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

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).