Concentrations and source regions of light-absorbing particles in snow/ice in northern Pakistan and their impact on snow albedo

摘要

Black carbon (BC), water-insoluble organic carbon (OC), and mineral dust are important particles in snow and ice which significantly reduce albedo and accelerate melting. Surface snow and ice samples were collected from the Karakoram-Himalayan region of northern Pakistan during 2015 and 2016 in summer (six glaciers), autumn (two glaciers), and winter (six mountain valleys). The average BC concentration overall was 2130 +/- 1560 ng g(-1) in summer samples, 2883 +/- 3439 ng g(-1) in autumn samples, and 992 +/- 883 ng g(-1) in winter samples. The average waterinsoluble OC concentration overall was 1839 +/- 1108 ng g(-1) in summer samples, 1423 +/- 208 ng g(-1) in autumn samples, and 1342 +/- 672 ng g(-1) in winter samples. The overall concentration of BC, OC, and dust in aged snow samples collected during the summer campaign was higher than the concentration in ice samples. The values are relatively high compared to reports by others for the Himalayas and the Tibetan Plateau. This is probably the result of taking more representative samples at lower elevation where deposition is higher and the effects of ageing and enrichment are more marked. A reduction in snow albedo of 0.1-8.3% for fresh snow and 0.9-32.5% for aged snow was calculated for selected solar zenith angles during daytime using the Snow, Ice, and Aerosol Radiation (SNICAR) model. The daily mean albedo was reduced by 0.07-12.0 %. The calculated radiative forcing ranged from 0.16 to 43.45 W m(-2) depending on snow type, solar zenith angle, and location. The potential source regions of the deposited pollutants were identified using spatial variance in wind vector maps, emission inventories coupled with backward air trajectories, and simple region-tagged chemical transport modeling. Central, south, and west Asia were the major sources of pollutants during the sampling months, with only a small contribution from east Asia. Analysis based on the Weather Research and Forecasting (WRF-STEM) chemical transport mode