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High global uncertainties remain in water‐air CO2, CH4, and N2O fluxes from estuaries due to spatial and temporal variability and the poor predictability of the gas transfer velocity (k600). This is the first study that directly compares k600 of CO2, CH4, and N2O in an estuary with the aim to evaluate the accuracy of using a uniform k600 value for estimating water‐air fluxes. We calculated 155 k600 values from CO2, CH4, and N2O fluxes over spatial (across, along) and temporal (tidal cycle) surveys in the subtropical Maroochy estuary using the floating chamber method. Combined k600 values showed a large range over the entire estuary (0.1–198.6 cm h−1) with slightly lower k600 in the lower compared to the upper estuary. Overall, temporal variability was greater than spatial variability of k600. We found the highest variability of k600 between gas species in the lower estuary, whereas the variability was less distinct in the upper estuary. In the Maroochy estuary, k600CO2 (mean 26.4 ± 37.3 cm h−1) was mostly higher than k600CH4 (mean 10.9 ± 10.6 cm h−1) and k600N2O (mean 9.9 ± 12.3 cm h−1), likely due to chemical and enzymatic enhancements and/or microbial activity in the surface microlayer. We demonstrate that empirical k600 models intended for CO2 may not accurately predict CH4 and N2O fluxes in estuaries. Our tested k600 models predicted the measured fluxes within an uncertainty range of 5%–40% (over or underestimation), but precise flux estimates should be based on in situk600 of all three gases. Plain Language Summary: Greenhouse gas emissions from estuaries are an important component of the coastal ocean carbon cycle. However, carbon dioxide, methane, and nitrous oxide fluxes from estuaries remain uncertain at the global scale, partially because of the gas transfer velocity, a relevant parameter of the flux computation. This study is the first study, to our knowledge, that directly compares gas transfer velocities of the three greenhouse gases with each other and over spatial and temporal gradients in a subtropical estuary in Australia. We find that gas transfer velocities were gas‐specific and differed in upper, mid, and lower estuary regions. The non‐uniformity of the gas transfer velocity in heterogeneous estuaries is likely due to different chemical, physical and biological processes that drive gas transfer of the three gases at the water‐air interface. This is important to consider when estimating estuary fluxes because models for one specific gas may not accurately predict the gas transfer of the other two greenhouse gases. Key Points: k600 of CO2, CH4, and N2O were non‐uniform over spatial and temporal estuary gradients and k600CO2 mostly greater than k600CH4 and k600N2OVariability of k600 between the gas species was greater at the estuary mouth compared to the mid and upper estuary sectionsEmpirical k600CO2 models may not accurately predict CH4 and N2O fluxes because they do not account for gas‐specific non‐diffusive processes [ABSTRACT FROM AUTHOR]

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩, where ⟨.⟩ indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σσU around ⟨U⟩ or, more preferably, a dimensionless coefficient of variation Iu= σσU/⟨U⟩. The proposed correction outperforms previous methodologies that adjusted k when using ⟨U⟩ only. An unexpected outcome was that upon setting Iu2 = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating Iu2 to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO2, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models.

Estuarine CO2 emissions are important components of regional and global carbon budgets, but assessments of this flux are plagued by uncertainties associated with gas transfer velocity (k) parameterization. We combined direct eddy covariance measurements of CO2 flux with waterside pCO2 determinations to generate more reliable k parameterizations for use in small estuaries. When all data were aggregated, k was described well by a linear relationship with wind speed (U10), in a manner consistent with prior open ocean and estuarine k parameterizations. However, k was significantly greater at night and under low wind speed, and nighttime k was best predicted by a parabolic, rather than linear, relationship with U10. We explored the effect of waterside thermal convection but found only a weak correlation between convective scale and k. Hence, while convective forcing may be important at times, it appears that factors besides waterside thermal convection were likely responsible for the bulk of the observed nighttime enhancement in k. Regardless of source, we show that these day‐night differences in k should be accounted for when CO2 emissions are assessed over short time scales or when pCO2 is constant and U10 varies. On the other hand, when temporal variability in pCO2 is large, it exerts greater control over CO2 fluxes than does k parameterization. In these cases, the use of a single k value or a simple linear relationship with U10 is often sufficient. This study provides important guidance for k parameterization in shallow or microtidal estuaries, especially when diel processes are considered. Key Points: When assessed over annual scales, short‐term pCO2 variation, rather than k parameterization, overwhelms uncertainty in calculated CO2 fluxCO2 fluxes generated from bulk transfer equations were significantly greater than those measured by eddy covarianceDay‐night differences in the wind speed versus k relationship can cause parameterized CO2 fluxes to diverge when pCO2 is relatively constant [ABSTRACT FROM AUTHOR]

