Simulated Secondary Organic Aerosol Research Articles

Modeling the influence of carbon branching structure on secondary organic aerosol formation via multiphase reactions of alkanes

Abstract. Branched alkanes represent a significant proportion of hydrocarbons emitted in urban environments. To accurately predict the secondary organic aerosol (SOA) budgets in urban environments, these branched alkanes should be considered as SOA precursors. However, the potential to form SOA from diverse branched alkanes under varying environmental conditions is currently not well understood. In this study, the Unified Partitioning Aerosol Phase Reaction (UNIPAR) model is extended to predict SOA formation via the multiphase reactions of various branched alkanes. Simulations with the UNIPAR model, which processes multiphase partitioning and aerosol-phase reactions to form SOA, require a product distribution predicted from an explicit gas kinetic mechanism, whose oxygenated products are applied to create a volatility- and reactivity-based αi species array. Due to a lack of practically applicable explicit gas mechanisms, the prediction of the product distributions of various branched alkanes was approached with an innovative method that considers carbon lengths and branching structures. The αi array of each branched alkane was primarily constructed using an existing αi array of the linear alkane with the nearest vapor pressure. Generally, the vapor pressures of branched alkanes and their oxidation products are lower than those of linear alkanes with the same carbon number. In addition, increasing the number of alkyl branches can also decrease the ability of alkanes to undergo autoxidation reactions that tend to form low-volatility products and significantly contribute to alkane SOA formation. To account for this, an autoxidation reduction factor, as a function of the degree and position of branching, was applied to the lumped groups that contain autoxidation products. The resulting product distributions were then applied to the UNIPAR model for predicting branched-alkane SOA formation. The simulated SOA mass was compared to SOA data generated under varying experimental conditions (i.e., NOx levels, seed conditions, and humidity) in an outdoor photochemical smog chamber. Branched-alkane SOA yields were significantly impacted by NOx levels but insignificantly impacted by seed conditions or humidity. The SOA formation from branched and linear alkanes in diesel fuel was simulated to understand the relative importance of branched and linear alkanes with a wide range of carbon numbers. Overall, branched alkanes accounted for a higher proportion of SOA mass than linear alkanes due to their higher contribution to diesel fuel.

Simulated phase state and viscosity of secondary organic aerosols over China

Abstract. Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states. Chemical transport models (CTMs), however, usually assume that SOA particles are homogeneous and well-mixed liquids, with rapid establishment of gas–particle equilibrium for simulations of SOA formation and partitioning. Missing the information of SOA phase state and viscosity in CTMs impedes accurate representation of SOA formation and evolution, affecting the predictions of aerosol effects on air quality and climate. We have previously developed a parameterization to estimate the glass transition temperature (Tg) of an organic compound based on volatility and to predict viscosity of SOA. In this study, we apply this method to predict the phase state of SOA particles over China in summer of 2018 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The simulated Tg of dry SOA (Tg,org) agrees well with the value estimated from ambient volatility measurements at an urban site in Beijing. For the spatial distributions of Tg,org, simulations show that at the surface the values of Tg,org range from ∼287 to 305 K, with higher values in northwestern China, where SOA particles have larger mass fractions of low-volatility compounds. Considering water uptake by SOA particles, the SOA viscosity shows a prominent geospatial gradient in which highly viscous or solid SOA particles are mainly predicted in northwestern China. The lowest and highest SOA viscosity values both occur over the Qinghai–Tibet Plateau, where the solid phase state is predicted over dry and high-altitude areas and the liquid phase state is predicted mainly in the south of the plateau with high relative humidity during the summer monsoon season. Sensitivity simulations show that, including the formation of extremely low-volatility organic compounds, the percent time that a SOA particle is in the liquid phase state decreases by up to 12 % in southeastern China during the simulated period. With an assumption that the organic and inorganic compounds are internally mixed in one phase, we show that the water absorbed by inorganic species can significantly lower the simulated viscosity over southeastern China. This indicates that constraining the uncertainties in simulated SOA volatility distributions and the mixing state of the organic and inorganic compounds would improve prediction of viscosity in multicomponent particles in southeastern China. We also calculate the characteristic mixing timescale of organic molecules in 200 m SOA particles to evaluate kinetic limitations in SOA partitioning. Calculations show that during the simulated period the percent time of the mixing timescale longer than 1 h is >70 % at the surface and at 500 hPa in most areas of northern China, indicating that kinetic partitioning considering the bulk diffusion in viscous particles may be required for more accurate prediction of SOA mass concentrations and size distributions over these areas.

