Volatility Basis Set Approach Research Articles

Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator

Abstract. The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

Simulation of the cooking organic aerosol concentration variability in an urban area

Cooking activities are a source of urban air pollution that has been often ignored. The corresponding particulate matter (PM) emissions are not included or are seriously underestimated in urban emission inventories. However, several field studies suggest that cooking organic aerosol (COA) can be an important component of the organic PM in urban areas. In this study we propose and evaluate a methodology for the simulation of the COA concentration and its variability in space and time in an urban area. The city of Patras, the third biggest in Greece, is used for this first application during a typical late summer period.The spatial distribution of COA emissions was based on the exact location of restaurants and grills, while the emission rates on the per person meat consumption in Greece. We estimated COA emissions of 0.6 g d−1 per person that corresponds to 150 kg d−1 for Patras. The temporal distribution of COA emissions was based on the known cooking times and the results of past field studies in the area. We estimated that half of the daily COA is emitted during dinner time (21:00–0:00 LT), while approximately 25% during lunch time (13:00–16:00 LT). The COA is simulated using the Volatility Basis Set approach and is treated as semivolatile and reactive. Its volatility distribution is based on laboratory measurements of COA from meat grilling.The chemical transport model PMCAMx predicts that the COA concentration reaches values up to 15 μg m−3 during the nights of the simulated summertime period in an area with high restaurant density. The average predicted COA concentration is around 1.2 μg m−3 in the center and 0.1–0.2 μg m−3 in the suburbs of the city. COA has a distinct daily profile that peaks during lunch (13:00–15:00 LT) and dinner (21:00–23:00 LT) periods. The local production of secondary COA is predicted to be slow and it represents just a few percent of the total COA. The model reproduces well the average PM2.5 concentrations at the outskirts of Patras and its overall performance for hourly PM2.5 values is rated as good. A 50% uncertainty of the reported COA emissions is estimated based on the results of the sensitivity tests and the observations in the city core. The emissions can be further constrained and the corresponding uncertainty can be further reduced with measurements focusing on COA and not on total PM2.5 as was the case in this study. These should take place in different areas of the city, selected based on the model predictions, to also improve our estimates of the spatial distribution of the emissions.

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.

Evaluation of European air quality modelled by CAMx including the volatility basis set scheme

Abstract. Four periods of EMEP (European Monitoring and Evaluation Programme) intensive measurement campaigns (June 2006, January 2007, September–October 2008 and February–March 2009) were modelled using the regional air quality model CAMx with VBS (volatility basis set) approach for the first time in Europe within the framework of the EURODELTA-III model intercomparison exercise. More detailed analysis and sensitivity tests were performed for the period of February–March 2009 and June 2006 to investigate the uncertainties in emissions as well as to improve the modelling of organic aerosol (OA). Model performance for selected gas phase species and PM2.5 was evaluated using the European air quality database AirBase. Sulfur dioxide (SO2) and ozone (O3) were found to be overestimated for all the four periods, with O3 having the largest mean bias during June 2006 and January–February 2007 periods (8.9 pbb and 12.3 ppb mean biases respectively). In contrast, nitrogen dioxide (NO2) and carbon monoxide (CO) were found to be underestimated for all the four periods. CAMx reproduced both total concentrations and monthly variations of PM2.5 for all the four periods with average biases ranging from −2.1 to 1.0 µg m−3. Comparisons with AMS (aerosol mass spectrometer) measurements at different sites in Europe during February–March 2009 showed that in general the model overpredicts the inorganic aerosol fraction and underpredicts the organic one, such that the good agreement for PM2.5 is partly due to compensation of errors. The effect of the choice of VBS scheme on OA was investigated as well. Two sensitivity tests with volatility distributions based on previous chamber and ambient measurements data were performed. For February–March 2009 the chamber case reduced the total OA concentrations by about 42 % on average. In contrast, a test based on ambient measurement data increased OA concentrations by about 42 % for the same period bringing model and observations into better agreement. Comparison with the AMS data at the rural Swiss site Payerne in June 2006 shows no significant improvement in modelled OA concentration. Further sensitivity tests with increased biogenic and anthropogenic emissions suggest that OA in Payerne was affected by changes in emissions from residential heating during the February–March 2009 whereas it was more sensitive to biogenic precursors in June 2006.

