Glacier melting represents an important flux of carbon and nitrogen (N) and affects the hydrological cycle. In this study, we presented the features of dissolved organic carbon (DOC) and N concentrations, their potential sources and export from the Muz Taw glacier in Central Asia. The average DOC and total dissolved nitrogen concentrations were 1.12 ± 1.66 and 0.62 ± 0.59 mg L in surface snow and 0.21 ± 0.04 and 0.31 ± 0.10 mg L in snowpit samples, respectively. The values from snowpit of the Muz Taw glacier were comparable to data reported from glaciers in the Tibetan Plateau but were considerably higher than those from polar regions. The C/N ratios in snow ranged from 0.7 to 11.7, indicating the high bioavailability of DOC. Mass absorption cross section of DOC at 365 nm in snow indicated that during the snow melting process, light-absorbing DOC was prone to be attached to particles, especially in the ablation zone of the Muz Taw glacier. Radiative forcing caused by DOC contributed approximately 38 ± 26% and 18 ± 9.8% of that caused by black carbon for surface snow and snowpit samples, respectively. DOC and N deposition on the glacier surface were influenced by the combined sources from anthropogenic input, wild biomass burning emission, and dust input from local regions and long range transport. Export of DOC and N from the Muz Taw glacier was estimated to be 3.47-18.5 t C yr and 5.11-10.23 t N yr respectively, based on their concentrations and current glacier mass balance. These results enhanced our understanding of the sources and cycle of DOC and N released from glaciers in Central Asia, where glacier meltwater can protect the population from drought stress.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.scitotenv.2020.138346 | DOI Listing |
Sci Total Environ
September 2024
College of Sciences, Shihezi University, Shihezi 832000, China.
Glacial changes are crucial to regional water resources and ecosystems in the Sawir Mountains. However, glacial changes, including the mass balance and glacial meltwater of the Sawir Mountains, have sparsely been reported. Three model calibration strategies were constructed including a regression model based on albedo and in-situ mass balance of Muz Taw Glacier (A-M), regression model based on albedo and geodetic mass balance of valley, cirque, and hanging glaciers (A-M), and degree-day model (DDM) to obtain a reliable glacier mass balance in the Sawir Mountains and provide the latest understanding in the contribution of glacial meltwater runoff to regional water resources.
View Article and Find Full Text PDFSci Total Environ
October 2020
Department of Environmental Science, Laboratory for Earth Surface Processes, Peking University, Beijing, China.
Light-absorbing impurities (LAIs), including black carbon (BC) and mineral dust, in snow can trigger a positive feedback. In this study, we estimate the contribution of BC and dust to glacial melting in Central Asia. Average BC and dust concentrations in the surface snow of the Muz Taw glacier are 1788 ± 1754 ng g and 172 ± 178 μg g, respectively.
View Article and Find Full Text PDFData Brief
June 2020
State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
This Data in Brief article provides a supplementary information to the dissolved organic carbon and nitrogen from the snow of Muz taw glacier in the Central Asia, which is related to the scientific article titled with "Characterization, sources and transport of dissolved organic carbon and nitrogen from a glacier in the Central Asia"[1]. Meanwhile, major ions (including Na, , NH , Ca, Mg, Cl, SO , NO , and NO ) were also reported. These data were analysed using descriptive statistics such as correlations and principle component analysis.
View Article and Find Full Text PDFSci Total Environ
July 2020
State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!