CAMx–UNIPAR simulation of secondary organic aerosol mass formed from multiphase reactions of hydrocarbons under the Central Valley urban atmospheres of California

Abstract. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model was integrated into the Comprehensive Air quality Model with extensions (CAMx) to process secondary organic aerosol (SOA) formation by capturing multiphase reactions of hydrocarbons (HCs) in regional scales. SOA growth was simulated using a wide range of anthropogenic HCs, including 10 aromatics and linear alkanes with different carbon lengths. The atmospheric processes of biogenic HCs (isoprene, terpenes, and sesquiterpene) were simulated for major oxidation paths (ozone, OH radicals, and nitrate radicals) to predict day and night SOA formation. The UNIPAR model streamlined the multiphase partitioning of the lumping species originating from semi-explicitly predicted gas products and their heterogeneous chemistry to form non-volatile oligomeric species in both organic aerosol and inorganic aqueous phase. The CAMx–UNIPAR model predicted SOA formation at four ground urban sites (San Jose, Sacramento, Fresno, and Bakersfield) in California, United States, during wintertime 2018. Overall, the simulated mass concentrations of the total organic matter, consisting of primary organic aerosol and SOA, showed a good agreement with the observations. The simulated SOA mass in the urban areas of California was predominated by alkane and terpene oxidation products. During the daytime, low-volatility products originating from the autoxidation of long-chain alkanes considerably contributed to the SOA mass. In contrast, a significant amount of nighttime SOA was produced by the reaction of terpene with ozone or nitrate radicals. The spatial distributions of anthropogenic SOA associated with aromatic and alkane HCs were noticeably affected by the southward wind direction, owing to the relatively long lifetime of their atmospheric oxidation, whereas those of biogenic SOA were nearly insensitive to wind direction. During wintertime 2018, the impact of inorganic aerosol hygroscopicity on the total SOA budget was not evident because of the small contribution of aromatic and isoprene products, which are hydrophilic and reactive in the inorganic aqueous phase. However, an increased isoprene SOA mass was predicted during the wet periods, although its contribution to the total SOA was little.

Effects of simulated secondary organic aerosol water on PM1 levels and composition over the US

Abstract. Water is a key component of atmospheric aerosol, affecting many aerosol processes including gas-to-particle partitioning of semi-volatile compounds. Water related to secondary organic aerosol (SOAW) is often neglected in atmospheric chemical transport models and is not considered in gas-to-particle partitioning calculations for inorganic species. We use a new inorganic aerosol thermodynamics model, ISORROPIA-lite, which considers the effects of SOAW, to perform chemical transport model simulations for 1 year over the continental United States to quantify its effects on aerosol mass concentration and composition. SOAW can increase average fine aerosol water levels by up to a factor of 2 when secondary organic aerosol (SOA) is a major PM1 component. This is often the case in the south-eastern US, where SOA concentrations are higher. Although the annual average impact of this added water on total dry PM1 concentrations due to increased partitioning of nitrate and ammonium is small (up to 0.1 µg m−3), total dry PM1 increases of up to 2 µg m−3 (with nitrate levels increases of up to 200 %) can occur when RH levels and PM1 concentrations are high.

Suppression of the phenolic SOA formation in the presence of electrolytic inorganic seed

