southern Hebei province to Beijing and Tianjin, with the emission rates up to 0.15 mg m−2 hr−1 and 0.3 mg m−2 hr−1, respectively. The glyoxal (GLY) and methylglyoxal (MGLY) emissions were similar in distribution to those of S/IVOC emissions, with the maximum of 0.08 mg m −2 hr−1. The simulated SOA concentrations exhibited a southwest-northeast belt extending from southern Hebei to Beijing, with the maximum of 35 μg m−3 in southern Hebei province. The average contributions from various precursors or chemical pathways to SOA formation during the study period were estimated, in which AVOCs (anthropogenic VOCs), SVOCs, IVOCs, BVOCs (biogenic VOCs), GLY and MGLY contributed 38.4%, 24.9%, 28.4%, 0.2% and 8.1% of SOA mass concentration, respectively, in the BTH region. The maximum average contribution of GLY and MGLY to SOA reached 16% in southern Hebei province during a severe haze episode. From the clean to haze periods, concentrations of all SOA components apparently increased along with increasing atmospheric stability and weakening dispersion, but the increasing rates of SOA concentration produced by AVOCs and aqueous reactions were larger than those by primary S/IVOCs due to different chemical processes, and the AVOC-produced SOA dominated over the other SOA components during the haze periods.

Emission inventory of semi-volatile and intermediate-volatility organic compounds and their effects on secondary organic aerosol over the Pearl River Delta region

Abstract. Semi-volatile and intermediate-volatility organic compounds (S–IVOCs) are considered critical precursors of secondary organic aerosol (SOA), which is an important component of fine particulate matter (PM2.5). However, knowledge of the contributions of S–IVOCs to SOA is still lacking in the Pearl River Delta (PRD) region, southern China. Therefore, in this study, an emission inventory of S–IVOCs in the PRD region was developed for the first time for the year 2010. The S–IVOC emissions were calculated based on a parameterization method involving the emission factors of POA (primary organic aerosol), emission ratios of S–IVOCs to POA, and domestic activity data. The total emissions of S–IVOCs were estimated to be 323.4 Gg, with major emissions from central cities in the PRD, i.e., Guangzhou, Foshan, and Shenzhen. On-road mobile sources and industries were the two major contributors of S–IVOC emissions, with contributions of ∼42 % and ∼35 %, respectively. Furthermore, uncertainties of the emission inventory were evaluated through Monte Carlo simulation. The uncertainties ranged from −79 % to 229 %, which could be mainly attributed to mass fractions of OC (organic carbon) to PM2.5 from on-road mobile emissions and emission ratios of IVOCs ∕ POA. The developed S–IVOC emission inventory was further incorporated into the Weather Research and Forecasting with Chemistry (WRF-Chem) model with a volatility basis-set (VBS) approach to improve the performance of SOA simulation and to evaluate the influence of S–IVOCs on SOA formation at a receptor site (Wan Qing Sha (WQS) site) in the PRD. The following results could be obtained. (1) The model could resolve about 34 % on average of observed SOA concentrations at WQS after considering the emissions of S–IVOCs, and 18 %–77 % with the uncertainties of the S–IVOC emission inventory considered. (2) The simulated SOA over the PRD region was increased by 161 % with the input of S–IVOC emissions, and it could be decreased to 126 % after the reaction coefficient of S–IVOCs with OH radical was improved. (3) Among all anthropogenic sources of S–IVOCs, industrial emission was the most significant contributor of S–IVOCs for SOA formation, followed by on-road mobile, dust, biomass burning, residential, and off-road mobile emissions. Overall, this study firstly quantified emissions of S–IVOCs and evaluated their roles in SOA formation over the PRD, which contributes towards significantly improving SOA simulation and better understanding of SOA formation mechanisms in the PRD and other regions in China.

