The mass and number size distributions of black carbon aerosol over Europe

C. Reddington,G. McMeeking,G. Mann,H. Coe,M. G. Frontoso,Dantong Liu,M. Flynn,D. Spracklen,K. Carslaw

Published 2013 in Atmospheric Chemistry and Physics

ABSTRACT

Abstract. Black carbon-containing aerosol particles play an important role in the direct and indirect radiative forcing of climate. However, the magnitude and sign of the net radiative effect is strongly dependent on the physical properties of the black carbon (BC) component of the particles, such as mass concentration, number size distribution and mixing state. Here we use a global aerosol model combined with aircraft measurements of BC particle number and size from the Single Particle Soot Photometer (SP2) to assess the realism with which these physical properties are predicted by global models. The comparison reveals a substantial mismatch between the measured and modelled BC size distribution over the size range of the SP2 instrument (90–400 nm BC diameter). The model predicts BC particle number concentrations a factor ~3.5–5.7 higher than measured and a mode diameter that is ~40–65 nm smaller than observed. More than ~90% of the model particles with dry diameters g260 nm contain BC, while the observations suggest only 14% on average. These model–observation biases in the BC properties are considerably greater than for the overall particle distribution, suggesting that the discrepancy is associated with model assumptions about the size and mixing state of the emitted carbonaceous particles. We expect the discrepancy in BC size distribution to be common among most global aerosol models, with implications for model estimates of absorption optical depth and direct radiative forcing.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    Atmospheric Chemistry and Physics

  • Publication date

    2013-05-14

  • Fields of study

    Physics, Chemistry, Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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