Phenolic compounds are largely attributed to wildfire gases and rapidly react with atmospheric oxidants to form persistent phenoxy free radicals, which influence atmospheric chemistry and secondary organic aerosol (SOA) formation. In this study, phenol or o-cresol was photochemically oxidized under various conditions (NOx levels, humidity, and seed conditions) in an outdoor photochemical reactor. Unexpectedly, SOA growth of both phenols was suppressed in the presence of salted aqueous aerosol compared to non-seed SOA. This discovery is different from the typical SOA formation of aromatic or biogenic hydrocarbons, which show noticeably higher SOA yields via organic aqueous reactions. Phenol, o-cresol, and their phenolic products (e.g., catechols) are absorbed in aqueous aerosol and form phenoxy radicals via heterogeneous reactions under sunlight. The resulting phenoxy radicals are redistributed between the gas and particle phases. Gaseous phenoxy radicals quickly react with ozone to form phenyl peroxide radicals and regenerated through a NOx cycle to retard phenol oxidation and SOA formation. The explicit oxidation mechanisms of phenol or o-cresol in the absence of aqueous phase were derived including the Master Chemical Mechanism (MCM v3.3.1) and the path for peroxy radical adducts originating from the addition of an OH radical to phenols to form low volatility products (e.g., multi-hydroxy aromatics). The resulting gas mechanisms of phenol or o-cresol were, then, applied to the Unified Partitioning Aerosol Phase Reaction (UNIPAR) model to predict SOA formation via multiphase partitioning of organics and aerosol-phase oligomerization. The model well simulated chamber-generated phenolic SOA in absence of wet-inorganic seed, but significantly overestimated SOA mass in presence of wet seed. This study suggests that heterogeneous chemistry to form phenoxy radicals needs to be included to improve SOA prediction from phenols. The suppression of atmospheric oxidation due to phenoxy radicals in wet inorganic aerosol can explain the low SOA formation during wildfire episodes.

Secondary organic aerosol formation and source contributions over east China in summertime

Various precursor emissions and chemical mechanisms for secondary organic aerosol (SOA) formation were incorporated into a regional air quality model system (RAQMS) and applied to investigate the distribution, composition, and source contribution of SOA over east China in summer 2018. Model comparison against a variety of observations at a national scale demonstrated that the model was able to reasonably reproduce meteorological variables, O3 and PM2.5 concentrations, and the model simulated SOA concentration generally agreed with observations, with the overall NMB of 7.0% and R of 0.4 in 10 cities over east China. The simulated period-mean SOA concentrations of 4–15 μg m−3 were mainly distributed over the North China Plain (NCP), the middle and lower reaches of the Yangtze River and Chongqing district. SOA dominated organic aerosol (OA) over China in summertime (90%). The percentage contributions to SOA from ASOA (SOA produced from anthropogenic volatile organic compounds (AVOC)), BSOA (SOA produced from biogenic volatile organic compounds (BVOC)), DSOA (SOA produced from aqueous uptake of glyoxal and methylglyoxal) and S/I-SOA (SOA produced from semi-volatile and intermediate volatile organic compounds) were estimated to be 48.3%, 28.6%, 14.3%, and 8.8% respectively, over east China in summertime. In terms of domain and period average, ASOA contributed most to SOA (59%) in north China, while BSOA contributed most to SOA (37.3%) in northeast China. The percentage contribution of DSOA to SOA reached 21.5% in southwest China. S/I-SOA accounted for approximately 10% of SOA in most areas of east China. This study reveals that while AVOC dominates SOA formation on average over east China, the SOA source contributions differ considerably in different regions of China. BVOC makes the same contribution to SOA formation as AVOC in northeast China and southwest China, where forest coverage and BVOC emission are higher and anthropogenic emissions are relatively low, highlighting the significant role of BVOC in summer SOA formation in China.

Evaluation of Secondary Organic Aerosol (SOA) Simulations for Seoul, Korea

AbstractOrganic aerosols (OA) represent a significant fraction of total submicron particulate matter (PM1) concentrations globally, including densely populated megacities such as Seoul. However, scientific understanding of the atmospheric formation and removal processes of OA, especially for secondary organic aerosols (SOA), is still highly uncertain. In this study, we examine the characteristics of SOA formation in Seoul during spring‐summer 2016 and fall‐winter 2017/2018, using airborne and ground observations along with a 3‐D global chemical transport model, GEOS‐Chem. We use four different SOA schemes in the model, including simplified and complex volatility‐based frameworks, and evaluate them by comparing the simulations with the observations to examine how our scientific understanding embedded in each SOA scheme affects the observed biases. Our analysis of the model performance of each scheme also provides the most suitable approach in simulating SOA in a typical urban environment. Comparisons of the simulated versus observed OA concentrations show that model biases range from −72% to +118%, with considerable variability among different schemes and seasons. We find that the inclusion of semi/intermediate volatile precursors, in addition to the traditional precursors, and chemical aging (functionalization) are important factors to simulate surface SOA concentrations in Seoul. However, a comparison of observed and simulated SOA/∆CO enhancement ratios suggests that most schemes underpredict SOA aging in upper levels in the boundary layer. We also find that the simplified SOA scheme can reproduce observed OA but often shows overestimation in surface air, indicating that uncertainties exist in bottom‐up emissions and precursor parameterization in Seoul.

