The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
An Algorithm for Combining Electrical Mobility and Aerodynamic Size Distributions Data when Measuring Ambient Aerosol Special Issue of Aerosol Science and Technology on Findings from the Fine Particulate Matter Supersites Program
Open accessAbstract
Ambient aerosol particles vary in size from a few nanometers to several micrometers.No instrument is currently available to cover such a wide size range, and so a combination of several instruments is usually used.One such combination is that of electrical mobility classifiers and an aerodynamic sizer.Because of the differences in measurement principles between the instruments, difficulties arise in the combination of the measurements into a single size distribution.Here we report a simple algorithm that was developed to combine aerosol size distributions measured with commercially available scanning mobility particle sizers (SMPS; TSI Inc.) and an aerodynamic particle sizer (APS; TSI Inc.).This algorithm was tested during July 2001 in the Pittsburgh Air Quality Study.The aerosol during the study had both urban and regional origin and is characteristic of urban atmosphere in the Northeastern U.S. The integrated volume concentrations from the SMPS-APS showed a good correlation with PM 2.5 mass concentration measurements using a TEOM.The relation of the aerosol mass to its volume is an "effective" density, a ratio of the bulk aerosol density to the shape factor.As a result of the comparison with the TEOM the ambient aerosol in the Pittsburgh area was found to have an effective density of 1.5 ± 0.3 g cm -3 .Given that the aerosol during the study was found to always contain water, the particles are expected to be spherical and thus the shape factor may be assumed to be 1.This assumption has been supported by a comparison with the MOUDI, using the aerosol density of 1.5 g/cm 3 .It should be noted that the estimated aerosol density and the shape factor are applicable to this study only and may be different in other locations.
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Cites
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Self-citationAerosol Measurement: Principles, Techniques, and Applications
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Cabada, J. C., Rees, S., Takahama, S., Khlystov, A., Pandis, S. N., Davidson, C. I., & Robinson, A. L. (2004) · Atmospheric Environment · doi:10.1016/j.atmosenv.2004.03.004 · Cited by 170
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Self-citationConcentration measurement and counting efficiency for the aerodynamic particle sizer 3320
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Mass balance closure and the Federal Reference Method for PM2.5 in Pittsburgh, Pennsylvania
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A review of biomass burning: Emissions and impacts on air quality, health and climate in China
Chen, J., Li, C., Ristovski, Z., Milic, A., Gu, Y., Islam, M. S., Wang, S., Hao, J., Zhang, H., He, C., et al. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2016.11.025 · Cited by 1,262
Overview of the Alaskan Layered Pollution and Chemical Analysis (ALPACA) Field Experiment
Simpson, W. R., Mao, J., Fochesatto, G. J., Law, K. S., DeCarlo, P. F., Schmale, J., Pratt, K. A., Arnold, S. R., Stutz, J., Dibb, J. E., et al. (2024) · ACS ES&T Air · doi:10.1021/acsestair.3c00076 · Cited by 42
Metadata
- Authors
- Khlystov, A., Stanier, C., & Pandis, S. N.
- Venue
- Aerosol Science and Technology
- Publisher
- Informa UK Limited
- Published
- 2004-12
- Volume
- 38
- Issue
- sup1
- Pages
- 229-238
- ISSN
- 0278-6826 (ISSN-L)
- 1521-7388
- OpenAlex
- W2063094669
- Cited by
- 255
- References
- 10
- FWCI
- 4.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Khlystov, A., Stanier, C., & Pandis, S. N. (2004). An Algorithm for Combining Electrical Mobility and Aerodynamic Size Distributions Data when Measuring Ambient Aerosol Special Issue of Aerosol Science and Technology on Findings from the Fine Particulate Matter Supersites Program. Aerosol Science and Technology. https://doi.org/10.1080/02786820390229543
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