scholarly journals Single particle measurements of bouncing particles and in-situ collection efficiency from an airborne aerosol mass spectrometer (AMS) with light scattering detection

2017 ◽  
Author(s):  
Jin Liao ◽  
Charles A. Brock ◽  
Daniel M. Murphy ◽  
Donna T. Sueper ◽  
André Welti ◽  
...  
Keyword(s):  
Light Scattering ◽  
Chemical Composition ◽  
Mass Spectrometer ◽  
Mass Spectra ◽  
Collection Efficiency ◽  
Particle Mass ◽  
Aerodynamic Diameter ◽  
Aerosol Mass Spectrometer ◽  
Mass Spectral ◽  
Aerosol Mass

Abstract. A light scattering module was coupled to an airborne, compact time-of-flight aerosol mass spectrometer (LS-ToF-AMS) to investigate collection efficiency (CE) while obtaining non-refractory aerosol chemical composition measurements during the Southeast Nexus (SENEX) campaign. In this instrument, particles typically larger than ~ 250 nm in vacuum aerodynamic diameter scatter light from an internal laser beam and trigger saving individual particle mass spectra. Over 33,000 particles are characterized as either prompt (27 %), delayed (15 %), or null (58 %), according to the appearance time and intensity of their mass spectral signals. The individual particle mass from the spectra is proportional to the mass derived from the vacuum aerodynamic diameter determined by the light scattering signals (dva-LS) rather than the traditional particle time-of-flight (PToF) size (dva). The delayed particles capture about 80 % of the total chemical mass compared to prompt ones. Both field and laboratory data indicate that the relative intensities of various ions in the prompt spectra show more fragmentation compared to the delayed spectra. The particles with a delayed mass spectral signal likely bounced on the vaporizer and vaporized later on a lower temperature surface within the confines of the ionization source. Because delayed particles are detected at a later time by the mass spectrometer than expected, they can affect the interpretation of PToF mass distributions especially at the larger sizes. CE, measured by the average number or mass fractions of particles optically detected that have measureable mass spectra, varied significantly (0.2–0.9) in different air masses. Relatively higher null fractions and corresponding lower CE for this study may have been related to the lower sensitivity of the AMS during SENEX. The measured CE generally agreed with the CE parameterization based on ambient chemical composition, including for acidic particles that had a higher CE as expected from previous studies.

scholarly journals Single-particle measurements of bouncing particles and in situ collection efficiency from an airborne aerosol mass spectrometer (AMS) with light-scattering detection

2017 ◽  
Vol 10 (10) ◽  
pp. 3801-3820 ◽  
Author(s):  
Jin Liao ◽  
Charles A. Brock ◽  
Daniel M. Murphy ◽  
Donna T. Sueper ◽  
André Welti ◽  
...  
Keyword(s):  
Light Scattering ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Total Mass ◽  
Mass Spectra ◽  
Collection Efficiency ◽  
Aerosol Mass Spectrometer ◽  
Mass Spectral ◽  
Aerosol Mass ◽  
Spectral Signal

Abstract. A light-scattering module was coupled to an airborne, compact time-of-flight aerosol mass spectrometer (LS-AMS) to investigate collection efficiency (CE) while obtaining nonrefractory aerosol chemical composition measurements during the Southeast Nexus (SENEX) campaign. In this instrument, particles scatter light from an internal laser beam and trigger saving individual particle mass spectra. Nearly all of the single-particle data with mass spectra that were triggered by scattered light signals were from particles larger than ∼ 280 nm in vacuum aerodynamic diameter. Over 33 000 particles are characterized as either prompt (27 %), delayed (15 %), or null (58 %), according to the time and intensity of their total mass spectral signals. The particle mass from single-particle spectra is proportional to that derived from the light-scattering diameter (dva-LS) but not to that from the particle time-of-flight (PToF) diameter (dva-MS) from the time of the maximum mass spectral signal. The total mass spectral signal from delayed particles was about 80 % of that from prompt ones for the same dva-LS. Both field and laboratory data indicate that the relative intensities of various ions in the prompt spectra show more fragmentation compared to the delayed spectra. The particles with a delayed mass spectral signal likely bounced off the vaporizer and vaporized later on another surface within the confines of the ionization source. Because delayed particles are detected by the mass spectrometer later than expected from their dva-LS size, they can affect the interpretation of particle size (PToF) mass distributions, especially at larger sizes. The CE, measured by the average number or mass fractions of particles optically detected that had measurable mass spectra, varied significantly (0.2–0.9) in different air masses. The measured CE agreed well with a previous parameterization when CE > 0.5 for acidic particles but was sometimes lower than the minimum parameterized CE of 0.5.