Prediction of secondary organic aerosol from the multiphase reaction of gasoline vapor by using volatility–reactivity base lumping

Abstract. Heterogeneous chemistry of oxidized carbons in aerosol phase is known to significantly contribute to secondary organic aerosol (SOA) burdens. The UNIfied Partitioning Aerosol phase Reaction (UNIPAR) model was developed to process the multiphase chemistry of various oxygenated organics into SOA mass predictions in the presence of salted aqueous phase. In this study, the UNIPAR model simulated the SOA formation from gasoline fuel, which is a major contributor to the observed concentration of SOA in urban areas. The oxygenated products, predicted by the explicit mechanism, were lumped according to their volatility and reactivity and linked to stoichiometric coefficients which were dynamically constructed by predetermined mathematical equations at different NOx levels and degrees of gas aging. To improve the model feasibility in regional scales, the UNIPAR model was coupled with the Carbon Bond 6 (CB6r3) mechanism. CB6r3 estimated the hydrocarbon consumption and the concentration of radicals (i.e., RO2 and HO2) to process atmospheric aging of gas products. The organic species concentrations, estimated by stoichiometric coefficient array and the consumption of hydrocarbons, were applied to form gasoline SOA via multiphase partitioning and aerosol-phase reactions. To improve the gasoline SOA potential in ambient air, model parameters were also corrected for gas–wall partitioning (GWP). The simulated gasoline SOA mass was evaluated against observed data obtained in the University of Florida Atmospheric PHotochemical Outdoor Reactor (UF-APHOR) chamber under varying sunlight, NOx levels, aerosol acidity, humidity, temperature, and concentrations of aqueous salts and gasoline vapor. Overall, gasoline SOA was dominantly produced via aerosol-phase reaction, regardless of the seed conditions owing to heterogeneous reactions of reactive multifunctional organic products. Both the measured and simulated gasoline SOA was sensitive to seed conditions showing a significant increase in SOA mass with increasing aerosol acidity and water content. A considerable difference in SOA mass appeared between two inorganic aerosol states (dry aerosol vs. wet aerosol) suggesting a large difference in SOA formation potential between arid (western United States) and humid regions (eastern United States). Additionally, aqueous reactions of organic products increased the sensitivity of gasoline SOA formation to NOx levels as well as temperature. The impact of the chamber wall on SOA formation was generally significant, and it appeared to be higher in the absence of wet salts. Based on the evaluation of UNIPAR against chamber data from 10 aromatic hydrocarbons and gasoline fuel, we conclude that the UNIPAR model with both heterogeneous reactions and the model parameters corrected for GWP can improve the ability to accurately estimate SOA mass in regional scales.

Global Distribution of the Phase State and Mixing Times within Secondary Organic Aerosol Particles in the Troposphere Based on Room-Temperature Viscosity Measurements

Information on the global distributions of secondary organic aerosol (SOA) phase state and mixing times within SOA is needed to predict the impact of SOA on air quality, climate, and atmospheric chemistry; nevertheless, such information is rare. In this study, we developed parameterizations for viscosity as a function of relative humidity (RH) and temperature based on room-temperature viscosity data for simulated pine tree SOA and toluene SOA. The viscosity parameterizations were then used together with tropospheric RH and temperature fields to predict the SOA phase state and mixing times of water and organic molecules within SOA in the troposphere for 200 nm particles. Based on our results, the glassy state can often occur, and the mixing times of water can often exceed 1 h within SOA at altitudes >6 km. Furthermore, the mixing times of organic molecules within SOA can often exceed 1 h throughout most of the free troposphere (i.e., ≳1 km in altitude). In most of the planetary boundary layer (i.e., ≲1 km in altitude), the glassy state is not important, and the mixing times of water and organic molecules are less than 1 h. Our results are qualitatively consistent with the results from Shiraiwa et al. (Nat. Commun., 2017), although there are quantitative differences. Additional studies are needed to better understand the reasons for these differences.

