Contribution of dust and elemental carbon to the reduction of snow albedo in the Indian Himalaya and the Finnish Arctic

Light-absorbing impurities (LAI) have the potential to substantially affect snow albedo, with subsequent changes on snow melt and impact on climate. To more accurately quantify the snow albedo, the contribution from different LAI needs to be assessed. Here we estimate the main LAI components, elemental carbon (EC) (as a proxy for black carbon) and mineral dust in snow from Indian Himalaya and compared it to snow samples from Arctic Finland. The impurities are collected onto quartz filters and are analyzed thermal-optically for EC, as well as with an additional optical measurement to estimate the light-absorption of dust separately on the filters. Laboratory tests were conducted using substrates containing soot and mineral particles specially prepared to test the experimental setup. Analyzed ambient snow samples show EC concentrations that are in the same range as presented by previous research, for each respective region. In terms of the mass absorption cross section (MAC) our ambient EC had surprisingly about half of the MAC value compared to our laboratory standard EC (chimney soot), suggesting a less light absorptive EC in the snow, which has consequences for the snow albedo reduction caused by EC. In the Himalayan samples, larger contributions by dust (in the range of 50 % or greater for the light absorption caused by the LAI) highlighted the importance of dust acting as a light absorber in the snow. Moreover, EC concentrations in the Indian samples, acquired from a 120 cm deep snow pit (covering possibly the last five years of snow fall), suggest an increase in both EC and dust, while at the same time there is a tendency for a reduction in the MAC value with snow depth. This work emphasizes the complexity in determining the snow albedo, showing that LAI concentrations alone might not be sufficient, but additional transient effects on the light-absorbing properties of the EC need to be considered and studied in the snow. Equally imperative is to confirm the spatial and temporal representativeness of these data by comparing data from several and longer pits explored at the same time.