A New Algorithm for Inversion of Aerosol Size Distribution Data

Crump, James G.; Seinfeld, John H.

doi:10.1080/02786828208958576

Cited by 71 publications

(30 citation statements)

References 13 publications

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“…The particle size distribution is then obtained from the CN timeseries using well-established SMPS inversion techniques (e.g., Crump and Seinfeld 1982;Hagen and Alofs 1983;Wang and Flagan 1989;Russell et al 1995;Collins et al 2002). In this study, the CN timeseries is inverted using the TSI AIM software (which is based on the method of Wang and Flagan 1989).…”

Section: Application Of Smcamentioning

confidence: 99%

Scanning Mobility CCN Analysis—A Method for Fast Measurements of Size-Resolved CCN Distributions and Activation Kinetics

Moore

Nenes

Medina

2010

Aerosol Science and Technology

167

183

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Section: Application Of Smcamentioning

confidence: 99%

Scanning Mobility CCN Analysis—A Method for Fast Measurements of Size-Resolved CCN Distributions and Activation Kinetics

Moore

Nenes

Medina

2010

Aerosol Science and Technology

167

183

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“…A number of approaches to data inversion have been developed to overcome this (Twomey 1975;Cooper and Spielman 1976;Alofs and Balacumar 1982;Crump and Seinfeld 1982;Hagen and Alofs 1983;Maher and Laird 1985;Markowski 1987;Wolfenbarger and Seinfeld 1990;Lloyd et al 1997). These data inversion routines attempt to nd a solution vector that approaches a solution of Equation (3) while requiring that each of the N i¸0 .…”

Section: Solving the Matrix Equationmentioning

confidence: 99%

Improved Inversion of Scanning DMA Data

Collins

Flagan

Seinfeld

2002

Aerosol Science and Technology

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150

126

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Recovery of aerosol size distributions from either stepping or scanning mode differential mobility analyzer (DMA) measurements requires an accurate description of the characteristics of the DMA itself, as well as certain properties of the aerosol. Inversion of scanning DMA data is further complicated by the nonunique relationship between the time a particle exits the DMA and the time it is ultimately detected. Without an accurate description of this relationship, and an appropriate method of accounting for it, inverted distributions will be broadened and skewed relative to the true distribution. A simpli ed approach to inversion of scanning DMA data is described here in which adjustment of the raw data to account for the delay time distribution associated with the instrument is accomplished prior to nal inversion. This provides the exibility to utilize more accurate descriptions of the delay time distribution and the DMA transfer function than is feasible if the inversion is to be accomplished in one step as described by Russell et al. (1995). The accuracy of this procedure has been demonstrated through analysis of actual as well as test-case data.

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“…This requires the use of calibrations to determine collection efficiencies of each stage as a function of particle size. Unfortunately, it is generally impossible to obtain a definitive solution, as the inversion problem is underdetermined and ill-posed (Crump and Seinfeld, 1982).…”

Section: Introductionmentioning

confidence: 99%