Evaluation of Aerosol Chemical Composition Simulations by the WRF-Chem Model at the Puy de Dôme Station (France)

ABSTRACTThe high altitude Puy de Dome (PUY) research station, located at 1465 m a.s.l. in central France, hosts many instruments allowing continuous measurements and intensive campaigns to measure meteorological parameters, gas-phase species, aerosol and cloud properties. Aerosol chemical composition measurements provided by a compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS) are used to evaluate the WRF-Chem model and more precisely its ability to simulate organic aerosol (OA) for a particular event in summer 2010. Using the Volatility Basis Set approach (VBS), dedicated to the formation of secondary organic aerosol (SOA), the WRF-Chem model strongly underestimates the high concentration levels of OA observed at the PUY station: 12.5 µg m–3 were observed and only 2.6 µg m–3 were simulated. By means of several measurements of gas-phase volatile organic compounds (VOCs), the robustness of both emissions and SOA formation processes in the WRF-Chem model was tested. The underestimation of the OA mass concentration appears to be mainly due to a misrepresentation of the oxidation rate of the organic condensable vapours (OCVs) and the SOA yields of both anthropogenic and biogenic VOCs in the VBS parameterization.

A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data

Abstract. A parameterization for secondary organic aerosol (SOA) production based on the volatility basis set (VBS) approach has been coupled with microphysics and radiative schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) model. The new chemistry option called "RACM-MADE-VBS-AQCHEM" was evaluated on a cloud resolving scale against ground-based and aircraft measurements collected during the IMPACT-EUCAARI (Intensive Cloud Aerosol Measurement Campaign – European Integrated project on Aerosol Cloud Climate and Air quality interaction) campaign, and complemented with satellite data from MODIS. The day-to-day variability and the diurnal cycle of ozone (O3) and nitrogen oxides (NOx) at the surface are captured by the model. Surface aerosol mass concentrations of sulfate (SO4), nitrate (NO3), ammonium (NH4), and organic matter (OM) are simulated with correlations larger than 0.55. WRF-Chem captures the vertical profile of the aerosol mass concentration in both the planetary boundary layer (PBL) and free troposphere (FT) as a function of the synoptic condition, but the model does not capture the full range of the measured concentrations. Predicted OM concentration is at the lower end of the observed mass concentrations. The bias may be attributable to the missing aqueous chemistry processes of organic compounds and to uncertainties in meteorological fields. A key role could be played by assumptions on the VBS approach such as the SOA formation pathways, oxidation rate, and dry deposition velocity of organic condensable vapours. Another source of error in simulating SOA is the uncertainties in the anthropogenic emissions of primary organic carbon. Aerosol particle number concentration (condensation nuclei, CN) is overestimated by a factor of 1.4 and 1.7 within the PBL and FT, respectively. Model bias is most likely attributable to the uncertainties of primary particle emissions (mostly in the PBL) and to the nucleation rate. Simulated cloud condensation nuclei (CCN) are also overestimated, but the bias is more contained with respect to that of CN. The CCN efficiency, which is a characterization of the ability of aerosol particles to nucleate cloud droplets, is underestimated by a factor of 1.5 and 3.8 in the PBL and FT, respectively. The comparison with MODIS data shows that the model overestimates the aerosol optical thickness (AOT). The domain averages (for 1 day) are 0.38 ± 0.12 and 0.42 ± 0.10 for MODIS and WRF-Chem data, respectively. The droplet effective radius (Re) in liquid-phase clouds is underestimated by a factor of 1.5; the cloud liquid water path (LWP) is overestimated by a factor of 1.1–1.6. The consequence is the overestimation of average liquid cloud optical thickness (COT) from a few percent up to 42 %. The predicted cloud water path (CWP) in all phases displays a bias in the range +41–80 %, whereas the bias of COT is about 15 %. In sensitivity tests where we excluded SOA, the skills of the model in reproducing the observed patterns and average values of the microphysical and optical properties of liquid and all phase clouds decreases. Moreover, the run without SOA (NOSOA) shows convective clouds with an enhanced content of liquid and frozen hydrometers, and stronger updrafts and downdrafts. Considering that the previous version of WRF-Chem coupled with a modal aerosol module predicted very low SOA content (secondary organic aerosol model (SORGAM) mechanism) the new proposed option may lead to a better characterization of aerosol–cloud feedbacks.

