Simulated Secondary Organic Aerosol Concentrations Research Articles

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.

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.

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.

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.

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.

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%.

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses

Abstract. The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with “low” and one with “high” vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of ∼ 2–5 for the low and ∼ 5–10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from ∼ 0.2 (no) to ∼ 0.5 (low) and to ∼ 0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA ∕ ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA ∕ ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model–measurement discrepancies.

Secondary organic aerosol model intercomparison based on secondary organic aerosol to odd oxygen ratio in Tokyo

AbstractImprovement of secondary organic aerosol (SOA) models is critical for accurate understanding of the behavior and sources of atmospheric aerosols. Over the last decade, a number of SOA production pathways were discovered, and several new SOA models have been developed. However, few comparative studies of the performances of the various SOA models have been conducted. In this study, simulation data obtained with five SOA models (two yield models, a volatility basis set (VBS) model, a mechanistic model, and a near‐explicit model) were compared. The performances of the models were evaluated by comparison of the simulated data with observed ratios of the SOA concentration to odd oxygen concentration ([SOA]/[Ox], where [Ox] = [O3] + [NO2]) in the Tokyo metropolitan area. In Tokyo, SOA concentrations have been shown to correlate well with Ox concentrations; thus, Tokyo is an appropriate location for this intercomparison study. All five models showed similar results for the concentrations of gaseous species, including ozone, reactive nitrogen, hydroxy radicals, and volatile organic compounds. In contrast, the simulated SOA concentrations varied substantially among the five models. The VBS model reproduced the observed [SOA]/[Ox] ratio well, whereas the other four models substantially underestimated the ratio. The sensitivity of the ratio to various input parameters differed substantially among the models, as did the volatility distribution of SOA and the source contributions of SOA, suggesting that the choice of SOA model is critical for accurate assessment of the atmospheric behavior and sources of SOA.

Improving the representation of secondary organic aerosol (SOA) in the MOZART-4 global chemical transport model

Abstract. The secondary organic aerosol (SOA) module in the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) was updated by replacing existing two-product (2p) parameters with those obtained from two-product volatility basis set (2p-VBS) fits (MZ4-C1), and by treating SOA formation from the following additional volatile organic compounds (VOCs): isoprene, propene and lumped alkenes (MZ4-C2). Strong seasonal and spatial variations in global SOA distributions were demonstrated, with significant differences in the predicted concentrations between the base case and updated model simulations. Updates to the model resulted in significant increases in annual average SOA mass concentrations, particularly for the MZ4-C2 simulation in which the additional SOA precursor VOCs were treated. Annual average SOA concentrations predicted by the MZ4-C2 simulation were 1.00 ± 1.04 μg m−3 in South America, 1.57 ± 1.88 μg m−3 in Indonesia, 0.37 ± 0.27 μg m−3 in the USA, and 0.47 ± 0.29 μg m−3 in Europe with corresponding increases of 178, 406, 311 and 292% over the base-case simulation, respectively, primarily due to inclusion of isoprene. The increases in predicted SOA mass concentrations resulted in corresponding increases in SOA contributions to annual average total aerosol optical depth (AOD) by ~ 1–6%. Estimated global SOA production was 5.8, 6.6 and 19.1 Tg yr−1 with corresponding burdens of 0.22, 0.24 and 0.59 Tg for the base-case, MZ4-C1 and MZ4-C2 simulations, respectively. The predicted SOA budgets fell well within reported ranges for comparable modeling studies, 6.7 to 96 Tg yr−1, but were lower than recently reported observationally constrained values, 50 to 380 Tg yr−1. For MZ4-C2, simulated SOA concentrations at the surface also were in reasonable agreement with comparable modeling studies and observations. Total organic aerosol (OA) mass concentrations at the surface, however, were slightly over-predicted in Europe, Amazonian regions and Malaysian Borneo (Southeast Asia) during certain months of the year, and under-predicted in most sites in Asia; relative to those regions, the model performed better for sites in North America. Overall, with the inclusion of additional SOA precursors (MZ4-C2), namely isoprene, MOZART-4 showed consistently better skill (NMB (normalized mean bias) of −11 vs. −26%) in predicting total OA levels and spatial distributions of SOA as compared with unmodified MOZART-4. Treatment of SOA formation by these known precursors (isoprene, propene and lumped alkenes) may be particularly important when MOZART-4 output is used to generate boundary conditions for regional air quality simulations that require more accurate representation of SOA concentrations and distributions.

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.

Explicit modelling of SOA formation from α-pinene photooxidation: sensitivity to vapour pressure estimation

Abstract. The sensitivity of the formation of secondary organic aerosol (SOA) to the estimated vapour pressures of the condensable oxidation products is explored. A highly detailed reaction scheme was generated for α-pinene photooxidation using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). Vapour pressures (Pvap) were estimated with three commonly used structure activity relationships. The values of Pvap were compared for the set of secondary species generated by GECKO-A to describe α-pinene oxidation. Discrepancies in the predicted vapour pressures were found to increase with the number of functional groups borne by the species. For semi-volatile organic compounds (i.e. organic species of interest for SOA formation), differences in the predicted Pvap range between a factor of 5 to 200 on average. The simulated SOA concentrations were compared to SOA observations in the Caltech chamber during three experiments performed under a range of NOx conditions. While the model captures the qualitative features of SOA formation for the chamber experiments, SOA concentrations are systematically overestimated. For the conditions simulated, the modelled SOA speciation appears to be rather insensitive to the Pvap estimation method.