Differences of the oxidation process and secondary organic aerosol formation at low and high precursor concentrations

Current atmospheric quality models usually underestimate the level of ambient secondary organic aerosol (SOA), one of the possible reasons is that the precursors at different concentrations may undergo different oxidation processes and further affect SOA formation. Therefore, there is a need to perform more chamber studies to disclose the influence. In this work, SOA formation over a wide range of initial precursor concentrations (tens of ppb to hundreds of ppb levels) was investigated in a 30 m3 indoor smog chamber, and mainly through the analysis of multiple generations of VOCs detected from HR-ToF-PTRMS to expound the difference in the oxidation process between low and high precursor concentrations. Compared to high initial concentrations, gas-phase intermediates formed at low concentrations had a higher intensity by about one order of magnitude, and the low-volatility compounds also had a higher formation potential due to the competition between semi-volatile intermediates and precursors with oxidants. In addition, the formed SOA was more oxidized with higher f44 value (0.14 ± 0.02) and more relevant to real atmosphere than that formed at high concentrations. This work should help to deeply understand SOA formation and improve the performance of air quality models for SOA simulation.

Kinetic modeling studies of SOA formation from &amp;lt;i&amp;gt;α&amp;lt;/i&amp;gt;-pinene ozonolysis

Abstract. This paper describes the implementation of a kinetic gas-particle partitioning approach used for the simulation of secondary organic aerosol (SOA) formation within the SPectral Aerosol Cloud Chemistry Interaction Model (SPACCIM). The kinetic partitioning considers the diffusion of organic compounds into aerosol particles and the subsequent chemical reactions in the particle phase. The basic kinetic partitioning approach is modified by the implementation of chemical backward reaction of the solute within the particle phase as well as a composition-dependent particle-phase bulk diffusion coefficient. The adapted gas-phase chemistry mechanism for α-pinene oxidation has been updated due to the recent findings related to the formation of highly oxidized multifunctional organic compounds (HOMs). Experimental results from a LEAK (Leipziger Aerosolkammer) chamber study for α-pinene ozonolysis were compared with the model results describing this reaction system.The performed model studies reveal that the particle-phase bulk diffusion coefficient and the particle-phase reactivity are key parameters for SOA formation. Using the same particle-phase reactivity for both cases, we find that liquid particles with higher particle-phase bulk diffusion coefficients have 310 times more organic material formed in the particle phase compared to higher viscous semi-solid particles with lower particle-phase bulk diffusion coefficients. The model results demonstrate that, even with a moderate particle-phase reactivity, about 61 % of the modeled organic mass consists of reaction products that are formed in the liquid particles. This finding emphasizes the potential role of SOA processing. Moreover, the initial organic aerosol mass concentration and the particle radius are of minor importance for the process of SOA formation in liquid particles. A sensitivity study shows that a 22-fold increase in particle size merely leads to a SOA increase of less than 10 %.Due to two additional implementations, allowing backward reactions in the particle phase and considering a composition-dependent particle-phase bulk diffusion coefficient, the potential overprediction of the SOA mass with the basic kinetic approach is reduced by about 40 %. HOMs are an important compound group in the early stage of SOA formation because they contribute up to 65 % of the total SOA mass at this stage. HOMs also induce further SOA formation by providing an absorptive medium for SVOCs (semi-volatile organic compounds). This process contributes about 27 % of the total organic mass. The model results are very similar to the LEAK chamber results. Overall, the sensitivity studies demonstrate that the particle reactivity and the particle-phase bulk diffusion require a better characterization in order to improve the current model implementations and to validate the assumptions made from the chamber simulations. The successful implementation and testing of the current kinetic gas-particle partitioning approach in a box model framework will allow further applications in a 3-D model for regional-scale process investigations.

Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ

The secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ, referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6–11 μg/m3 and 8–17 μg/m3, respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%.

