Fire Technology

, Volume 51, Issue 2, pp 247–269 | Cite as

Quantification of Optical and Physical Properties of Combustion-Generated Carbonaceous Aerosols (< PM2.5) Using Analytical and Microscopic Techniques

  • Inoka Eranda PereraEmail author
  • Charles D. Litton


A series of experiments were conducted to quantify and characterize the optical and physical properties of combustion-generated aerosols during both flaming and smoldering combustion of three materials common to underground mines—Pittsburgh Seam coal, Styrene Butadiene Rubber (a common mine conveyor belt material), and Douglas-fir wood—using a combination of analytical and gravimetric measurements. Laser photometers were utilized in the experiments for continuous measurement of aerosol mass concentrations and for comparison to measurements made using gravimetric filter samples. The aerosols of interest lie in the size range of tens to a few hundred nanometers, out of range of the standard photometer calibration. To correct for these uncertainties, the photometer mass concentrations were compared to gravimetric samples to determine if consistent correlations existed. The response of a calibrated and modified combination ionization/photoelectric smoke detector was also used. In addition, the responses of this sensor and a similar, prototype ionization/photoelectric sensor, along with discrete angular scattering, total scattering, and total extinction measurements, were used to define in real time the size, morphology, and radiative transfer properties of these differing aerosols that are generally in the form of fractal aggregates. SEM/TEM images were also obtained in order to compare qualitatively the real-time, continuous experimental measurements with the visual microscopic measurements. These data clearly show that significant differences exist between aerosols from flaming and from smoldering combustion and that these differences produce very different scattering and absorption signatures. The data also indicate that ionization/photoelectric sensors can be utilized to measure continuously and in real time aerosol properties over a broad spectrum of applications related to adverse environmental and health effects.


Carbonaceous aerosols Flaming Smoldering Photometry Particulate matter Smoke 

List of Symbols


Number mean Diameter


Fractal dimension


Diameter of primary particles (nm)


Count mean diameter (cm)


Ion diffusion coefficient (cm3/s)


Incident intensity of the light


Reduced intensity of light


Fractal pre-factor


Path length (m)


Aerosol mass concentration (mg/m3)


Mass of a fractal aggregate


Number of primary particles per aggregate


Number of aggregate per cm3


Radius of gyration


Size parameter


Mass specific extinction (m2/g)


Mass specific scattering (m2/g)


Mass specific absorption (m2/g)


Wavelength (nm)


Particle density (g/m3)



The authors would like to acknowledge Diane Schwegler-Berry at the National Institute for Occupational Safety and Health (NIOSH), Morgantown, WV, for her help in SEM/TEM imaging.


