Changes in organic aerosol composition with aging inferred from aerosol mass spectra

Organic aerosols (OA) can be separated with factor analysis of aerosol mass spectrometer (AMS) data into hydrocarbon-like OA (HOA) and oxygenated OA (OOA). We develop a new method to parameterize H:C of OOA in terms of f_(43)(ratio of m/z 43, mostly C_2H_3O^+, to total signal in the component mass spectrum). Such parameterization allows for the transformation of large database of ambient OOA components from the f_(44) (mostly CO^+_2, likely from acid groups) vs. f_(43) space ("triangle plot") (Ng et al., 2010) into the Van Krevelen diagram (H:C vs. O:C) (Van Krevelen, 1950). Heald et al. (2010) examined the evolution of total OA in the Van Krevelen diagram. In this work total OA is deconvolved into components that correspond to primary (HOA and others) and secondary (OOA) organic aerosols. By deconvolving total OA into different components, we remove physical mixing effects between secondary and primary aerosols which allows for examination of the evolution of OOA components alone in the Van Krevelen space. This provides a unique means of following ambient secondary OA evolution that is analogous to and can be compared with trends observed in chamber studies of secondary organic aerosol formation. The triangle plot in Ng et al. (2010) indicates that f_(44) of OOA components increases with photochemical age, suggesting the importance of acid formation in OOA evolution. Once they are transformed with the new parameterization, the triangle plot of the OOA components from all sites occupy an area in Van Krevelen space which follows a ΔH:C/ΔO:C slope of ~ −0.5. This slope suggests that ambient OOA aging results in net changes in chemical composition that are equivalent to the addition of both acid and alcohol/peroxide functional groups without fragmentation (i.e. C-C bond breakage), and/or the addition of acid groups with fragmentation. These results provide a framework for linking the bulk aerosol chemical composition evolution to molecular-level studies

Elemental composition and oxidation of chamber organic aerosol

Recently, graphical representations of aerosol mass spectrometer (AMS) spectra and elemental composition have been developed to explain the oxidative and aging processes of secondary organic aerosol (SOA). It has been shown previously that oxygenated organic aerosol (OOA) components from ambient and laboratory data fall within a triangular region in the f_(44) vs. f_(43) space, where f_(44) and f_(43) are the ratios of the organic signal at m/z 44 and 43 to the total organic signal in AMS spectra, respectively; we refer to this graphical representation as the "triangle plot." Alternatively, the Van Krevelen diagram has been used to describe the evolution of functional groups in SOA. In this study we investigate the variability of SOA formed in chamber experiments from twelve different precursors in both "triangle plot" and Van Krevelen domains. Spectral and elemental data from the high-resolution Aerodyne aerosol mass spectrometer are compared to offline species identification analysis and FTIR filter analysis to better understand the changes in functional and elemental composition inherent in SOA formation and aging. We find that SOA formed under high- and low-NO_x conditions occupy similar areas in the "triangle plot" and Van Krevelen diagram and that SOA generated from already oxidized precursors allows for the exploration of areas higher on the "triangle plot" not easily accessible with non-oxidized precursors. As SOA ages, it migrates toward the top of the triangle along a path largely dependent on the precursor identity, which suggests increasing organic acid content and decreasing mass spectral variability. The most oxidized SOA come from the photooxidation of methoxyphenol precursors which yielded SOA O/C ratios near unity. α-pinene ozonolysis and naphthalene photooxidation SOA systems have had the highest degree of mass closure in previous chemical characterization studies and also show the best agreement between AMS elemental composition measurements and elemental composition of identified species within the uncertainty of the AMS elemental analysis. In general, compared to their respective unsaturated SOA precursors, the elemental composition of chamber SOA follows a slope shallower than −1 on the Van Krevelen diagram, which is indicative of oxidation of the precursor without substantial losss of hydrogen, likely due to the unsaturated nature of the precursors. From the spectra of SOA studied here, we are able to reproduce the triangular region originally constructed with ambient OOA compents with chamber aerosol showing that SOA becomes more chemically similar as it ages. Ambient data in the middle of the triangle represent the ensemble average of many different SOA precursors, ages, and oxidative processes