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.

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.

Simulating the impact of gas-wall partitioning on SOA formation using the explicit gas mechanism integrated with aqueous reactions containing electrolytes

The impact of the Teflon reactor wall on secondary organic aerosol (SOA) formation was explicitly simulated by using the Unified Partitioning Aerosol Phase Reaction (UNIPAR) model integrated with gas-wall partitioning (GWP). The formation of oxygenated semivolatile organic compounds (SVOCs) from the photooxidation of hydrocarbons (HC) was simulated by using an explicit gas-kinetic mechanism (MCM V3.3.1). In the model, SVOC's GWP and gas-particle partitioning onto preexisting particulate matter were kinetically treated with the absorption and desorption processes. The UNIPAR model streamlined aerosol growth via the oligomerization of reactive SVOCs in the organic phase and aqueous reactions in the inorganic phase. Two important GWP parameters, GWP coefficient (Kw, i) and the deposition rate constant (k_onw, i) of SVOCs (i) to the wall were predicted by using a quantitative structure activity relationship (QSAR) employing SVOCs' physicochemical descriptors. This GWP model was then incorporated with the UNIPAR model in the DSMACC-KPP platform and simulated SOA chamber data. The three different HCs (toluene, 1,3,5-trimethylbenzene, and α-pinene) were photochemically oxidized in the presence of NOx and inorganic seed aerosols in an outdoor photochemical smog chamber (UF-APHOR). The impact of GWP on SOA mass varied ranging from 9% to 71% with HCs, seed conditions, NOx, and temperature. Toluene SOA in the absence of inorganic aerosol was the most sensitive to GWP. However, in the presence of wet-inorganic seed, the impact of GWP on SOA was smaller than that of non-seed SOA owing to rapid reactions of organic species in the aqueous phase. SOA mass can be significantly underestimated in the absence of wet-inorganic seed when the aerosol model employs parameters derived using SOA data with GWP artifacts.

Numerical Sensitivity Tests of Volatile Organic Compounds Emission to PM2.5 Formation during Heat Wave Period in 2018 in Two Southeast Korean Cities

A record-breaking severe heat wave was recorded in southeast Korea from 11 July to 15 August 2018, and the numerical sensitivity simulations of volatile organic compound (VOC) to secondarily generated particulate matter with diameter of less than 2.5 µm (PM2.5) concentrations were studied in the Busan and Ulsan metropolitan areas in southeast Korea. A weather research and forecasting (WRF) model coupled with chemistry (WRF-Chem) was employed, and we carried out VOC emission sensitivity simulations to investigate variations in PM2.5 concentrations during the heat wave period that occurred from 11 July to 15 August 2018. In our study, when anthropogenic VOC emissions from the Comprehensive Regional Emissions Inventory for Atmospheric Transport Experiment-2015 (CREATE-2015) inventory were increased by approximately a factor of five in southeast Korea, a better agreement with observations of PM2.5 mass concentrations was simulated, implying an underestimation of anthropogenic VOC emissions over southeast Korea. The simulated secondary organic aerosol (SOA) fraction, in particular, showed greater dominance during high temperature periods such as 19–21 July, 2018, with the SOA fractions of 42.3% (in Busan) and 34.3% (in Ulsan) among a sub-total of seven inorganic and organic components. This is considerably higher than observed annual mean organic carbon (OC) fraction (28.4 ± 4%) among seven components, indicating the enhancement of secondary organic aerosols induced by photochemical reactions during the heat wave period in both metropolitan areas. The PM2.5 to PM10 ratios were 0.69 and 0.74, on average, during the study period in the two cities. These were also significantly higher than the typical range in those cities, which was 0.5–0.6 in 2018. Our simulations implied that extremely high temperatures with no precipitation are significantly important to the secondary generation of PM2.5 with higher secondary organic aerosol fraction via photochemical reactions in southeastern Korean cities. Other possible relationships between anthropogenic VOC emissions and temperature during the heat wave episode are also discussed in this study.

