Abstract

Large uncertainties remain in global estuarine CO2 and CH4 emissions estimates due to spatial heterogeneity, differences in methodologies and insufficient data at key locations. This study utilised novel techniques to integrate high-resolution temporal measurements of dissolved CO2 and CH4 and gas transfer velocity, within an urbanised subtropical estuary (Coffs Creek, Australia). An intensive four-station 25hr moving time series approach accounted for diurnal, tidal and spatial trends along an estuarine salinity gradient. Using 185 floating chamber measurements, results revealed major differences in emission rates over short distances. Average CO2 emission rates ranged from 16.7 to 84.4 mmol m−2 day−1 from lower to upper estuary respectively (averaged 49.0 mmol m−2 day−1). The CH4 emissions ranged from 38.8 to 193.4 μmol m−2 day−1 (averaged 115.0 μmol m−2 day−1), equating to 2.4% of the average CO2 emissions, when converted to global warming potential CO2 equivalent (over 100 years). Conservative mixing plots revealed a mid-estuary source of groundwater and porewater exchange that corresponded with a source of pCO2 and pCH4 in the mangrove lined portion of the estuary. Between the mouth and upper-estuary, a 230-fold change in gas transfer velocity (k600) (0.1–25.9 cm hr−1), 130-fold change in CO2 fluxes (1.6–202.6 mmol m−2 day−1) and 260-fold change of CH4 fluxes were observed (2.6–671.1 μmol m−2 day−1). Current velocity was the most important driver of k600 in the lower estuary (r2 = 0.37, p < 0.001) and a significant driver across the whole estuary (r2 = 0.77, p < 0.001). A comparison of measured emissions to existing empirical k models indicated empirical models were less effective at characterising emissions within different ecotypes because of changing physical drivers along the estuary. The kCO2 chemical enhancement may be significant, especially in low k settings such as upper estuaries. This study highlights the importance of characterizing distinct estuarine zones and accounting for spatio-temporal variability to reduce uncertainties of emissions estimates.

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