Modeling organic aerosols in a megacity: potential contribution of semi-volatile and intermediate volatility primary organic compounds to secondary organic aerosol formation

It has been established that observed local and regional levels of secondary organic aerosols (SOA) in polluted areas cannot be explained by the oxidation and partitioning of anthropogenic and biogenic VOC precursors, at least using current mechanisms and parameterizations. In this study, the 3-D regional air quality model CHIMERE is applied to estimate the potential contribution to SOA formation of recently identified semi-volatile and intermediate volatility organic precursors (S/IVOC) in and around Mexico City for the MILAGRO field experiment during March 2006. The model has been updated to include explicitly the volatility distribution of primary organic aerosols (POA), their gas-particle partitioning and the gas-phase oxidation of the vapors. Two recently proposed parameterizations, those of Robinson et al. (2007) ("ROB") and Grieshop et al. (2009) ("GRI") are compared and evaluated against surface and aircraft measurements. The 3-D model results are assessed by comparing with the concentrations of OA components from Positive Matrix Factorization of Aerosol Mass Spectrometer (AMS) data, and for the first time also with oxygen-to-carbon ratios derived from high-resolution AMS measurements. The results show a substantial enhancement in predicted SOA concentrations (2–4 times) with respect to the previously published base case without S/IVOCs (Hodzic et al., 2009), both within and downwind of the city leading to much reduced discrepancies with the total OA measurements. Model improvements in OA predictions are associated with the better-captured SOA magnitude and diurnal variability. The predicted production from anthropogenic and biomass burning S/IVOC represents 40–60% of the total measured SOA at the surface during the day and is somewhat larger than that from commonly measured aromatic VOCs, especially at the T1 site at the edge of the city. The SOA production from the continued multi-generation S/IVOC oxidation products continues actively downwind. Similar to aircraft observations, the predicted OA/ΔCO ratio for the ROB case increases from 20–30 μg sm<sup>−3</sup> ppm<sup>−1</sup> up to 60–70 μg sm<sup>−3</sup> ppm<sup>−1</sup> between a fresh and 1-day aged air mass, while the GRI case produces a 30% higher OA growth than observed. The predicted average O/C ratio of total OA for the ROB case is 0.16 at T0, substantially below observed value of 0.5. A much better agreement for O/C ratios and temporal variability (<i>R</i><sup>2</sup>=0.63) is achieved with the updated GRI treatment. Both treatments show a deficiency in regard to POA ageing with a tendency to over-evaporate POA upon dilution of the urban plume suggesting that atmospheric HOA may be less volatile than assumed in these parameterizations. This study highlights the important potential role of S/IVOC chemistry in the SOA budget in this region, and highlights the need for further improvements in available parameterizations. The agreement observed in this study is not sufficient evidence to conclude that S/IVOC are the major missing SOA source in megacity environments. The model is still very underconstrained, and other possible pathways such as formation from very volatile species like glyoxal may explain some of the mass and especially increase the O/C ratio

Deconvolution of FIGAERO-CIMS thermal desorption profiles using positive matrix factorisation to identify chemical and physical processes during particle evaporation

