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Natural and anthropogenic impacts on the DOC characteristics in the Yellow River continuum

论文题目:

Natural and anthropogenic impacts on the DOC characteristics in the Yellow River continuum

英文论文题目:

Natural and anthropogenic impacts on the DOC characteristics in the Yellow River continuum

第一作者:

温志丹

英文第一作者:

wenzhidan

联系作者:

宋开山

英文联系作者:

songkaishan

外单位作者单位:

 

英文外单位作者单位:

 

发表年度:

2021

:

287

:

 

页码:

117231-117231

摘要:

The Yellow River is the second largest river in China. Carbon transport by the Yellow River has significant influence on riverine carbon cycles in Asia. During the wet season, the riverine carbon was mainly found in dissolved form, i.e., dissolved organic carbon (DOC), along the entire course of the river. The distinct spatial variations of DOC concentration were observed at different reaches of the mainstream (p<0.01), while the highest mean DOC concentration was generally observed at midstream (4.13±0.91mg/L). Carbon stable isotope analysis delta13C and C: N ratio of DOC, evidenced the sources of DOC in headwater and upstream were primarily the terrestrial plants (94% and 61%), but it was changed to soil organic matter (SOM) in mid- and downstream (36% and 37%), and the contribution of sewage to DOC were also increased to 17% and 18%. In the whole mainstream of the Yellow River, water temperature (WT) had a significant impact on DOC concentration, and it could explain 67% of the DOC variance. However, in a large catchment, the driving mechanisms on the DOC variations in headwaters will not necessarily be those controlling DOC trends in downstream. The study firstly quantified, in headwater and upstream, the natural factors explained as much as 65% and 73% of the DOC variations, respectively. In mid- and downstream areas, DOC was significantly influenced by the amount of wastewater discharged by the industry and the use of chemical fertilizers (p<0.05). These findings may facilitate a better assessment of global riverine carbon cycling and may help to reveal the importance of the balance between development and environmental sustainability with the changing DOC transport features in the Yellow River due to human disturbances.

英文摘要:

The Yellow River is the second largest river in China. Carbon transport by the Yellow River has significant influence on riverine carbon cycles in Asia. During the wet season, the riverine carbon was mainly found in dissolved form, i.e., dissolved organic carbon (DOC), along the entire course of the river. The distinct spatial variations of DOC concentration were observed at different reaches of the mainstream (p<0.01), while the highest mean DOC concentration was generally observed at midstream (4.13±0.91mg/L). Carbon stable isotope analysis delta13C and C: N ratio of DOC, evidenced the sources of DOC in headwater and upstream were primarily the terrestrial plants (94% and 61%), but it was changed to soil organic matter (SOM) in mid- and downstream (36% and 37%), and the contribution of sewage to DOC were also increased to 17% and 18%. In the whole mainstream of the Yellow River, water temperature (WT) had a significant impact on DOC concentration, and it could explain 67% of the DOC variance. However, in a large catchment, the driving mechanisms on the DOC variations in headwaters will not necessarily be those controlling DOC trends in downstream. The study firstly quantified, in headwater and upstream, the natural factors explained as much as 65% and 73% of the DOC variations, respectively. In mid- and downstream areas, DOC was significantly influenced by the amount of wastewater discharged by the industry and the use of chemical fertilizers (p<0.05). These findings may facilitate a better assessment of global riverine carbon cycling and may help to reveal the importance of the balance between development and environmental sustainability with the changing DOC transport features in the Yellow River due to human disturbances.

刊物名称:

Environmental pollution

英文刊物名称:

Environmental pollution

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参与作者:

Z. Wen, K. Song, Y. Shang, L. Lyu, H. Tao and G. Liu

英文参与作者:

Z. Wen, K. Song, Y. Shang, L. Lyu, H. Tao and G. Liu