Local and distant source contributions to secondary organic aerosol in the Beijing urban area in summer

Quantification of local and distant source contributions to particulate matter is a key issue to improving air quality in large urban areas, but few studies have focused on secondary organic aerosol (SOA) source contributions in a large area, especially in China. In this study, we extended the Comprehensive Air Quality Model with Extensions (CAMX) version 5.4, replacing the two-product approach by the volatility basis-set (VBS) approach, with updated SOA yields based on smog chamber studies. The modules related to the computationally efficient particulate source apportionment technology (PSAT) used in CAMX v5.4 were extended based on the volatility basis set (VBS) approach. The updated version of the CAMX model was then used to calculate the local and distant source contributions to SOA in Beijing for the first time. The results indicated that the VBS approach substantially improved hourly, daily, and monthly SOA simulations, compared with the two-product approach and the observations. In August 2007, the local source contributions to anthropogenic and biogenic SOA in Beijing were 23.8% and 16.6%, respectively; distant sources dominated for both anthropogenic and biogenic SOA in Beijing: Northern Hebei, Middle Hebei, Northeast China, Inner Mongolia, Shandong, and Tianjin (including Xianghe) contributed 5.1% e18.2% to anthropogenic SOA in Beijing; whereas, Inner Mongolia, Northern Hebei, and Northeast China contributed 12.2%, 18.6%, and 10.1%, respectively, to biogenic SOA in Beijing. Additionally, other areas outside China respectively contributed 5.3% and 10.8% to anthropogenic and biogenic SOA in Beijing: this could be related to strong summer monsoon.

Application of WRF/Chem over North America under the AQMEII Phase 2 – Part 2: Evaluation of 2010 application and responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) simulation with the 2005 Carbon Bond (CB05) gas-phase mechanism coupled to the Modal for Aerosol Dynamics for Europe (MADE) and the volatility basis set approach for secondary organic aerosol (SOA) are conducted over a domain in North America for 2006 and 2010 as part of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 project. Following the Part 1 paper that focuses on the evaluation of the 2006 simulations, this Part 2 paper focuses on a comparison of model performance in 2006 and 2010 as well as analysis of the responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010. In general, emissions for gaseous and aerosol species decrease from 2006 to 2010, leading to a reduction in gaseous and aerosol concentrations and associated changes in radiation and cloud variables due to various feedback mechanisms. WRF/Chem is able to reproduce most observations and the observed variation trends from 2006 to 2010, despite its slightly worse performance than WRF that is likely due to inaccurate chemistry feedbacks resulting from less accurate emissions and chemical boundary conditions (BCONs) in 2010. Compared to 2006, the performance for most meteorological variables in 2010 gives lower normalized mean biases but higher normalized mean errors and lower correlation coefficients. The model also shows poorer performance for most chemical variables in 2010. This could be attributed to underestimations in emissions of some species, such as primary organic aerosol in some areas of the US in 2010, and inaccurate chemical BCONs and meteorological predictions. The inclusion of chemical feedbacks in WRF/Chem reduces biases in meteorological predictions in 2010; however, it increases errors and weakens correlations comparing to WRF simulations. Sensitivity simulations show that the net changes in meteorological variables from 2006 to 2010 are mostly influenced by changes in meteorology and those of ozone and fine particulate matter are influenced to a large extent by emissions and/or chemical BCONs and to a lesser extent by changes in meteorology. Using a different set of emissions and/or chemical BCONs helps improve the performance of individual variables, although it does not improve the degree of agreement with observed interannual trends. These results indicate a need to further improve the accuracy and consistency of emissions and chemical BCONs, the representations of SOA and chemistry–meteorology feedbacks in the online-coupled models.

