scholarly journals Supplementary material to "FATES: A Flexible Analysis Toolkit for the Exploration of Single Particle Mass Spectrometer Data"

Author(s):  
Camille M. Sultana ◽  
Gavin Cornwell ◽  
Paul Rodriguez ◽  
Kimberly A. Prather
2016 ◽  
Author(s):  
Camille M. Sultana ◽  
Gavin Cornwell ◽  
Paul Rodriguez ◽  
Kimberly A. Prather

Abstract. Single particle mass spectrometer (SPMS) analysis of aerosols has become increasingly popular since its invention in the 1990s. Today many iterations of commercial and lab-built SPMS are in use worldwide. However supporting analysis toolkits for these powerful instruments are either outdated, have limited functionality, or are versions that are not available to the scientific community at large. In an effort to advance this field and allow better communication and collaboration between scientists we have developed FATES (Flexible Analysis Toolkit for the Exploration of SPMS data), a MATLAB toolkit easily extensible to an array of SPMS designs and data formats. FATES was developed to minimize the computational demands of working with large datasets while still allowing easy maintenance, modification, and utilization by novice programmers. FATES permits scientists to explore, without constraint, complex SPMS data with simple scripts in a language popular for scientific numerical analysis. In addition FATES contains an array of data visualization GUIs which can aid both novice and expert users in calibration of raw data, exploration of the dependence of mass spectra characteristics on size, time, and peak intensity, as well investigations of clustered data sets.


2017 ◽  
Vol 10 (4) ◽  
pp. 1323-1334 ◽  
Author(s):  
Camille M. Sultana ◽  
Gavin C. Cornwell ◽  
Paul Rodriguez ◽  
Kimberly A. Prather

Abstract. Single-particle mass spectrometer (SPMS) analysis of aerosols has become increasingly popular since its invention in the 1990s. Today many iterations of commercial and lab-built SPMSs are in use worldwide. However, supporting analysis toolkits for these powerful instruments are outdated, have limited functionality, or are versions that are not available to the scientific community at large. In an effort to advance this field and allow better communication and collaboration between scientists, we have developed FATES (Flexible Analysis Toolkit for the Exploration of SPMS data), a MATLAB toolkit easily extensible to an array of SPMS designs and data formats. FATES was developed to minimize the computational demands of working with large data sets while still allowing easy maintenance, modification, and utilization by novice programmers. FATES permits scientists to explore, without constraint, complex SPMS data with simple scripts in a language popular for scientific numerical analysis. In addition FATES contains an array of data visualization graphic user interfaces (GUIs) which can aid both novice and expert users in calibration of raw data; exploration of the dependence of mass spectral characteristics on size, time, and peak intensity; and investigations of clustered data sets.


2012 ◽  
Vol 12 (4) ◽  
pp. 1681-1700 ◽  
Author(s):  
R. M. Healy ◽  
J. Sciare ◽  
L. Poulain ◽  
K. Kamili ◽  
M. Merkel ◽  
...  

Abstract. An Aerosol Time-Of-Flight Mass Spectrometer (ATOFMS) was deployed to investigate the size-resolved chemical composition of single particles at an urban background site in Paris, France, as part of the MEGAPOLI winter campaign in January/February 2010. ATOFMS particle counts were scaled to match coincident Twin Differential Mobility Particle Sizer (TDMPS) data in order to generate hourly size-resolved mass concentrations for the single particle classes observed. The total scaled ATOFMS particle mass concentration in the size range 150–1067 nm was found to agree very well with the sum of concurrent High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and Multi-Angle Absorption Photometer (MAAP) mass concentration measurements of organic carbon (OC), inorganic ions and black carbon (BC) (R2 = 0.91). Clustering analysis of the ATOFMS single particle mass spectra allowed the separation of elemental carbon (EC) particles into four classes: (i) EC attributed to biomass burning (ECbiomass), (ii) EC attributed to traffic (ECtraffic), (iii) EC internally mixed with OC and ammonium sulfate (ECOCSOx), and (iv) EC internally mixed with OC and ammonium nitrate (ECOCNOx). Average hourly mass concentrations for EC-containing particles detected by the ATOFMS were found to agree reasonably well with semi-continuous quantitative thermal/optical EC and optical BC measurements (r2 = 0.61 and 0.65–0.68 respectively, n = 552). The EC particle mass assigned to fossil fuel and biomass burning sources also agreed reasonably well with BC mass fractions assigned to the same sources using seven-wavelength aethalometer data (r2 = 0.60 and 0.48, respectively, n = 568). Agreement between the ATOFMS and other instrumentation improved noticeably when a period influenced by significantly aged, internally mixed EC particles was removed from the intercomparison. 88% and 12% of EC particle mass was apportioned to fossil fuel and biomass burning respectively using the ATOFMS data compared with 85% and 15% respectively for BC estimated from the aethalometer model. On average, the mass size distribution for EC particles is bimodal; the smaller mode is attributed to locally emitted, mostly externally mixed EC particles, while the larger mode is dominated by aged, internally mixed ECOCNOx particles associated with continental transport events. Periods of continental influence were identified using the Lagrangian Particle Dispersion Model (LPDM) "FLEXPART". A consistent minimum between the two EC mass size modes was observed at approximately 400 nm for the measurement period. EC particles below this size are attributed to local emissions using chemical mixing state information and contribute 79% of the scaled ATOFMS EC particle mass, while particles above this size are attributed to continental transport events and contribute 21% of the EC particle mass. These results clearly demonstrate the potential benefit of monitoring size-resolved mass concentrations for the separation of local and continental EC emissions. Knowledge of the relative input of these emissions is essential for assessing the effectiveness of local abatement strategies.


2013 ◽  
Vol 6 (3) ◽  
pp. 5653-5691 ◽  
Author(s):  
F. Freutel ◽  
F. Drewnick ◽  
J. Schneider ◽  
T. Klimach ◽  
S. Borrmann

Abstract. Single particle mass spectrometry has proven a valuable tool for gaining information on the mixing state of aerosol particles. With the Aerodyne aerosol mass spectrometer (AMS) equipped with a light scattering probe, non-refractory components of submicron particles with diameters larger than about 300 nm can even be quantified on a single particle basis. Here, we present a new method for the analysis of AMS single particle mass spectra. The developed algorithm classifies the particles according to their components (e.g., sulphate, nitrate, different types of organics) and simultaneously provides quantitative information about the composition of the single particles. This classification algorithm was validated by applying it to data acquired in laboratory experiments with particles of known composition, and applied to field data acquired during the MEGAPOLI summer campaign (July 2009) in Paris. As shown, it is not only possible to directly measure the mixing state of atmospheric particles, but also to directly observe repartitioning of semi-volatile species between gas and particle phase during the course of the day.


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