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Rapid daily change in surface water pCO2 and CO2 evasion: A case study in a subtropical eutrophic lake in Southern USA

Author:
Xu, Y. Jun, Xu, Zhen, Yang, Rongjie
Source:
Journal of hydrology 2019 v.570 pp. 486-494
ISSN:
0022-1694
Subject:
ambient water, aquatic ecosystems, carbon, carbon dioxide, carbon dioxide production, case studies, eutrophication, lakes, metabolism, solar radiation, surface water, temperature, uncertainty, winter, Southeastern United States
Abstract:
Evasion of carbon dioxide (CO2) from lakes is a significant component in the continental carbon balance, but most current CO2 evasion estimates ignore daily CO2 fluctuations. To test the hypothesis that partial pressure of CO2 (pCO2) and CO2 evasion vary throughout a day due to biological processes driven by solar radiation, we conducted in-situ pCO2 and ambient water measurements over eleven 10-h periods in a subtropical, eutrophic shallow lake from November 2017 to May 2018. In-situ measurements were performed at 7:00, 10:00, 14:00, and 17:00 Central Standard Time of the United States (CST), and CO2 evasion rates were estimated based on the field pCO2 records. Strong daily declining trends of pCO2 and CO2 flux were found throughout the seasons except for one winter day with unusually low temperatures. At 7:00, 10:00, 14:00, and 17:00 CST of a day, average pCO2 were 1131, 839, 345 and 205 µatm, respectively, while average CO2 fluxes were 80, 67, −10, and −34 mmol m2 h−1. Significant differences were found in average pCO2 between any two measured time points in a day, while significant reductions in CO2 flux were observed between 10:00 and 14:00 CST and between 14:00 and 17:00 CST. pCO2 and CO2 flux dynamics were most likely driven by the air-water exchanges during nighttime hours and mainly driven by aquatic metabolism in the daytime. These findings suggest possible large uncertainties in the estimation of carbon emitted from trophic lakes, highlighting the need for further research on diurnal pCO2 fluctuation from different aquatic ecosystems to improve CO2 evasion estimation.
Agid:
6289384