Modeling organic aerosols over east China using a volatility basis-set approach with aging mechanism in a regional air quality model

Abstract A volatility basis set approach with chemical aging mechanism has been incorporated into a regional air quality model system (RAQMS) and used to investigate the distribution of organic aerosols (OA) over east China in April 2009, with focus on secondary organic aerosols (SOA) in fine particle and relative contributions from a series of anthropogenic and biogenic VOC precursors. The comparison between the VBS approach prediction and observation at four sites in east China demonstrates a significant improvement in SOA and OA concentrations compared with the traditional two-product model, which predicts very low SOA level. The average value of secondary organic carbon (SOC) for all sites predicted by the VBS approach with chemical aging is 2.8 μgC m −3 , quite close to the estimated value of 3.3 μgC m −3 . The SOC fraction of organic carbon (OC) also increases from just 5% predicted by the two-product model to 33% by the VBS approach with aging, close to the estimated fraction of 32%, suggesting a more realistic and precise representation of SOA formation by the VBS approach. The enhanced SOC prediction further improve OC prediction, reducing the normalized mean bias from −43% to −18%. The VBS approach with aging predicts SOA concentration in PM 2.5 of 5–10 μg m −3 over most parts of east China. The predicted ASOA concentrations vary from 5.0 to 7.5 μg m −3 in the Pearl River Delta, the Yangtze River Delta and the wide areas north of the Yangtze River. BSOA is predicted to be 1.0–2.5 μg m −3 across the regions from southeast China to the middle reaches of the Yangtze River and the Yellow River. Prediction with the VBS approach exhibits that ASOA becomes dominant component of SOA, which is more realistic as compared to the BSOA dominance by the two-product model. The domain-average surface POA and SOA concentrations predicted by the VBS approach with aging over east China are 4.86 μg m −3 and 4.45 μg m −3 , with the SOA fraction of total OA and the ASOA fraction of SOA being 48% and 85%, respectively. This indicates the comparable contributions to OA from SOA and POA, and the predominant contribution of ASOA to SOA over east China in springtime. The mean SOA concentrations over east China produced from aromatics, alkanes, alkenes, isoprene, monoterpene and sesquiterpene are predicted to be 2.44, 0.57, 0.8, 0.17, 0.42 and 0.06 μg m −3 , respectively, which contribute 55%, 13%, 18%, 4%, 9% and 1% of the total SOA. Aromatics are the dominant contributors to SOA formation.

Biogenic SOA formation through gas-phase oxidation and gas-to-particle partitioning – a comparison between process models of varying complexity

Abstract. Biogenic volatile organic compounds (BVOCs) emitted by vegetation play an important role for aerosol mass loadings since the oxidation products of these compounds can take part in the formation and growth of secondary organic aerosols (SOA). The concentrations and properties of BVOCs and their oxidation products in the atmosphere are poorly characterized, which leads to high uncertainties in modeled SOA mass and properties. In this study, the formation of SOA has been modeled along an air-mass trajectory over northern European boreal forest using two aerosol dynamics box models where the prediction of the condensable organics from the gas-phase oxidation of BVOC is handled with schemes of varying complexity. The use of box model simulations along an air-mass trajectory allows us to compare, under atmospheric relevant conditions, different model parameterizations and their effect on SOA formation. The result of the study shows that the modeled mass concentration of SOA is highly dependent on the organic oxidation scheme used to predict oxidation products. A near-explicit treatment of organic gas-phase oxidation (Master Chemical Mechanism version 3.2) was compared to oxidation schemes that use the volatility basis set (VBS) approach. The resulting SOA mass modeled with different VBS schemes varies by a factor of about 7 depending on how the first-generation oxidation products are parameterized and how they subsequently age (e.g., how fast the gas-phase oxidation products react with the OH radical, how they respond to temperature changes, and if they are allowed to fragment during the aging process). Since the VBS approach is frequently used in regional and global climate models due to its relatively simple treatment of the oxidation products compared to near-explicit oxidation schemes, a better understanding of the above-mentioned processes is needed. Based on the results of this study, fragmentation should be included in order to obtain a realistic SOA formation. Furthermore, compared to the most commonly used VBS schemes, the near-explicit method produces less – but more oxidized – SOA.