scholarly journals Organic particle types by single-particle measurements using a time-of-flight aerosol mass spectrometer coupled with a light scattering module

2012 ◽  
Vol 5 (2) ◽  
pp. 3047-3077 ◽  
Author(s):  
S. Liu ◽  
L. M. Russell ◽  
D. T. Sueper ◽  
T. B. Onasch
Keyword(s):  
Light Scattering ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Mass Spectra ◽  
Time Of Flight ◽  
Particle Mass ◽  
Aerosol Mass Spectrometer ◽  
Particle Measurements ◽  
Aerosol Mass ◽  
Organic Particle

Abstract. Chemical and physical properties of individual ambient aerosol particles can vary greatly, so measuring the chemical composition at the single-particle level is essential for understanding atmospheric sources and transformations. Here we describe 46 days of single-particle measurements of atmospheric particles using a time-of-flight aerosol mass spectrometer coupled with a light scattering module (LS-ToF-AMS). The light scattering module optically detects particles larger than 180 nm vacuum aerodynamic diameter (130 nm geometric diameter) (with size resolution of 5–10 defined as dΔd at full width at half maximum) before they arrive at the chemical mass detector and then triggers the saving of single-particle mass spectra. 271 641 particles were detected and sampled during 237 h of sampling in single particle mode. By comparing the timing of light scattering and chemical ion signals for each particle, particle types were classified and their number fractions determined as follows: prompt vaporization (49%), delayed vaporization (7%), and null (44%). LS-ToF-AMS provided the first direct measurement of the size-resolved collection efficiency (CE) of ambient particles, with an approximate 50% number-based CE for particles above detection limit. Prompt and delayed vaporization particles (147 357 particles) were clustered based on similar organic mass spectra (using K-means algorithm) to result in three major clusters: highly oxidized particles (dominated by m/z 44), relatively less oxidized particles (dominated by m/z 43), and particles associated with fresh urban emissions. Each of the three organic clusters had limited chemical properties of other clusters, suggesting that all of the sampled organic particle types were internally mixed to some degree; however, the internal mixing was never uniform and distinct particle types existed throughout the study. Furthermore, the single particle mass spectra and diurnal variations of these clusters agreed well with mass-based components identified (using factor analysis) from simultaneous ensemble-averaged measurements, supporting the connection between ensemble-based factors and atmospheric particle sources and processes. Measurements in this study illustrate that LS-ToF-AMS provides unique information about organic particle types by number as well as mass.

scholarly journals Organic particle types by single-particle measurements using a time-of-flight aerosol mass spectrometer coupled with a light scattering module

2013 ◽  
Vol 6 (2) ◽  
pp. 187-197 ◽  
Author(s):  
S. Liu ◽  
L. M. Russell ◽  
D. T. Sueper ◽  
T. B. Onasch
Keyword(s):  
Light Scattering ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Mass Spectra ◽  
Time Of Flight ◽  
Particle Mass ◽  
Aerosol Mass Spectrometer ◽  
Particle Measurements ◽  
Aerosol Mass ◽  
Organic Particle

Abstract. Chemical and physical properties of individual ambient aerosol particles can vary greatly, so measuring the chemical composition at the single-particle level is essential for understanding atmospheric sources and transformations. Here we describe 46 days of single-particle measurements of atmospheric particles using a time-of-flight aerosol mass spectrometer coupled with a light scattering module (LS-ToF-AMS). The light scattering module optically detects particles larger than 180 nm vacuum aerodynamic diameter (130 nm geometric diameter) before they arrive at the chemical mass spectrometer and then triggers the saving of single-particle mass spectra. 271 641 particles were detected and sampled during 237 h of sampling in single-particle mode. By comparing timing of the predicted chemical ion signals from the light scattering measurement with the measured chemical ion signals by the mass spectrometer for each particle, particle types were classified and their number fractions determined as follows: prompt vaporization (46%), delayed vaporization (6%), and null (48%), where null was operationally defined as less than 6 ions per particle. Prompt and delayed vaporization particles with sufficient chemical information (i.e., more than 40 ions per particle) were clustered based on similarity of organic mass spectra (using k-means algorithm) to result in three major clusters: highly oxidized particles (dominated by m/z 44), relatively less oxidized particles (dominated by m/z 43), and particles associated with fresh urban emissions. Each of the three organic clusters had limited chemical properties of other clusters, suggesting that all of the sampled organic particle types were internally mixed to some degree; however, the internal mixing was never uniform and distinct particle types existed throughout the study. Furthermore, the single-particle mass spectra and time series of these clusters agreed well with mass-based components identified (using factor analysis) from simultaneous ensemble-averaged measurements, supporting the connection between ensemble-based factors and atmospheric particle sources and processes. Measurements in this study illustrate that LS-ToF-AMS provides unique information about organic particle types by number as well as mass.