Model-simulated Source Contributions to PM2.5 in Santiago and the Central Region of Chile

The contributions to PM2.5 from different emission sectors across central Chile and the Santiago metropolitan area during summer/fall and winter have been evaluated using a chemical transport model. The simulations generally underestimate the mean PM2.5 concentrations compared to measurements conducted at stations in Santiago that belong to the Chilean National Air Quality Information System (SINCA). The potential reasons for this discrepancy include underestimated direct PM2.5 emissions, missing emissions for semi- and intermediately volatile organic compounds (SVOCs and IVOCs) and overestimated wind speeds in the simulations. The simulated winter PM2.5 concentrations in Santiago are lower and higher than the values observed during nighttime, and daytime and late evening, respectively, which may be related to excessive simulated wind speeds, as well as to uncertainties in the diurnal variation in the emissions. During summer/fall, the simulated diurnal variation better agrees with the observations, but the peak concentrations during the morning are underestimated, whereas those during the evening are overestimated. The simulated contributions of different aerosol components to the PM2.5 at one station in Santiago are all lower than the observed values, except for elemental carbon equivalent black carbon (BCe) , which exhibit comparable or higher levels in the simulations. The absolute differences are the largest for the total organic matter, whereas the relative differences are the largest for BCe and ammonium. The simulated sector contributions indicate that emissions originating from transport and construction machinery dominate the PM2.5 in Santiago; however, residential wood combustion is the primary source in other urban areas of central Chile, except near major point sources. Away from urban areas, traffic routes and major industrial sources, secondary inorganic aerosol (SIA) is estimated to be the largest component of the aerosol, whereas the simulated secondary organic aerosol (SOA) only contributes a small fraction.

The formation and evolution of secondary organic aerosol during haze events in Beijing in wintertime

A regional air quality model system (RAQMS) with a volatility basis set approach for secondary organic aerosol (SOA) formation and an emission inventory of semi-volatile (SVOC) and intermediate volatile organic compounds (IVOC) are applied to investigate the distribution and evolution of organic aerosols over the Beijing-Tianjin-Hebei (BTH) region in winter 2014, with focus on Beijing. Model validation demonstrates the model is capable of reproducing meteorological variables and major aerosol components, and the model significantly improves SOA and organic aerosol (OA) simulations by taking S/IVOCs (SVOC + IVOC) and relevant aging processes into account. SVOC and IVOC emissions in the BTH region are estimated to be 0.47 Tg and in a range of 0.09–0.36 Tg, respectively, which are about 18% and 4–14% of the emission amounts of volatile organic compounds (VOCs). The distribution of mean organic aerosols is characterized by a high concentration belt oriented southwest-northeast from southern Hebei to Beijing, with the maximum concentration up to 50 μg m−3 in Beijing and Shijiazhuang. The simulated SOA concentration is comparable in magnitude to primary organic aerosol (POA) concentration, and the SOA/OA ratio is around 50% in most areas of the BTH region. In terms of domain average, the percentage contributions to SOA mass concentration from anthropogenic volatile organic compounds (AVOCs), SVOCs, IVOCs and biogenic VOCs are estimated to be 46.1%, 40.1%, 9.4% and 4.4%, respectively, in the BTH region during the study period, which indicates an important role of S/IVOCs in SOA formation. From clean to haze periods, both POA and SOA concentrations apparently increase, with an increasing (decreasing) trend of the SOA/OA (POA/OA) ratio. SOA dominates over POA in fine organic aerosols during the haze periods. The increase of POA in hazy days is mainly due to the weakened vertical diffusion and accumulation near the surface, whereas the increase of SOA is likely attributed to both the reduced diffusivity and a series of competing chemical processes, in which the decreased photolysis rate by aerosol attenuation tends to decrease SOA concentration by about 6% during the most severe haze day, whereas the lower surface air temperature and higher POA and S/IVOC concentrations in haze days both enhance gas to particle partition, and consequently lead to higher SOA concentration.

