scholarly journals Interactive comment on “Direct links between hygroscopicity and mixing state of ambient aerosols: Estimating particle hygroscopicity from their single particle mass spectra” by Xinning Wang et al

2020 ◽  
Author(s):  
Anonymous
2016 ◽  
Vol 132 ◽  
pp. 123-132 ◽  
Author(s):  
Honglei Wang ◽  
Junlin An ◽  
Lijuan Shen ◽  
Bin Zhu ◽  
Li Xia ◽  
...  

2020 ◽  
Author(s):  
Xinning Wang ◽  
Xiaofei Wang ◽  
Xin Yang

Abstract. Hygroscopicity plays a crucial role in determining aerosol optical properties and aging processes in the atmosphere. We investigated submicron aerosol hygroscopicity and composition by connecting an aerosol time-of-flight mass spectrometer (ATOFMS) to the downstream of a hygroscopic tandem differential mobility analyzer (HTDMA), to simultaneously characterize hygroscopicities and chemical compositions of ambient aerosols in Shanghai, China. Major particle types, including biomass burning, EC, Dust/Ash, organics particles, cooking particles and sea salt, were shown to have distinct hygroscopicity distributions. It is also found that particles with stronger hygroscopicities were more likely to have higher effective densities. Based on the measured hygroscopicity-composition relations, we developed a statistical method to estimate ambient particle hygroscopicity just from their mass spectra. This method was applied to another ambient ATOFMS dataset sampled from September 12nd to 28th, 2012 in Shanghai, and it is found that ambient particles were present in three major hygroscopicity modes, whose growth factors at relative humidity 85 % peaked at 1.05, 1.42 and 1.60, respectively. The temporal variations of the estimated particle hygroscopicity were consistent with the back-trajectory analysis and atmospheric visibility observations. These hygroscopicity estimation results with single particle mass spectra analysis can provide critical information on particulate water content, particle source apportionment and aging processes.


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.


2014 ◽  
Vol 14 (12) ◽  
pp. 6289-6299 ◽  
Author(s):  
R. M. Healy ◽  
N. Riemer ◽  
J. C. Wenger ◽  
M. Murphy ◽  
M. West ◽  
...  

Abstract. A newly developed framework for quantifying aerosol particle diversity and mixing state based on information-theoretic entropy is applied for the first time to single particle mass spectrometry field data. Single particle mass fraction estimates for black carbon, organic aerosol, ammonium, nitrate and sulfate, derived using single particle mass spectrometer, aerosol mass spectrometer and multi-angle absorption photometer measurements are used to calculate single particle species diversity (Di). The average single particle species diversity (Dα) is then related to the species diversity of the bulk population (Dγ) to derive a mixing state index value (χ) at hourly resolution. The mixing state index is a single parameter representation of how internally/externally mixed a particle population is at a given time. The index describes a continuum, with values of 0 and 100% representing fully external and internal mixing, respectively. This framework was applied to data collected as part of the MEGAPOLI winter campaign in Paris, France, 2010. Di values are low (~ 2) for fresh traffic and wood-burning particles that contain high mass fractions of black carbon and organic aerosol but low mass fractions of inorganic ions. Conversely, Di values are higher (~ 4) for aged carbonaceous particles containing similar mass fractions of black carbon, organic aerosol, ammonium, nitrate and sulfate. Aerosol in Paris is estimated to be 59% internally mixed in the size range 150–1067 nm, and mixing state is dependent both upon time of day and air mass origin. Daytime primary emissions associated with vehicular traffic and wood-burning result in low χ values, while enhanced condensation of ammonium nitrate on existing particles at night leads to higher χ values. Advection of particles from continental Europe containing ammonium, nitrate and sulfate leads to increases in Dα, Dγ and χ. The mixing state index represents a useful metric by which to compare and contrast ambient particle mixing state at other locations globally.


2013 ◽  
Vol 6 (11) ◽  
pp. 3131-3145 ◽  
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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