Spatial variability in surface-water pCO₂ and gas exchange in the world's largest semi-enclosed estuarine system: St. Lawrence Estuary (Canada)

Abstract. The incomplete spatial coverage of CO₂ partial pressure (pCO₂) measurements across estuary types represents a significant knowledge gap in current regional- and global-scale estimates of estuarine CO₂ emissions. Given the limited research on CO₂ dynamics in large estuaries and bay systems, as well as the sources of error in the calculation of pCO₂ (carbonic acid dissociation constants, organic alkalinity), estimates of air–sea CO₂ fluxes in estuaries are subject to large uncertainties. The Estuary and Gulf of St. Lawrence (EGSL) at the lower limit of the subarctic region in eastern Canada is the world's largest estuarine system, and is characterized by an exceptional richness in environmental diversity. It is among the world's most intensively studied estuaries, yet there are no published data on its surface-water pCO₂ distribution. To fill this data gap, a comprehensive dataset was compiled from direct and indirect measurements of carbonate system parameters in the surface waters of the EGSL during the spring or summer of 2003–2016. The calculated surface-water pCO₂ ranged from 435 to 765 µatm in the shallow partially mixed upper estuary, 139–578 µatm in the deep stratified lower estuary, and 207–478 µatm along the Laurentian Channel in the Gulf of St. Lawrence. Overall, at the time of sampling, the St. Lawrence Estuary served as a very weak source of CO₂ to the atmosphere, with an area-averaged CO₂ degassing flux of 0.98 to 2.02 mmol C m⁻² d⁻¹ (0.36 to 0.74 mol C m⁻² yr⁻¹). A preliminary analysis revealed that respiration (upper estuary), photosynthesis (lower estuary), and temperature (Gulf of St. Lawrence) controlled the spatial variability in surface-water pCO₂. Whereas we used the dissociation constants of Cai and Wang (1998) to calculate estuarine pCO₂, formulations recommended for best practices in open ocean environments may underestimate pCO₂ at low salinities, while those of Millero (2010) may result in overestimates.