The roles of volatile organic compound deposition and oxidation mechanisms in determining secondary organic aerosol production: a global perspective using the UKCA chemistry–climate model (vn8.4)

Abstract. The representation of volatile organic compound (VOC) deposition and oxidation mechanisms in the context of secondary organic aerosol (SOA) formation are developed in the United Kingdom Chemistry and Aerosol (UKCA) chemistry–climate model. Impacts of these developments on both the global SOA budget and model agreement with observations are quantified. Firstly, global model simulations were performed with varying VOC dry deposition and wet deposition fluxes. Including VOC dry deposition reduces the global annual-total SOA production rate by 2 %–32 %, with the range reflecting uncertainties in surface resistances. Including VOC wet deposition reduces the global annual-total SOA production rate by 15 % and is relatively insensitive to changes in effective Henry's law coefficients. Without precursor deposition, simulated SOA concentrations are lower than observed with a normalised mean bias (NMB) of −51 %. Hence, including SOA precursor deposition worsens model agreement with observations even further (NMB =-66 %). Secondly, for the anthropogenic and biomass burning VOC precursors of SOA (VOCANT∕BB), model simulations were performed by (a) varying the parent hydrocarbon reactivity, (b) varying the number of reaction intermediates, and (c) accounting for differences in volatility between oxidation products from various pathways. These changes were compared to a scheme where VOCANT∕BB adopts the reactivity of a monoterpene (α-pinene), and is oxidised in a single-step mechanism with a fixed SOA yield. By using the chemical reactivity of either benzene, toluene, or naphthalene for VOCANT∕BB, the global annual-total VOCANT∕BB oxidation rate changes by −3 %, −31 %, or −66 %, respectively, compared to when using α-pinene. Increasing the number of reaction intermediates, by introducing a peroxy radical (RO2), slightly slows the rate of SOA formation, but has no impact on the global annual-total SOA production rate. However, RO2 undergoes competitive oxidation reactions, forming products with substantially different volatilities. Accounting for the differences in product volatility between RO2 oxidation pathways increases the global SOA production rate by 153 % compared to using a single SOA yield. Overall, for relatively reactive compounds such as toluene and naphthalene, the reduction in reactivity for VOCANT∕BB oxidation is outweighed by accounting for the difference in volatility of RO2 products, leading to a net increase in the global annual-total SOA production rate of 85 % and 145 %, respectively, and improvements in model agreement (NMB of −46 % and 56 %, respectively). However, for benzene, the reduction in VOCANT∕BB oxidation is not outweighed by accounting for the difference in SOA yield pathways, leading to a small change in the global annual-total SOA production rate of −3 %, and a slight worsening of model agreement with observations (NMB =-77 %). These results highlight that variations in both VOC deposition and oxidation mechanisms contribute to substantial uncertainties in the global SOA budget and model agreement with observations.

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.

Investigating secondary organic aerosol formation pathways in China during 2014

The concentrations of organic aerosol (OA) in central and eastern China are much higher than those in Europe and North America. Compared with observations, recent numerical modeling studies have largely underestimated the concentrations of OA, especially the secondary components. Based on the volatility basis set framework, a secondary OA (SOA) module is developed and coupled into the nested air quality prediction modeling system (NAQPMS). This model is applied to investigate the concentration and formation pathways of SOA in central and eastern China during 2014, and the simulation performance is validated through observation. The oxidation of intermediate volatile organic compounds (IVOCs) is significant to SOA formation and could reduce the great discrepancy between simulations and observations. In winter, the contribution of IVOCs accounted for 60%–80% of SOA formation. In spring and autumn, IVOCs and volatile organic compounds (VOCs) have a considerable effect on SOA formation. In summer, the contributions of VOCs reach 40%–60% due to an increase in the emissions of biogenic VOCs. The mass yields and other parameters of IVOCs remain largely uncertain. By using the latest mass yields obtained from chamber experiments, the simulated SOA concentrations in winter increase by 10–20 μg m−3 compared with the base scenario. To more thoroughly understand SOA formation in China, further research on the emission sources and mass yields of IVOCs is warranted.

Composition and light absorption of N-containing aromatic compounds in organic aerosols from laboratory biomass burning.

