Modeling Heating Rate to Distinguish Black Carbon from Other Impurities in Snow

Abstract:

Samples of snow were collected on Mount Rainier, Washington, and near Grand Junction, Colorado, to determine the concentration of black carbon and other light-absorbing impurities in the snow. Filtered samples were analyzed by a Light Absorption Heating Method (LAHM) instrument, which uses an intense beam of white light to radiatively heat the darkened filters. A novel methodological feature of this work is the fitting of the resulting temperature profiles to an exponential function of the form B(1-e^-t/to), in which the pre-exponential factor describes the steady-state temperature increase eventually achieved, and t_o is a response time that characterizes the rate of temperature increase. We show that B provides an accurate measure of impurity loading when calibrated against the manufacturer-supplied algorithm. We also present evidence that the response time is characteristic of the composition of the impurity, in that loadings prepared from soil samples, presumed to contain significant non-black-carbon impurities, exhibited LAHM heating rates significantly slower (t_o >10 s) compared to filters spiked with fullerene, a black-carbon surrogate (t_o∼5 s). Applying this methodology to snow on Mount Rainier, we obtained black-carbon-equivalent concentrations ranging from 1 to 8 ng/g, and even shorter response times (t_o =3-4 s).