Modeling the meteorological and chemical effects of secondary organic aerosols during an EUCAARI campaign

Abstract. A volatility basis set (VBS) approach for the simulation of secondary organic aerosol (SOA) formation is incorporated in the online coupled atmospheric model system COSMO-ART and applied over Europe during the EUCAARI May 2008 campaign. Organic aerosol performance is improved when compared to the default SOA module of COSMO-ART (SORGAM) against high temporal resolution aerosol mass spectrometer ground measurements. The impact of SOA on the overall radiative budget was investigated. The mean direct surface radiative cooling averaged over Europe is −1.2 W m−2, representing approximately 20% of the total effect of aerosols on the radiative budget. However, responses are not spatially correlated with the radiative forcing, due to the nonlinear interactions among changes in particle chemical composition, water content, size distribution and cloud cover. These interactions initiated~by the effect of SOA on radiation are found to result even in a positive forcing in specific areas. Further model experiments showed that the availability of nitrogen oxides slightly affects SOA production, but that the aging rate constant used in the VBS approximation and boundary concentrations assumed in the model should be carefully selected. The aging of SOA is found to reduce hourly nitrate levels by up to 30%, while the condensation of inorganic species upon pre-existing, SOA-rich particles results in a monthly average increase of 5% in sulfate and ammonium formation in the accumulation mode.

Regional modeling of secondary organic aerosol over China using WRF/Chem

Using a new generation air quality modeling system (WRF/Chem) fully coupled with secondary organic aerosol model (SORGAM), we investigate the spatial and temporal characteristics of secondary organic aerosol (SOA) as well as the relative contributions of anthropogenic and biogenic sources to the formation of SOA in 2006 over China. To improve SOA simulation, a parameterization scheme for the isoprene induced SOA formation was added in WRF/Chem. The simulated SOA concentrations show large temporal and spatial variability, with the highest levels occur in summer and the lowest concentrations occur in winter. The high SOA regions are located near 30°N in central China in summer, with values exceeding 8 μg m −3, while they shift to South China, mainly in Pearl River Delta (PRD) region in winter, with the concentrations at or below 2 μg m −3. Across the whole country, the average ground level SOA concentrations are 0.94, 2.54, 1.41, 0.43, and 1.34 μg m −3 in spring, summer, autumn, winter, and year, respectively. Commonly, the SOA loading is mostly concentrated in the boundary layer (∼70%). Although the SOA concentrations are dominated by biogenic sources in summer, the contributions of anthropogenic sources exceed biogenic sources over most areas in winter. On the national level, the anthropogenic sources contribute 35% of total SOA, with 41%, 26%, 39%, and 59% in spring, summer, autumn and winter, respectively. The estimated annual SOA production reaches 3.05 Tg yr −1 over China, accounting for about 4–25% of global SOA formation. The modeled OC and EC concentrations as well as SOC to OC ratios are compared with the measurements and previous studies. The results suggest that the spatial and temporal characteristic of OC and EC levels is well captured by the model. However, the simulated SOA concentrations in this study might be underestimated by 0–75%. The modeling SOA in this paper are in agreement with other field and modeling studies, also showing the importance of SOA in total organic aerosol in China.

A large organic aerosol source in the free troposphere missing from current models

Aircraft measurements of organic carbon (OC) aerosol by two independent methods over the NW Pacific during the ACE‐Asia campaign reveal unexpectedly high concentrations in the free troposphere (FT). Concentrations average 4 μg sm−3 in the 2–6.5 km column with little vertical gradient. These values are 10–100 times higher than computed with a global chemical transport model (CTM) including a standard 2‐product simulation of secondary organic aerosol (SOA) formation based on empirical fits to smog chamber data. The same CTM reproduces the observed vertical profiles of sulfate and elemental carbon aerosols, which indicate sharp decreases from the boundary layer to the FT due to wet scavenging. Our results suggest a large, sustained source of SOA in the FT from oxidation of long‐lived volatile organic compounds. We find that this SOA is the dominant component of aerosol mass in the FT, with implications for intercontinental pollution transport and radiative forcing of climate.