This study seeks to understand the compositional details of N-containing aromatic compounds (NACs) emitted during biomass burning (BB) and their contribution to light-absorbing organic carbon (OC), also termed brown carbon (BrC). Three laboratory BB experiments were conducted with two U.S. pine forest understory fuels typical of those consumed during prescribed fires. During the experiments, submicron aerosol particles were collected on filter media and subsequently extracted with methanol and examined for their optical and chemical properties. Significant correlations (p < 0.05) were observed between BrC absorption and elemental carbon (EC)/OC ratios for individual burns data. However, the pooled experimental data indicated that the BB BrC absorption depends on more than the BB fire conditions as represented by the EC/OC ratio. Fourteen NAC formulas were identified in the BB samples, most of which were also observed in simulated secondary organic aerosol (SOA) from photo-oxidation of aromatic VOCs with NOX. However, the molecular structures associated with the identical NAC formula from BB and SOA are different. In this work, the identified NACs from BB are featured by methoxy and cyanate groups, and are predominately generated during the flaming phase. The mass concentrations of identified NACs were quantified using authentic and surrogate standards, and their contributions to bulk light absorption of solvent extractable OC were also calculated. The contributions of identified NACs to organic matter (OM) and BrC absorption were significantly higher in flaming-phase samples than those in smoldering-phase samples, and correlated with EC/OC ratio (p < 0.05) for both individual burns and pooled experimental data, indicating that the formation of NACs from BB largely depends on burn conditions. The average contributions of identified NACs to overall BrC absorption at 365 nm ranged from 0.087 ± 0.024 to 1.22 ± 0.54%, 3 - 10 times higher than their mass contributions to OM (0.023 ± 0.0089 to 0.18 ± 0.067%), so the NACs with light absorption identified in this work from BB are likely strong BrC chromophores. Further studies are warranted to identify more light-absorbing compounds to explain the unknown fraction (> 98%) of BB BrC absorption.

The impact of biogenic, anthropogenic, and biomass burning volatile organic compound emissions on regional and seasonal variations in secondary organic aerosol

Abstract. The global secondary organic aerosol (SOA) budget is highly uncertain, with global annual SOA production rates, estimated from global models, ranging over an order of magnitude and simulated SOA concentrations underestimated compared to observations. In this study, we use a global composition-climate model (UKCA) with interactive chemistry and aerosol microphysics to provide an in-depth analysis of the impact of each VOC source on the global SOA budget and its seasonality. We further quantify the role of each source on SOA spatial distributions, and evaluate simulated seasonal SOA concentrations against a comprehensive set of observations. The annual global SOA production rates from monoterpene, isoprene, biomass burning, and anthropogenic precursor sources is 19.9, 19.6, 9.5, and 24.6 Tg (SOA) a−1, respectively. When all sources are included, the SOA production rate from all sources is 73.6 Tg (SOA) a−1, which lies within the range of estimates from previous modelling studies. SOA production rates and SOA burdens from biogenic and biomass burning SOA sources peak during Northern Hemisphere (NH) summer. In contrast, the anthropogenic SOA production rate is fairly constant all year round. However, the global anthropogenic SOA burden does have a seasonal cycle which is lowest during NH summer, which is probably due to enhanced wet removal. Inclusion of the new SOA sources also accelerates the ageing by condensation of primary organic aerosol (POA), making it more hydrophilic, leading to a reduction in the POA lifetime. With monoterpene as the only source of SOA, simulated SOA and total organic aerosol (OA) concentrations are underestimated by the model when compared to surface and aircraft measurements. Model agreement with observations improves with all new sources added, primarily due to the inclusion of the anthropogenic source of SOA, although a negative bias remains. A further sensitivity simulation was performed with an increased anthropogenic SOA reaction yield, corresponding to an annual global SOA production rate of 70.0 Tg (SOA) a−1. Whilst simulated SOA concentrations improved relative to observations, they were still underestimated in urban environments and overestimated further downwind and in remote environments. In contrast, the inclusion of SOA from isoprene and biomass burning did not improve model–observations biases substantially except at one out of two tropical locations. However, these findings may reflect the very limited availability of observations to evaluate the model, which are primarily located in the NH mid-latitudes where anthropogenic emissions are high. Our results highlight that, within the current uncertainty limits in SOA sources and reaction yields, over the NH mid-latitudes, a large anthropogenic SOA source results in good agreement with observations. However, more observations are needed to establish the importance of biomass burning and biogenic sources of SOA in model agreement with observations.