he measurements of aerosol particles with a filter inlet for gases and aerosols (FIGAERO) together with a chemical ionisation mass spectrometer (CIMS) yield the overall chemical composition of the particle phase. In addition, the thermal desorption profiles obtained for each detected ion composition contain information about the volatility of the detected compounds, which is an important property for understanding many physical properties like gas–particle partitioning. We coupled this thermal desorption method with isothermal evaporation prior to the sample collection to investigate the chemical composition changes during isothermal particle evaporation and particulate-water-driven chemical reactions in α-pinene secondary organic aerosol (SOA) of three different oxidative states. The thermal desorption profiles of all detected elemental compositions were then analysed with positive matrix factorisation (PMF) to identify the drivers of the chemical composition changes observed during isothermal evaporation. The keys to this analysis were to use the error matrix as a tool to weight the parts of the data carrying most information (i.e. the peak area of each thermogram) and to run PMF on a combined data set of multiple thermograms from different experiments to enable a direct comparison of the individual factors between separate measurements. The PMF was able to identify instrument background factors and separate them from the part of the data containing particle desorption information. Additionally, PMF allowed us to separate the direct desorption of compounds detected at a specific elemental composition from other signals with the same composition that stem from the thermal decomposition of thermally instable compounds with lower volatility. For each SOA type, 7–9 factors were needed to explain the observed thermogram behaviour. The contribution of the factors depended on the prior isothermal evaporation. Decreased contributions from the factors with the lowest desorption temperatures were observed with increasing isothermal evaporation time. Thus, the factors identified by PMF could be interpreted as volatility classes. The composition changes in the particles due to isothermal evaporation could be attributed to the removal of volatile factors with very little change in the desorption profiles of the individual factors (i.e. in the respective temperatures of peak desorption, Tmax). When aqueous-phase reactions took place, PMF was able to identify a new factor that directly identified the ions affected by the chemical processes. We conducted a PMF analysis of the FIGAERO–CIMS thermal desorption data for the first time using laboratory-generated SOA particles. But this method can be applied to, for example, ambient FIGAERO–CIMS measurements as well. There, the PMF analysis of the thermal desorption data identifies organic aerosol (OA) sources (such as biomass burning or oxidation of different precursors) and types, e.g. hydrocarbon-like (HOA) or oxygenated organic aerosol (OOA). This information could also be obtained with the traditional approach, namely the PMF analysis of the mass spectra data integrated for each thermogram. But only our method can also obtain the volatility information for each OA source and type. Additionally, we can identify the contribution of thermal decomposition to the overall signal

Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign

Organic aerosol concentrations are simulated using the WRF-CHEM model in Mexico City during the period from 24 to 29 March in association with the MILAGRO-2006 campaign. Two approaches are employed to predict the variation and spatial distribution of the organic aerosol concentrations: (1) a traditional 2-product secondary organic aerosol (SOA) model with non-volatile primary organic aerosols (POA); (2) a non-traditional SOA model including the volatility basis-set modeling method in which primary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA (Mexico City Metropolitan Area) 2006 official emission inventory is used in simulations and the POA emissions are modified and distributed by volatility based on dilution experiments for the non-traditional SOA model. The model results are compared to the Aerosol Mass Spectrometry (AMS) observations analyzed using the Positive Matrix Factorization (PMF) technique at an urban background site (T0) and a suburban background site (T1) in Mexico City. The traditional SOA model frequently underestimates the observed POA concentrations during rush hours and overestimates the observations in the rest of the time in the city. The model also substantially underestimates the observed SOA concentrations, particularly during daytime, and only produces 21% and 25% of the observed SOA mass in the suburban and urban area, respectively. The non-traditional SOA model performs well in simulating the POA variation, but still overestimates during daytime in the urban area. The SOA simulations are significantly improved in the non-traditional SOA model compared to the traditional SOA model and the SOA production is increased by more than 100% in the city. However, the underestimation during daytime is still salient in the urban area and the non-traditional model also fails to reproduce the high level of SOA concentrations in the suburban area. In the non-traditional SOA model, the aging process of primary organic components considerably decreases the OH levels in simulations and further impacts the SOA formation. If the aging process in the non-traditional model does not have feedback on the OH in the gas-phase chemistry, the SOA production is enhanced by more than 10% compared to the simulations with the OH feedback during daytime, and the gap between the simulations and observations in the urban area is around 3 μg m[superscript −3] or 20% on average during late morning and early afternoon, within the uncertainty from the AMS measurements and PMF analysis. In addition, glyoxal and methylglyoxal can contribute up to approximately 10% of the observed SOA mass in the urban area and 4% in the suburban area. Including the non-OH feedback and the contribution of glyoxal and methylglyoxal, the non-traditional SOA model can explain up to 83% of the observed SOA in the urban area, and the underestimation during late morning and early afternoon is reduced to 0.9 μg m[superscript −3] or 6% on average. Considering the uncertainties from measurements, emissions, meteorological conditions, aging of semi-volatile and intermediate volatile organic compounds, and contributions from background transport, the non-traditional SOA model is capable of closing the gap in SOA mass between measurements and models.National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-0528227)National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-0810931)Molina Center for Energy and the Environmen