Volatility basis-set approach simulation of organic aerosol formation in East Asia: implications for anthropogenic–biogenic interaction and controllable amounts

Abstract. Organic aerosol (OA) simulations using the volatility basis-set approach were made for East Asia and its outflow region. Model simulations were evaluated through comparisons with OA measured by aerosol mass spectrometers in and around Tokyo (at Komaba and Kisai in summer 2003 and 2004) and over the outflow region in East Asia (at Fukue and Hedo in spring 2009). The simulations with aging processes of organic vapors reproduced the mass concentrations, temporal variations, and formation efficiencies of observed OA at all of the sites reasonably well. As OA mass was severely underestimated in the simulations without the aging processes, the oxidations of organic vapors are essential for reasonable OA simulations over East Asia. By considering the aging processes, simulated OA concentrations increased from 0.24 to 1.28 μg m−3 in the boundary layer over the whole of East Asia. OA formed from the interaction of anthropogenic and biogenic sources was also enhanced by the aging processes. The fraction of controllable OA was estimated to be 87% of total OA over the whole of East Asia, which indicated that most of the OA in our simulations were formed anthropogenically (from controllable combustion sources). A large portion of biogenic secondary OA (78% of biogenic secondary OA) was formed through the influence of anthropogenic sources. These fractions were higher than the fraction of anthropogenic emissions. An important reason for these higher controllable fractions was higher oxidant concentrations and the resulting faster oxidation rates of OA precursors by considering anthropogenic sources. Both the amounts (from 0.18 to 1.12 μg m−3) and the fraction (from 75 to 87%) of controllable OA were increased by aging processes of organic vapors over East Asia.

1.5-Dimensional volatility basis set approach for modeling organic aerosol in CAMx and CMAQ

A hybrid volatility basis set (VBS) approach to modeling atmospheric organic aerosol (OA) is developed that combines the simplicity of the 1-dimensional (1-D) VBS with the ability to describe evolution of OA in the 2-dimensional space of oxidation state and volatility. This 1.5-D scheme uses four basis sets to describe varying degrees of oxidation in ambient OA: two basis sets for chemically aged oxygenated OA (anthropogenic and biogenic) and two for freshly emitted OA (from anthropogenic sources and biomass burning). Each basis set has five volatility bins including a zero-volatility bin for essentially non-volatile compounds. The scheme adjusts oxidation state as well as volatility in response to chemical aging by simplifying the 2-dimensional VBS model. The 1.5-D VBS module is implemented in two widely used photochemical grid models (CAMx and CMAQ) and evaluated for summer and winter 2005 episodes over the eastern U.S. CAMx performs reasonably well in predicting observed organic carbon (OC) concentrations while CMAQ under-estimates OC, with differences between models being attributed to science algorithms other than the VBS. Oxygenated OA accounts for less than half of the modeled OA mass in winter but about 80% of total OA in summer due to more rapid chemical aging in summer.

Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models

Abstract. Despite critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, a "best available" set of SOA modeling parameters is selected by comparing predicted SOA yields and mass concentrations with observed yields and mass concentrations from a comprehensive list of published smog chamber studies. Evaluated SOA model parameters include existing parameters for two product (2p) and volatility basis set (VBS) modeling frameworks, and new 2p-VBS parameters; 2p-VBS parameters are developed to exploit advantages of the VBS approach within the computationally-economical and widely-used 2p framework. Fine particulate matter (PM2.5) and SOA mass concentrations are simulated for the continental United States using CMAQv.4.7.1; results are compared for a base case (with default CMAQ parameters) and two best available parameter cases to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future modeling and measurement efforts. The comparisons of SOA yield predictions with data from 22 published chamber studies illustrate that: (1) SOA yields for naphthalene, and cyclic and > C5 straight-chain/branched alkanes are not well represented using either the newly developed or existing parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for four of seven volatile organic compound+oxidant systems, the 2p-VBS parameters better represent chamber data than do the default CMAQ v.4.7.1 parameters. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 15% and 7%, respectively, for the high-NOx case and up to 215% (~3 μg m−3) and 55%, respectively, for the low-NOx case. Percent bias between model-based and observationally-based secondary organic carbon (SOC) improved from −63% for the base case to −15% for the low-NOx case. The ability to robustly assign "best available" parameters in all volatile organic compound+oxidant systems, however, is critically limited due to insufficient data; particularly for photo-oxidation of diverse monoterpenes, sesquiterpenes, and alkanes under a range of atmospherically relevant conditions.

Effects of chemical aging on global secondary organic aerosol using the volatility basis set approach

A global 3-D chemical transport model (GEOS-Chem) is used with the volatility basis set (VBS) approach to examine the effects of chemical aging on global secondary organic aerosol (SOA) concentrations and budgets. We present full-year simulations and their comparisons with the global aerosol mass spectrometer (AMS) dataset, the Interagency Monitoring of Protected Visual Environments (IMPROVE) dataset from the United States, the European Monitoring and Evaluation Programme (EMEP) dataset from Europe, and water-soluble organic carbon observation data collected over East Asia. Using different chemical aging constants, we find that the model results with 4 × 10−11 cm3 molecule−1 s−1 are in better agreement with all observations relative to the model results with other aging constants, without aging, and with the two-product approach. The model simulations are improved when chemical aging is considered, especially for rural regions. However, the simulations still underestimate observed oxygenated organic aerosol (OOA) in urban areas. Two sensitivity simulations including semi-volatile primary organic aerosol (POA) were conducted. We find that including semi-volatile POA improves the model in terms of the hydrogen-like organic aerosol (HOA) to OOA ratio. However, the total OA concentrations are not improved. The total SOA production is considerably increased by 53%, from 26.0 to 39.9 Tg yr−1, after considering chemical aging, remaining lower than top-down estimates of SOA production. Direct radiative forcing (DRF) increases by −0.07 W m−2 due to the chemical aging of SOA, which is comparable to the mean DRF (−0.13 W m−2) of OA from the AeroCom multi-model study. This result indicates considerable global and, more importantly, regional climate implications. For example, the regional DRF change due to chemical aging of SOA in the eastern US is −0.29 W m−2, which is 4 times greater in magnitude than the global mean value.

Gas-Particle Partitioning of Primary Organic Aerosol Emissions: (2) Diesel Vehicles

Experiments were performed to investigate the gas-particle partitioning of primary organic aerosol (POA) emissions from two medium-duty (MDDV) and three heavy-duty (HDDV) diesel vehicles. Each test was conducted on a chassis dynamometer with the entire exhaust sampled into a constant volume sampler (CVS). The vehicles were operated over a range of driving cycles (transient, high-speed, creep/idle) on different ultralow sulfur diesel fuels with varying aromatic content. Four independent yet complementary approaches were used to investigate POA gas-particle partitioning: artifact correction of quartz filter samples, dilution from the CVS into a portable environmental chamber, heating in a thermodenuder, and thermal desorption/gas chromatography/mass spectrometry (TD-GC-MS) analysis of quartz filter samples. During tests of vehicles not equipped with diesel particulate filters (DPF), POA concentrations inside the CVS were a factor of 10 greater than ambient levels, which created large and systematic partitioning biases in the emissions data. For low-emitting DPF-equipped vehicles, as much as 90% of the POA collected on a quartz filter from the CVS were adsorbed vapors. Although the POA emission factors varied by more than an order of magnitude across the set of test vehicles, the measured gas-particle partitioning of all emissions can be predicted using a single volatility distribution derived from TD-GC-MS analysis of quartz filters. This distribution is designed to be applied directly to quartz filter data that are the basis for existing emissions inventories and chemical transport models that have implemented the volatility basis set approach.

