4.8 Article

Varying thermal structure controls the dynamics of CO2 emissions from a subtropical reservoir, south China

期刊

WATER RESEARCH
卷 178, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2020.115831

关键词

CO2 emission; Thermal stratification; Mixing period; Groundwater-fed reservoir; China

资金

  1. National Natural Science Foundation of China [41977166, 41572234, 41702271]
  2. Guangxi Natural Science Foundation [2017GXNSFFA198006, 2018GXNSFBA138031]
  3. Special Fund for Basic Scientific Research of Institute of Karst Geology, CAGS [2020004]

向作者/读者索取更多资源

Thermal stratification and mixing are important to the physicochemical composition of reservoirs and lakes and impact their water quality and biogeochemical cycles. However, it remains unclear how thermal stratification and mixing process control the exchange of CO2 between surface water and the Earth's atmosphere. To address this issue, we examine the temporal characteristics of some physicochemical parameters, partial pressure of CO2 (pCO(2)), the delta C-13(DIC), and CO2 emission from a typical karst groundwater-fed reservoir (Dalongdong reservoir). During the 23 month study (2016-2018) thermal stratification limited CO2 emission, in part from photosynthetic uptake of CO2, from early April to late October, while mixing processes stimulated CO2 emission of CO2 generated from organic matter remineralization in bottom water from October to April. The Dalongdong reservoir is an atmospheric source of CO2 for most of the study period; however, during periods of stratification, approximately 0.37 +/- 0.44 Gg CO2 (1 Gg = 10(9)g) dissolved into the water from the atmosphere, while approximately 6.24 +/- 3.73 Gg CO2 was lost to the atmosphere during periods lacking stratification. Limited emissions during stratified period may thus represent a negative feedback to CO2 contributions to global warming, which has increased lengths of stratified periods. These study results are important to optimize sampling monitoring strategies to reduce errors of regional CO2 emission estimation. (C) 2020 Elsevier Ltd. All rights reserved.

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