Intercomparison of an Aerosol Chemical Speciation Monitor (ACSM) with ambient fine aerosol measurements in downtown Atlanta, Georgia

Currently, there are a limited number of field studies that evaluate the long-term performance of the Aerodyne Aerosol Chemical Speciation Monitor (ACSM) against established monitoring networks. In this study, we present seasonal intercomparisons of the ACSM with collocated fine aerosol (PM_2.5) measurements at the Southeastern Aerosol Research and Characterization (SEARCH) Jefferson Street (JST) site near downtown Atlanta, GA, during 2011–2012. Intercomparison of two collocated ACSMs resulted in strong correlations (<i>r</i>² > 0.8) for all chemical species, except chloride (<i>r</i>² = 0.21) indicating that ACSM instruments are capable of stable and reproducible operation. In general, speciated ACSM mass concentrations correlate well (<i>r</i>² > 0.7) with the filter-adjusted continuous measurements from JST, although the correlation for nitrate is weaker (<i>r</i>² = 0.55) in summer. Correlations of the ACSM NR-PM₁ (non-refractory particulate matter with aerodynamic diameter less than or equal to 1 μm) plus elemental carbon (EC) with tapered element oscillating microbalance (TEOM) PM_2.5 and Federal Reference Method (FRM) PM₁ mass are strong with <i>r</i>² > 0.7 and <i>r</i>² > 0.8, respectively. Discrepancies might be attributed to evaporative losses of semi-volatile species from the filter measurements used to adjust the collocated continuous measurements. This suggests that adjusting the ambient aerosol continuous measurements with results from filter analysis introduced additional bias to the measurements. We also recommend to calibrate the ambient aerosol monitoring instruments using aerosol standards rather than gas-phase standards. The fitting approach for ACSM relative ionization for sulfate was shown to improve the comparisons between ACSM and collocated measurements in the absence of calibrated values, suggesting the importance of adding sulfate calibration into the ACSM calibration routine

Transmission Efficiency of an Aerodynamic Focusing Lens System: Comparison of Model Calculations and Laboratory Measurements for the Aerodyne Aerosol Mass Spectrometer

The size-dependent particle transmission efficiency of the aerodynamic lens system used in the Aerodyne Aerosol Mass Spectrometer (AMS) was investigated with computational fluid dynamics (CFD) calculations and experimental measurements. The CFD calculations revealed that the entire lens system, including the aerodynamic lens itself, the critical orifice which defines the operating lens pressure, and a valve assembly, needs to be considered. Previous calculations considered only the aerodynamic lens. The calculations also investigated the effect of operating the lens system at two different sampling pressures, 7.8 × 104 Pa (585 torr) and 1.0 × 105 Pa (760 torr). Experimental measurements of transmission efficiency were performed with size-selected diethyl hexyl sebacate (DEHS), NH4NO3, and NaNO3 particles on three different AMS instruments at two different ambient sampling pressures (7.8 × 104 Pa, 585 torr and 1.0 × 105 Pa, 760 torr). Comparisons of the measurements and the calculations showqualitative agreement, but there are significant deviations which are as yet unexplained. On the small size end (30 nm to 150 nm vacuum aerodynamic diameter), the measured transmission efficiency is lower than predicted. On the large size end (\u3e350 nm vacuum aerodynamic diameter

