An Enhanced Procedure for the Merging of Atmospheric Particle Size Distribution Data Measured Using Electrical Mobility and Time-of-Flight Analysers

2010 ◽  
Vol 44 (11) ◽  
pp. 930-938 ◽  
Author(s):  
David C. S. Beddows ◽  
Manuel Dall'osto ◽  
Roy M. Harrison
Author(s):  
Steven L. Alderman ◽  
Chen Song ◽  
Serban C. Moldoveanu ◽  
Stephen K. Cole

AbstractThe relatively volatile nature of the particulate matter fraction of e-cigarette aerosols presents an experimental challenge with regard to particle size distribution measure-ments. This is particularly true for instruments requiring a high degree of aerosol dilution. This was illustrated in a previous study, where average particle diameters in the 10-50 nm range were determined by a high-dilution, electrical mobility method. Total particulate matter (TPM) masses calculated based on those diameters were orders of magnitude smaller than gravimetrically determined TPM. This discrepancy was believed to result from almost complete particle evaporation at the dilution levels of the electrical mobility analysis. The same study described a spectral transmission measurement of e-cigarette particle size in an undiluted state, and reported particles from 210-380 nm count median diameter. Observed particle number concentrations were in the 10Described here is a study in which e-cigarette aerosols were collected on Cambridge filters with adsorbent traps placed downstream in an effort to capture any material passing through the filter. Amounts of glycerin, propylene glycol, nicotine, and water were quantified on the filter and downstream trap. Glycerin, propylene glycol, and nicotine were effciently captured (> 98%) by the upstream Cambridge filter, and a correlation was observed between filtration efficiency and the partial vapor pressure of each component. The present analysis was largely inconclusive with regard to filter efficiency and particle-vapor partitioning of water. [Beitr. Tabakforsch. Int. 26 (2014) 183-190]


2021 ◽  
Author(s):  
Pak Lun Fung ◽  
Martha Arbayani Zaidan ◽  
Ola Surakhi ◽  
Sasu Tarkoma ◽  
Tuukka Petäjä ◽  
...  

Abstract. In air quality research, often only particle mass concentrations as indicators of aerosol particles are considered. However, the mass concentrations do not provide sufficient information to convey the full story of fractionated size distribution, which are able to deposit differently on respiratory system and cause various harm. Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. From the raw data the ambient size distribution is determined utilising a suite of inversion algorithms. However, the inversion problem is quite often ill-posed and challenging to invert. Due to the instrumental insufficiency and inversion limitations, models for fractionated particle size distribution are of great significance to fill the missing gaps or negative values. The study at hand involves a merged particle size distribution, from a scanning mobility particle sizer (NanoSMPS) and an optical particle sizer (OPS) covering the aerosol size distributions from 0.01 to 0.42 μm (electrical mobility equivalent size) and 0.3 μm to 10 μm (optical equivalent size) and meteorological parameters collected at an urban background region in Amman, Jordan in the period of 1st Aug 2016–31st July 2017. We develop and evaluate feed-forward neural network (FFNN) models to estimate number concentrations at particular size bin with (1) meteorological parameters, (2) number concentration at other size bins, and (3) both of the above as input variables. Two layers with 10–15 neurons are found to be the optimal option. Lower model performance is observed at the lower edge (0.01 


2015 ◽  
Vol 133 ◽  
pp. 30-43 ◽  
Author(s):  
David R. Ochsenbein ◽  
Stefan Schorsch ◽  
Fabio Salvatori ◽  
Thomas Vetter ◽  
Manfred Morari ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document