Daily CO₂ partial pressure and CO₂ outgassing in the upper Yangtze River basin: a case study of Longchuanjiang, China

Abstract. Rivers have been under sampled to establish them as sinks or sources of the atmospheric carbon oxide (CO₂). Such poor coverage is well known for tropical and sub-tropical, particularly monsoon driven rivers. An unprecedented high-temporal-resolution (daily) sampling during July 2008–August 2009 were conducted from the Longchuanjiang River of the upper Yangtze basin, a subtropical monsoon river in China to reveal the daily-to-seasonal dynamics of the partial pressure of CO₂ (pCO₂) and CO₂ degassing flux from the river. The pCO₂ levels were supersaturated in CO₂ with respect to atmospheric equilibrium (380 μatm) during the entire survey period with obvious daily and seasonal variations, ranging from 450 to 63 000 μatm with an average of 3900 μatm. pCO₂ values in the surface water in the wet season were relatively low, except flooding period in November, due to a dilution effect by heavy rainfall. However, both daily and monthly minimal and maximal pCO₂ also occurred in this period. In contrast, the pCO₂ levels in the dry season were much higher, mainly resulted from lower pH by anthropogenic activities. Net CO₂ flux and pCO₂ were strongly correlated with pH, but weakly with water temperature, dissolved inorganic carbon and water discharge, and uncorrelated with particulate nutrients and biogenic elements. The estimated water-to-air CO₂ degassing flux in the Longchuanjiang River was about 110 mol m⁻² yr⁻¹, with the upper limit of 460 mol m⁻² yr⁻¹. Our study also indicated that among the total organic carbon remobilized through soil erosion, around 17% (11 400 t C yr⁻¹) of was emitted to the atmosphere, 52% (35 000 t C yr⁻¹) deposited in the river-reservoirs system and 31% (21 000 t C yr⁻¹) exported further downstream. High spatial and temporal resolution of estimates of CO₂ emission from the world large rivers is required due to that catchment characteristics and anthropogenic activities are extremely heterogeneous in space and time.