Chemical characterization of secondary organic aerosol at a rural site in the southeastern US: insights from simultaneous high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and FIGAERO chemical ionization mass spectrometer (CIMS) measurements

The formation and evolution of secondary organic aerosol (SOA) were investigated at Yorkville, GA, in late summer (mid-August to mid-October 2016). The organic aerosol (OA) composition was measured using two online mass spectrometry instruments, the high-resolution time-of-flight aerosol mass spectrometer (AMS) and the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct chemical ionization mass spectrometer (FIGAERO-CIMS). Through analysis of speciated organics data from FIGAERO-CIMS and factorization analysis of data obtained from both instruments, we observed notable SOA formation from isoprene and monoterpenes during both day and night. Specifically, in addition to isoprene epoxydiol (IEPOX) uptake, we identified isoprene SOA formation from non-IEPOX pathways and isoprene organic nitrate formation via photooxidation in the presence of NO_x and nitrate radical oxidation. Monoterpenes were found to be the most important SOA precursors at night. We observed significant contributions from highly oxidized acid-like compounds to the aged OA factor from FIGAERO-CIMS. Taken together, our results showed that FIGAERO-CIMS measurements are highly complementary to the extensively used AMS factorization analysis, and together they provide more comprehensive insights into OA sources and composition

Chemical characterization of secondary organic aerosol at a rural site in the southeastern US: insights from simultaneous high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and FIGAERO chemical ionization mass spectrometer (CIMS) measurements

The formation and evolution of secondary organic aerosol (SOA) were investigated at Yorkville, GA, in late summer (mid-August to mid-October 2016). The organic aerosol (OA) composition was measured using two online mass spectrometry instruments, the high-resolution time-of-flight aerosol mass spectrometer (AMS) and the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct chemical ionization mass spectrometer (FIGAERO-CIMS). Through analysis of speciated organics data from FIGAERO-CIMS and factorization analysis of data obtained from both instruments, we observed notable SOA formation from isoprene and monoterpenes during both day and night. Specifically, in addition to isoprene epoxydiol (IEPOX) uptake, we identified isoprene SOA formation from non-IEPOX pathways and isoprene organic nitrate formation via photooxidation in the presence of NO_x and nitrate radical oxidation. Monoterpenes were found to be the most important SOA precursors at night. We observed significant contributions from highly oxidized acid-like compounds to the aged OA factor from FIGAERO-CIMS. Taken together, our results showed that FIGAERO-CIMS measurements are highly complementary to the extensively used AMS factorization analysis, and together they provide more comprehensive insights into OA sources and composition

Experiment to Characterize Aircraft Volatile Aerosol and Trace-Species Emissions (EXCAVATE)

The Experiment to Characterize Aircraft Volatile and Trace Species Emissions (EXCAVATE) was conducted at Langley Research Center (LaRC) in January 2002 and focused upon assaying the production of aerosols and aerosol precursors by a modern commercial aircraft, the Langley B757, during ground-based operation. Remaining uncertainty in the postcombustion fate of jet fuel sulfur contaminants, the need for data to test new theories of particle formation and growth within engine exhaust plumes, and the need for observations to develop air quality models for predicting pollution levels in airport terminal areas were the primary factors motivating the experiment. NASA's Atmospheric Effects of Aviation Project (AEAP) and the Ultra Effect Engine Technology (UEET) Program sponsored the experiment which had the specific objectives of determining ion densities; the fraction of fuel S converted from S(IV) to S(VI); the concentration and speciation of volatile aerosols and black carbon; and gas-phase concentrations of long-chain hydrocarbon and PAH species, all as functions of engine power, fuel composition, and plume age