Modeling organic aerosol from the oxidation of α-pinene in a Potential Aerosol Mass (PAM) chamber

Abstract. A model has been developed to simulate the formation and evolution of secondary organic aerosol (SOA) and was tested against data produced in a Potential Aerosol Mass (PAM) flow reactor and a large environmental chamber. The model framework is based on the two-dimensional volatility basis set approach (2D-VBS), in which SOA oxidation products in the model are distributed on the 2-D space of effective saturation concentration (Ci*) and oxygen-to-carbon ratio (O : C). The modeled organic aerosol mass concentrations (COA) and O : C agree with laboratory measurements within estimated uncertainties. However, while both measured and modeled O : C increase with increasing OH exposure as expected, the increase of modeled O : C is rapid at low OH exposure and then slows as OH exposure increases while the increase of measured O : C is initially slow and then accelerates as OH exposure increases. A global sensitivity analysis indicates that modeled COA values are most sensitive to the assumed values for the number of Ci* bins, the heterogeneous OH reaction rate coefficient, and the yield of first-generation products. Modeled SOA O : C values are most sensitive to the assumed O : C of first-generation oxidation products, the number of Ci* bins, the heterogeneous OH reaction rate coefficient, and the number of O : C bins. All these sensitivities vary as a function of OH exposure. The sensitivity analysis indicates that the 2D-VBS model framework may require modifications to resolve discrepancies between modeled and measured O : C as a function of OH exposure.

Modeling the formation and properties of traditional and non-traditional secondary organic aerosol: problem formulation and application to aircraft exhaust

Abstract. We present a methodology to model secondary organic aerosol (SOA) formation from the photo-oxidation of unspeciated low-volatility organics (semi-volatile and intermediate volatile organic compounds) emitted by combustion systems. It is formulated using the volatility basis-set approach. Unspeciated low-volatility organics are classified by volatility and then allowed to react with the hydroxyl radical. The new methodology allows for larger reductions in volatility with each oxidation step than previous volatility basis set models, which is more consistent with the addition of common functional groups and similar to those used by traditional SOA models. The methodology is illustrated using data collected during two field campaigns that characterized the atmospheric evolution of dilute gas-turbine engine emissions using a smog chamber. In those experiments, photo-oxidation formed a significant amount of SOA, much of which could not be explained based on the emissions of traditional speciated precursors; we refer to the unexplained SOA as non-traditional SOA (NT-SOA). The NT-SOA can be explained by emissions of unspeciated low-volatility organics measured using sorbents. We show that the parameterization proposed by Robinson et al. (2007) is unable to explain the timing of the NT-SOA formation in the aircraft experiments because it assumes a very modest reduction in volatility of the precursors with every oxidation reaction. In contrast the new method better reproduces the NT-SOA formation. The NT-SOA yields estimated for the unspeciated low-volatility organic emissions in aircraft exhaust are similar to literature data for large n-alkanes and other low-volatility organics. The estimated yields vary with fuel composition (Jet Propellent-8 versus Fischer-Tropsch) and engine load (ground idle versus non-ground idle). The framework developed here is suitable for modeling SOA formation from emissions from other combustion systems.

Determination of Volatility Distributions of Primary Organic Aerosol Emissions from Internal Combustion Engines Using Thermal Desorption Gas Chromatography Mass Spectrometry