scholarly journals Single particle characterization using a light scattering module coupled to a time-of-flight aerosol mass spectrometer

2008 ◽  
Vol 8 (6) ◽  
pp. 21313-21381 ◽  
Author(s):  
E. S. Cross ◽  
T. B. Onasch ◽  
M. Canagaratna ◽  
J. T. Jayne ◽  
J. Kimmel ◽  
...  
Keyword(s):  
Light Scattering ◽  
Chemical Composition ◽  
Single Particle ◽  
Mass Spectra ◽  
Sampling Period ◽  
Particle Mass ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Mass Fractions ◽  
Mixing States

Abstract. We present the first single particle results obtained using an Aerodyne time-of-flight aerosol mass spectrometer coupled with a light scattering module (LS-ToF-AMS). The instrument was deployed at the T1 ground site approximately 40 km northeast of the Mexico City Metropolitan Area (MCMA) as part of the MILAGRO field study in March of 2006. The instrument was operated as a standard AMS from 12–30 March, acquiring average chemical composition and size distributions for the ambient aerosol, and in single particle mode from 27–30 March. Over a 75-h sampling period, 12 853 single particle mass spectra were optically triggered, saved, and analyzed. The correlated optical and chemical detection allowed detailed examination of single particle collection and quantification within the LS-ToF-AMS. The single particle data enabled the mixing states of the ambient aerosol to be characterized within the context of the size-resolved ensemble chemical information. The particulate mixing states were examined as a function of sampling time and most of the particles were found to be internal mixtures containing many of the organic and inorganic species identified in the ensemble analysis. The single particle mass spectra were deconvolved, using techniques developed for ensemble AMS data analysis, into HOA, OOA, NH4NO3, (NH4)2SO4, and NH4Cl fractions. Average single particle mass and chemistry measurements are shown to be in agreement with ensemble MS and PTOF measurements. While a significant fraction of ambient particles were internal mixtures of varying degrees, single particle measurements of chemical composition allowed the identification of time periods during which the ambient ensemble was externally mixed. In some cases the chemical composition of the particles suggested a likely source. Throughout the full sampling period, the ambient ensemble was an external mixture of combustion-generated HOA particles from local sources (e.g. traffic), with number concentrations peaking during morning rush hour (04:00–08:00 LT) each day, and more processed particles of mixed composition from nonspecific sources. From 09:00–12:00 LT all particles within the ambient ensemble, including the locally produced HOA particles, became coated with NH4NO3 due to photochemical production of HNO3. The number concentration of externally mixed HOA particles remained low during daylight hours. Throughout the afternoon the OOA component dominated the organic fraction of the single particles, likely due to secondary organic aerosol formation and condensation. Single particle mass fractions of (NH4)2SO4 were lowest during the day and highest during the night. In one instance, gas-to-particle condensation of (NH4)2SO4 was observed on all measured particles within a strong SO2 plume arriving at T1 from the northwest. Particles with high NH4Cl mass fractions were identified during early morning periods. A limited number of particles (~5% of the total number) with mass spectral features characteristic of biomass burning were also identified.

scholarly journals Single particle characterization using a light scattering module coupled to a time-of-flight aerosol mass spectrometer

2009 ◽  
Vol 9 (20) ◽  
pp. 7769-7793 ◽  
Author(s):  
E. S. Cross ◽  
T. B. Onasch ◽  
M. Canagaratna ◽  
J. T. Jayne ◽  
J. Kimmel ◽  
...  
Keyword(s):  
Light Scattering ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Collection Efficiency ◽  
Time Of Flight ◽  
Chemical Compositions ◽  
Single Particles ◽  
Mixing State ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass

Abstract. We present the first single particle results obtained with an Aerodyne time-of-flight aerosol mass spectrometer coupled with a light scattering module (LS-ToF-AMS). The instrument was deployed at the T1 ground site approximately 40 km northeast of the Mexico City Metropolitan Area as part of the MILAGRO field study in March of 2006. The LS-ToF-AMS acquires both ensemble average and single particle data. Over a 75-h sampling period from 27–30 March 2006, 12 853 single particle mass spectra were optically-triggered and saved. The single particles were classified based on observed vaporization histories and measured chemical compositions. The single particle data is shown to provide insights on internal AMS collection efficiencies and ambient mixing state information that augments the ensemble data. Detection of correlated light scattering and chemical ion signals allowed for a detailed examination of the vaporization/ionization process for single particles measured with the AMS instrument. Three particle vaporization event types were identified as a fraction of the total number of particles detected: (1) 23% with prompt vaporization, (2) 26% with delayed vaporization, and (3) 51% characterized as null. Internal consistency checks show that average single particle nonrefractory mass and chemical composition measurements were in reasonable agreement with ensemble measurements and suggest that delayed and null vaporization events are the dominant source of the nonunit collection efficiency of the AMS. Taken together, the simultaneous prompt single particle and aerosol ensemble measurements offer insight into the mixing state and atmospheric transformations of ambient aerosol particles.

scholarly journals Quantitative determination of carbonaceous particle mixing state in Paris using single particle mass spectrometer and aerosol mass spectrometer measurements

2013 ◽  
Vol 13 (4) ◽  
pp. 10345-10393
Author(s):  
R. M. Healy ◽  
J. Sciare ◽  
L. Poulain ◽  
M. Crippa ◽  
A. Wiedensohler ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Organic Aerosol ◽  
Particle Mass ◽  
Mixing State ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Particle Mixing ◽  
Mixing States

Abstract. Single particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been estimated using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulphate and potassium were compared with concurrent measurements from an Aerodyne high resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal/optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived mass concentrations reproduced the variability of these species well (R2 = 0.67–0.78), and ten discrete mixing states for carbonaceous particles were identified and quantified. Potassium content was used to identify particles associated with biomass combustion. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorization, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulphate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA/EC ratios. Aged biomass burning OA (OOA2-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidized OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the heterogeneity of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental scale emissions.

scholarly journals STRAPS v1.0: evaluating a methodology for predicting electron impact ionisation mass spectra for the aerosol mass spectrometer

2017 ◽  
Vol 10 (6) ◽  
pp. 2365-2377 ◽  
Author(s):  
David O. Topping ◽  
James Allan ◽  
M. Rami Alfarra ◽  
Bernard Aumont
Keyword(s):  
Electron Impact ◽  
Mass Spectrometer ◽  
Mass Spectra ◽  
Charge Ratio ◽  
Support Vector ◽  
Aerosol Mass Spectrometer ◽  
Mass Spectral ◽  
Aerosol Mass ◽  
Supervised Methods ◽  
Impact Ionisation

Abstract. Our ability to model the chemical and thermodynamic processes that lead to secondary organic aerosol (SOA) formation is thought to be hampered by the complexity of the system. While there are fundamental models now available that can simulate the tens of thousands of reactions thought to take place, validation against experiments is highly challenging. Techniques capable of identifying individual molecules such as chromatography are generally only capable of quantifying a subset of the material present, making it unsuitable for a carbon budget analysis. Integrative analytical methods such as the Aerosol Mass Spectrometer (AMS) are capable of quantifying all mass, but because of their inability to isolate individual molecules, comparisons have been limited to simple data products such as total organic mass and the O : C ratio. More detailed comparisons could be made if more of the mass spectral information could be used, but because a discrete inversion of AMS data is not possible, this activity requires a system of predicting mass spectra based on molecular composition. In this proof-of-concept study, the ability to train supervised methods to predict electron impact ionisation (EI) mass spectra for the AMS is evaluated. Supervised Training Regression for the Arbitrary Prediction of Spectra (STRAPS) is not built from first principles. A methodology is constructed whereby the presence of specific mass-to-charge ratio (m∕z) channels is fitted as a function of molecular structure before the relative peak height for each channel is similarly fitted using a range of regression methods. The widely used AMS mass spectral database is used as a basis for this, using unit mass resolution spectra of laboratory standards. Key to the fitting process is choice of structural information, or molecular fingerprint. Our approach relies on using supervised methods to automatically optimise the relationship between spectral characteristics and these molecular fingerprints. Therefore, any internal mechanisms or instrument features impacting on fragmentation are implicitly accounted for in the fitted model. Whilst one might expect a collection of keys specifically designed according to EI fragmentation principles to offer a robust basis, the suitability of a range of commonly available fingerprints is evaluated. Using available fingerprints in isolation, initial results suggest the generic public MACCS fingerprints provide the most accurate trained model when combined with both decision trees and random forests, with median cosine angles of 0.94–0.97 between modelled and measured spectra. There is some sensitivity to choice of fingerprint, but most sensitivity is in choice of regression technique. Support vector machines perform the worst, with median values of 0.78–0.85 and lower ranges approaching 0.4, depending on the fingerprint used. More detailed analysis of modelled versus mass spectra demonstrates important composition-dependent sensitivities on a compound-by-compound basis. This is further demonstrated when we apply the trained methods to a model α-pinene SOA system, using output from the GECKO-A model. This shows that use of a generic fingerprint referred to as FP4 and one designed for vapour pressure predictions (Nanoolal) gives plausible mass spectra, whilst the use of the MACCS keys in isolation performs poorly in this application, demonstrating the need for evaluating model performance against other SOA systems rather than existing laboratory databases on single compounds. Given the limited number of compounds used within the AMS training dataset, it is difficult to prescribe which combination of approach would lead to a robust generic model across all expected compositions. Nonetheless, the study demonstrates the use of a methodology that would be improved with more training data, fingerprints designed explicitly for fragmentation mechanisms occurring within the AMS, and data from additional mixed systems for further validation. To facilitate further development of the method, including application to other instruments, the model code for re-training is provided via a public Github and Zenodo software repository.