  1. 1.
    Bond TC, Bergstrom RW (2006) Light absorption by carbonaceous particles: an investigative review. Aerosol Sci Technol 40:27–67.CrossRefGoogle Scholar
  2. 2.
    Butler KM Mulholland GW (2004) Generation and transport of smoke components, Fire Technol 40:149–176.CrossRefGoogle Scholar
  3. 3.
    Blomqvist P, Bror P, Simonson M (2007) Fire emissions of organics into the atmosphere, Fire Technol 43:213–231.CrossRefGoogle Scholar
  4. 4.
    Chung A, Chang DPY, Kleeman MJ, Perry KD, Cahill TA, Dutcher D, McDougall EM, Stroud K (2001) Comparison of real-time instruments used to monitor airborne particulate matter. J Air Waste Manag Assoc 51 109–120.CrossRefGoogle Scholar
  5. 5.
    Edwards JC, Morrow GS (1995) Development of coal combustion sensitivity tests for smoke detectors. United States Department of Interior, Report of Investigation 9551:1–12.Google Scholar
  6. 6.
    Farias TL, Carvalho MG, Koylu UO, Faeth GM (1995) Computational evaluation of approximate Rayleigh–Debye–Gans/fractal-aggregate theory for the absorption and scattering properties of soot. J Heat Transf 117:152–159.CrossRefGoogle Scholar
  7. 7.
    Kelly WP, Mcmurry PH (1992) Measurement of particle density by inertial classification of differential mobility analyzer generated monodisperse aerosols. Aerosol Sci Technol 17:199–212.CrossRefGoogle Scholar
  8. 8.
    Kingham S, Durand M, Aberkane T, Harrison J, Wilson JG, Epton M (2006) Winter comparison of TEOM, MiniVol and DustTrak PM10 monitors in a woodsmoke environment. Atmos Environ 40:338–347.CrossRefGoogle Scholar
  9. 9.
    Kinsey JS, Mitchell, WA, Squier WC, Linna K, King FG, Logan R, Dong YJ, Thompson GJ, Clark NN (2006) Evaluation of methods for the determination of diesel-generated fine particulate matter: physical characterization results. J Aerosol Sci 37:63–87.CrossRefGoogle Scholar
  10. 10.
    Lehocky AH, Williams PL (1996) Comparison of respirable samplers to direct-reading real time aerosol monitors for measuring coal dust. Am Ind Hyg Assoc J 57:1013–1018.CrossRefGoogle Scholar
  11. 11.
    Litton CD (2002) The use of light scattering and ion chamber responses for the detection of fires in diesel contaminated atmospheres. Fire Saf J 37:409–425.CrossRefGoogle Scholar
  12. 12.
    Litton CD (2009) Laboratory evaluation of smoke detectors for use in underground mines. Fire Saf J 44:387–393.CrossRefGoogle Scholar
  13. 13.
    Litton CD, Smith KR, Edwards R, Allen T (2004) Combined optical and ionization measurement techniques for inexpensive characterization of micrometer and submicrometer aerosols. Aerosol Sci Technol 38:1054–1062.CrossRefGoogle Scholar
  14. 14.
    Litton CD (1977) A mathematical model for ionization-type smoke detectors and the reduced source approximation. Fire Technol 13:261–28.CrossRefGoogle Scholar
  15. 15.
    Litton CD (1979) Optimizing ionization-type smoke detectors. Fire Technol 15:25–42.CrossRefGoogle Scholar
  16. 16.
    Moosmuller H, Arnott WP, Rogers CF, Bowen JL, Gillies JA, Pierson WR, Collins JF, Durbin TD, Norbeck JM (2001a) Time-resolved characterization of diesel particulate emissions. 2. Instruments for elemental and organic carbon measurements. Environ Sci Technol 35:1935–1942.CrossRefGoogle Scholar
  17. 17.
    Perera IE, Litton CD (2011) A detailed study of the properties of smoke particles produced from both flaming and non-flaming combustion of common mine combustibles. Fire Saf Sci 10:213–226. doi: 10.3801/IAFSS.FSS.10-213.
  18. 18.
    Ramachandran G, Adgate JL, Hill N, Sexton K, Pratt GC, Bock D (2000) Comparison of short-term variations (15-minute averages) in outdoor and indoor PM2.5 concentrations. J Air Waste Manag Assoc 50:1157–1166.CrossRefGoogle Scholar
  19. 19.
    Slowik JG et al (2007) An inter-comparison of instruments measuring black carbon content of soot particles, Aerosol Sci Technol 41:295–314.CrossRefGoogle Scholar
  20. 20.
    Sorensen CM (2001) Light scattering by fractal aggregates: a review. Aerosol Sci Technol 35:648–687.CrossRefGoogle Scholar
  21. 21.
    Wolin SD, Noah LR, Frederic L, James AM, Frederick WM, Jose LT (2001) Measurements of smoke characteristics in HVAC ducts. Fire Technol 37:363–395.CrossRefGoogle Scholar
  22. 22.
    Yanosky JD, Williams PL, MacIntosh DL (2002) A comparison of two direct-reading aerosol monitors with the federal reference method for PM2.5 in indoor air. Atmos Environ 36:107–113.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Pittsburgh Research Laboratory, Fires and Explosions Branch, Office of Mine Safety and Health ResearchNational Institute for Occupational Safety and Health, Centers for Disease Control & Prevention, U. S. Department of Health & Human ServicesPittsburghUSA

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