Dissolved organic carbon in snow cover of the Chinese Altai Mountains, Central Asia: Concentrations, sources and light-absorption properties

摘要

Dissolved organic carbon (DOC) in snow plays an important role in river ecosystems that are fed by snowmelt water. However, limited knowledge is available on the DOC content in snow of the Chinese Altai Mountains in Central Asia. In this study, DOC in the snow cover of the Kayiertesi river basin, southern slope of Altai Mountains, was investigated during November 2016 to April 2017. The results showed that average concentrations of DOC in the surface snowcover (1.01 +/- 0.52 mgL(-1)) were only a little higher than those in glaciers of the Tibetan Plateau, European Alps, and Alaska, but much higher than in Greenland Ice Sheet. Depth variations of DOC concentrations from snowpack profiles indicated higher values in the surface layer. During the observation period, scavenging efficiency for DOC in snow cover is estimated to be 0.15 +/- 0.10, suggesting that DOC in snow can be affected more by the meltwater during ablation season than during accumulation season. The average mass absorption cross section at 365 nm and the absorption Angstrom exponent of DOC were 0.45 +/- 0.35 m(2) g(-1) and 2.59 +/- 1.03, respectively, with higher values in March and April 2017. Fraction of radiative forcing caused by DOC relative to black carbon accounted for about 10.5%, implying DOC is a non-ignorable light-absorber of solar radiation in snow of the Altai regions. Backward trajectories analysis and aerosol vertical distribution images from satellites showed that DOC in the snow of the Altai Mountains was mainly influenced by air masses from Central Asia, Western Siberia, the Middle East, and some even from Europe. Biomass burning and organic carbon mixed with mineral dust contributed significantly to the DOC concentration. This study highlights the effects of DOC in the snow cover for radiative forcing and the need to study carbon cycling for evaluation of quality of the down-streams ecosystems. (c) 2018 Elsevier B.V. All rights reserved.