scholarly journals Studies of aerosol at a coastal site using two aerosol mass spectrometry instruments and identification of biogenic particle types

2005 ◽  
Vol 5 (5) ◽  
pp. 10799-10838 ◽  
Author(s):  
M. Dall’Osto ◽  
R. M. Harrison ◽  
H. Furutani ◽  
K. A. Prather ◽  
H. Coe ◽  
...  
Keyword(s):  
Mass Spectrometer ◽  
Atmospheric Chemistry ◽  
Mass Spectra ◽  
Sea Salt ◽  
Aerosol Mass Spectrometer ◽  
Mass Spectral ◽  
Aerosol Mass ◽  
Aerosol Mass Spectrometry ◽  
Neural Network Algorithm ◽  
Individual Particles

Abstract. During August 2004 an Aerosol Time-of-Flight Mass Spectrometer (TSI ATOFMS Model 3800-100) and an Aerodyne Aerosol Mass Spectrometer (AMS) were deployed at Mace Head during the NAMBLEX campaign. Single particle data (size, positive and negative mass spectra) from the ATOFMS were imported into ART 2a, a neural network algorithm, which assigns individual particles to clusters on the basis of their mass spectral similarities. Results are very consistent with previous time consuming manual classifications (Dall'Osto et al., 2004). Three broad classes were found: sea-salt, dust and carbon-containing particles, with a number of sub-classes within each. The Aerodyne (AMS) instrument was also used during NAMBLEX, providing online, real time measurements of the mass of non-refractory components of aerosol particles as function of their size. The ATOFMS detected a type of particle not identified in our earlier analysis, with a strong signal at m/z 24, likely due to magnesium. This type of particle was detected during the same periods as pure unreacted sea salt particles and is thought to be biogenic, originating from the sea surface. AMS data are consistent with this interpretation, showing an additional organic peak in the corresponding size range at times when the Mg-rich particles are detected. The work shows the ATOFMS and AMS to be largely complementary, and to provide a powerful instrumental combination in studies of atmospheric chemistry.

scholarly journals Quantitative determination of carbonaceous particle mixing state in Paris using single-particle mass spectrometer and aerosol mass spectrometer measurements

2013 ◽  
Vol 13 (18) ◽  
pp. 9479-9496 ◽  
Author(s):  
R. M. Healy ◽  
J. Sciare ◽  
L. Poulain ◽  
M. Crippa ◽  
A. Wiedensohler ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Mass Spectrometer ◽  
Single Particle ◽  
Organic Aerosol ◽  
Particle Mass ◽  
Mixing State ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Particle Mixing ◽  
Mixing States

Abstract. Single-particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single-particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been determined using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulfate and potassium were compared with concurrent measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal–optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived estimated mass concentrations reproduced the variability of these species well (R2 = 0.67–0.78), and 10 discrete mixing states for carbonaceous particles were identified and quantified. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorisation, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulfate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA / EC ratios. Aged biomass burning OA (OOA2-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidised OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the range of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental-scale emissions.

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