A new technique for measuring the primary organic aerosol (POA) emissions from internal combustion engines is presented. The method combines thermal-optical OC/EC analysis and thermal desorption gas chromatography mass spectrometry (TD-GC-MS) of quartz filter samples collected using a dilution sampler to quantify the total emissions of low-volatility organics and to distribute them across the volatility basis set. These data can be used in conjunction with partitioning theory to predict the gas-particle partitioning and thus the total amount of POA over the entire range of atmospheric conditions. The approach is evaluated using POA emissions data from two gas-turbine engines and one diesel generator. To evaluate the new method, we directly measured the effects of temperature and concentration on gas-particle partitioning of the emissions from each. Predictions based on the volatility distributions derived from the filter analyses are consistent with the direct partitioning measurements. The new approach represents a major improvement over the traditional assumption of nonvolatile POA emissions, which over predicts actual POA emissions from these sources by a factor of 2–4 at typical ambient concentration and temperature. By using quartz filter samples, this new technique is designed to be applied to routine source test data. Volatility distributions derived using this new approach can also be applied directly to the large catalog of quartz filter data used by existing emission inventories and models. The emissions data derived from this approach are designed for use in the next generation of chemical transport models and emissions inventories that employ the volatility basis set approach to explicitly track the gas-particle partitioning of POA emissions. Copyright 2012 American Association for Aerosol Research

Predicted changes in summertime organic aerosol concentrations due to increased temperatures

Changes in summertime organic aerosol (OA) concentrations in the Eastern U.S. are investigated for different temperature change scenarios using the chemical transport model PMCAMx-2008. OA is simulated using the volatility basis set approach, assuming that the primary emissions are semi-volatile and that the intermediate volatile and semi-volatile organic compounds are oxidized in the gas phase, resulting in products with lower volatility. For the basic temperature change scenario where biogenic emissions are kept constant, ground-level OA decreases by −0.3% K−1 on average. Increases in the north (+0.1% K−1) and decreases in the south (−0.5% K−1) are predicted. The effect of the uncertain temperature dependence of the aging rate constant is modest, changing the OA by only 0.1% K−1 over the temperature-independent case. For the more realistic scenario in which biogenic OA precursor emissions are allowed to increase with temperature (up to 10% K−1), however, average OA increases by 4.1% K−1, with even higher increases in southern regions. These results suggest that as temperature increases, complicated changes in production, partitioning and chemical aging will take place. Nevertheless, the change in biogenic emissions and subsequent production of biogenic OA is more than an order of magnitude more important than the changes in the rates of chemical and physical atmospheric processes.

Modeling organic aerosols in a megacity: comparison of simple and complex representations of the volatility basis set approach

Abstract. The Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is modified to include a volatility basis set (VBS) treatment of secondary organic aerosol formation. The VBS approach, coupled with SAPRC-99 gas-phase chemistry mechanism, is used to model gas-particle partitioning and multiple generations of gas-phase oxidation of organic vapors. In addition to the detailed 9-species VBS, a simplified mechanism using 2 volatility species (2-species VBS) is developed and tested for similarity to the 9-species VBS in terms of both mass and oxygen-to-carbon ratios of organic aerosols in the atmosphere. WRF-Chem results are evaluated against field measurements of organic aerosols collected during the MILAGRO 2006 campaign in the vicinity of Mexico City. The simplified 2-species mechanism reduces the computational cost by a factor of 2 as compared to 9-species VBS. Both ground site and aircraft measurements suggest that the 9-species and 2-species VBS predictions of total organic aerosol mass as well as individual organic aerosol components including primary, secondary, and biomass burning are comparable in magnitude. In addition, oxygen-to-carbon ratio predictions from both approaches agree within 25 %, providing evidence that the 2-species VBS is well suited to represent the complex evolution of organic aerosols. Model sensitivity to amount of anthropogenic semi-volatile and intermediate volatility (S/IVOC) precursor emissions is also examined by doubling the default emissions. Both the emission cases significantly under-predict primary organic aerosols in the city center and along aircraft flight transects. Secondary organic aerosols are predicted reasonably well along flight tracks surrounding the city, but are consistently over-predicted downwind of the city. Also, oxygen-to-carbon ratio predictions are significantly improved compared to prior studies by adding 15 % oxygen mass per generation of oxidation; however, all modeling cases still under-predict these ratios downwind as compared to measurements, suggesting a need to further improve chemistry parameterizations of secondary organic aerosol formation.