In this study we compile and present results from the factor analysis of 43 Aerosol Mass Spectrometer (AMS) datasets (27 of the datasets are reanalyzed in this work). The components from all sites, ...when taken together, provide a holistic overview of Northern Hemisphere organic aerosol (OA) and its evolution in the atmosphere. At most sites, the OA can be separated into oxygenated OA (OOA), hydrocarbon-like OA (HOA), and sometimes other components such as biomass burning OA (BBOA). We focus on the OOA components in this work. In many analyses, the OOA can be further deconvolved into low-volatility OOA (LV-OOA) and semi-volatile OOA (SV-OOA). Differences in the mass spectra of these components are characterized in terms of the two main ions m/z 44 (CO2+) and m/z 43 (mostly C2H3O+), which are used to develop a new mass spectral diagnostic for following the aging of OA components in the atmosphere. The LV-OOA component spectra have higher f44 (ratio of m/z 44 to total signal in the component mass spectrum) and lower f43 (ratio of m/z 43 to total signal in the component mass spectrum) than SV-OOA. A wide range of f44 and O:C ratios are observed for both LV-OOA (0.17±0.04, 0.73±0.14) and SV-OOA (0.07±0.04, 0.35±0.14) components, reflecting the fact that there is a continuum of OOA properties in ambient aerosol. The OOA components (OOA, LV-OOA, and SV-OOA) from all sites cluster within a well-defined triangular region in the f44 vs. f43 space, which can be used as a standardized means for comparing and characterizing any OOA components (laboratory or ambient) observed with the AMS. Examination of the OOA components in this triangular space indicates that OOA component spectra become increasingly similar to each other and to fulvic acid and HULIS sample spectra as f44 (a surrogate for O:C and an indicator of photochemical aging) increases. This indicates that ambient OA converges towards highly aged LV-OOA with atmospheric oxidation. The common features of the transformation between SV-OOA and LV-OOA at multiple sites potentially enable a simplified description of the oxidation of OA in the atmosphere. Comparison of laboratory SOA data with ambient OOA indicates that laboratory SOA are more similar to SV-OOA and rarely become as oxidized as ambient LV-OOA, likely due to the higher loadings employed in the experiments and/or limited oxidant exposure in most chamber experiments.
Reliable characterization of particles freshly emitted from the ocean surface requires a sampling method that is able to isolate those particles and prevent them from interacting with ambient gases ...and particles. Here we report measurements of particles directly emitted from the ocean using a newly developed in situ particle generator (Sea Sweep). The Sea Sweep was deployed alongside R/V Atlantis off the coast of California during May of 2010. Bubbles were generated 0.75 m below the ocean surface with stainless steel frits and swept into a hood/vacuum hose to feed a suite of aerosol instrumentation on board the ship. The number size distribution of the directly emitted, nascent particles had a dominant mode at 55–60 nm (dry diameter) and secondary modes at 30–40 nm and 200–300 nm. The nascent aerosol was not volatile at 230°C and was not enriched in SO4=, Ca++, K+, or Mg++above that found in surface seawater. The organic component of the nascent aerosol (7% of the dry submicrometer mass) volatilized at a temperature between 230 and 600°C. The submicrometer organic aerosol characterized by mass spectrometry was dominated by non‐oxygenated hydrocarbons. The nascent aerosol at 50, 100, and 145 nm dry diameter behaved hygroscopically like an internal mixture of sea salt with a small organic component. The CCN/CN activation ratio for 60 nm Sea Sweep particles was near 1 for all supersaturations of 0.3 and higher indicating that all of the particles took up water and grew to cloud drop size. The nascent organic aerosol mass fraction did not increase in regions of higher surface seawater chlorophyll but did show a positive correlation with seawater dimethylsulfide (DMS).
Key Points
The ocean is a source of sub 100nm particles to the atmosphere
Hygroscopically the particles behave like an internal mixture of sea salt/organic
Organic mass fraction did not correlate with chlorophyll
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 f44 vs. f43 space, where f44 and f43 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-NOx 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.
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−3 ppm−1 up to 60–70 μg sm−3 ppm−1 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 (R2=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.
Organic aerosol (OA) data acquired by the Aerosol Mass Spectrometer (AMS) in 37 field campaigns were deconvolved into hydrocarbon‐like OA (HOA) and several types of oxygenated OA (OOA) components. ...HOA has been linked to primary combustion emissions (mainly from fossil fuel) and other primary sources such as meat cooking. OOA is ubiquitous in various atmospheric environments, on average accounting for 64%, 83% and 95% of the total OA in urban, urban downwind, and rural/remote sites, respectively. A case study analysis of a rural site shows that the OOA concentration is much greater than the advected HOA, indicating that HOA oxidation is not an important source of OOA, and that OOA increases are mainly due to SOA. Most global models lack an explicit representation of SOA which may lead to significant biases in the magnitude, spatial and temporal distributions of OA, and in aerosol hygroscopic properties.
We have designed and characterized a new inlet and aerodynamic lens for the Aerodyne aerosol mass spectrometer (AMS) that transmits particles between 80 nm and more than 3 μm in vacuum aerodynamic ...diameter. The design of the inlet and lens was optimized with computational fluid dynamics (CFD) modeling of particle trajectories. Major changes include a redesigned critical orifice holder and valve assembly, addition of a relaxation chamber behind the critical orifice, and a higher lens operating pressure. The transmission efficiency of the new inlet and lens was characterized experimentally with size-selected particles. Experimental measurements are in good agreement with the calculated transmission efficiency.
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−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−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.
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
NOx 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.
Particulate matter (PM) pollution is a severe environmental problem in the Beijing–Tianjin–Hebei (BTH) region in North
China. PM studies have been conducted extensively in Beijing, but the
chemical ...composition, sources, and atmospheric processes of PM are still
relatively less known in nearby Tianjin and Hebei. In this study, fine PM
in urban Shijiazhuang (the capital of Hebei Province) was characterized using
an Aerodyne quadrupole aerosol chemical speciation monitor (Q-ACSM) from
11 January to 18 February in 2014. The average mass concentration of
non-refractory submicron PM (diameter <1 µm, NR-PM1) was
178±101 µg m−3, and it was composed of 50 % organic aerosol
(OA), 21 % sulfate, 12 % nitrate, 11 % ammonium, and 6 % chloride.
Using the multilinear engine (ME-2) receptor model, five OA sources were
identified and quantified, including hydrocarbon-like OA from vehicle
emissions (HOA, 13 %), cooking OA (COA, 16 %), biomass burning OA (BBOA,
17 %), coal combustion OA (CCOA, 27 %), and oxygenated OA (OOA, 27 %).
We found that secondary formation contributed substantially to PM in episodic
events, whereas primary emissions were dominant (most significant) on average.
The episodic events with the highest NR-PM1 mass range of
300–360 µg m−3 were comprised of 55 % of secondary species. On the
contrary, a campaign-average low OOA fraction (27 %) in OA indicated the
importance of primary emissions, and a low sulfur oxidation degree
(FSO4) of 0.18 even at RH >90 % hinted at insufficient
oxidation. These results suggested that in Shijiazhuang in wintertime fine PM
was mostly from primary emissions without sufficient atmospheric aging,
indicating opportunities for air quality improvement by mitigating direct
emissions. In addition, secondary inorganic and organic (OOA) species
dominated in pollution events with high-RH conditions, most likely due to
enhanced aqueous-phase chemistry, whereas primary organic aerosol (POA)
dominated in pollution events with low-RH and stagnant conditions. These
results also highlighted the importance of meteorological conditions for PM
pollution in this highly polluted city in North China.
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