Reservoirs are considered as important carbon source of the atmosphere, whilst, regional and global reservoir CO 2 quantification is hampered by data limitation and bias in spatial and temporal sampling. By deploying chamber measurements and employing the newly developed model of gas transfer velocity, CO 2 partial pressure ( p CO 2 ) and evasion in the main stem of the Three Gorges Reservoir (TGR) were investigated. The p CO 2 ranged from 429 to 8668 μatm with an average of 2511.6 ± 1721.3 μatm, 6.1-fold higher than the ambient air p CO 2 (mean: 410 μatm). All the samples were net CO 2 sources via water-air interface, displaying pronounced spatial and monthly variability. The CO 2 areal flux averaged 212.5 ± 120.1 mmol/m 2 /d in June, 123.3 ± 78.5 mmol/m 2 /d in July in the lotic TGR main stream, much higher than its lentic system, i.e., 79.6 ± 41.3 mmol/m 2 /d in November, and 76.3 ± 88.1 mmol/m 2 /d in March. Much lower k levels in the lentic reservoir surface resulted in lower CO 2 evasion rates. Furthermore, dam impoundment considerably altered the riverine carbon cycle, as reflected by the changing magnitude of CO 2 efflux and environmental controls of dissolved CO 2 . Precipitation and concurrent soil CO 2 influx exhibited a central role in controlling riverine p CO 2 , and respiration of allochthonous organic carbon was a secondary factor in the TGR lotic system, whilst, both in-stream metabolism and terrestrial inputs played crucial roles in controlling aqueous CO 2 in the TGR lentic system. In comparison, we provided key findings of k model and more reliable CO 2 quantification with a consideration of water level shifts and a complete coverage of spatial sampling. Our higher CO 2 emission (1.47 (1.16–2.13) Tg CO 2 /y) than previous studies called more field measurements to assess the resulting changes in CO 2 flux owing to dam operation and changing environment, and their implications for regional carbon budgets should be warranted. [ABSTRACT FROM AUTHOR]

Wave breaking is known to cause air entrainment and enhancement of the near-surface turbulence. Thus, it intensifies the gas exchange across the air–sea interface. Based on the combination of the vertical distribution of the turbulence in the wave-affected layer and the breaking wave-energy dissipation rate in the wave-breaking layer, we proposed a composite model for the gas transfer velocity in the presence of wave breaking. The gas transfer velocity was calculated as a function of the air frictional velocity, wave age, and whitecap coverage. The model was validated by the dependences on winds and wave ages by field and laboratory measurements. The results supported the hypothesis that the large uncertainties in the traditional gas transfer velocities based on wind speed alone at moderate-to-high wind speeds can be ascribed to the neglect of the wind–wave effect, which is mainly attributed to the whitecap coverage as a function of the wind–sea Reynolds number.

Microalgal technology is one of the most promising technologies to eliminate the anthropogenic CO 2 and to create a benign environment. Carbon dioxide is bubbled into the microalgae reactors during bio sequestration process. Since CO 2 concentration in the atmosphere is very less, mass transfer occur naturally from the reactor to the atmosphere. The possibility of losses to the atmosphere occurs due to the higher flow rate, lower fixation rate of the species and also due to the wind speed available at the particular locations. The objective of the study is to evaluate the CO 2 loss due to the different wind speeds in an open pond reactor. The wind velocities in the range of 2.7 m/s to 10.5 m/s on the percentage loss of carbon dioxide were studied. The results indicate that higher the wind speed, higher the CO 2 loss to the atmosphere. The gas transfer velocity was evaluated at each wind speed. The empirical relation was determined relating the wind speed and gas transfer velocity. The developed correlation was verified satisfactorily for the percentage loss of carbon dioxide in the open air. Based on the wind speed available at any location, the rate of CO 2 loss could be predicted from the correlation. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) fluxes between the ocean and atmosphere (FCO2) are commonly computed from differences between their partial pressures of CO2 (ΔpCO2) and the gas transfer velocity (k). Commonly used wind-based parameterizations for k imply a zero intercept, although in situ field data below 4 m s−1 are scarce. Considering a global average wind speed over the ocean of 6.6 m s−1, a nonzero intercept might have a significant impact on global FCO2. Here, we present a database of 245 in situ measurements of k obtained with the floating chamber technique (Sniffle), 190 of which have wind speeds lower than 4 m s−1. A quadratic parameterization with wind speed and a nonzero intercept resulted in the best fit for k. We further tested FCO2 calculated with a different parameterization with a complementary pCO2 observation-based product. Furthermore, we ran a simulation in a well-tested ocean model of intermediate complexity to test the implications of different gas transfer velocity parameterizations for the natural carbon cycle. The global ocean observation-based analysis suggests that ignoring a nonzero intercept results in an ocean-sink increase of 0.73 Gt C yr−1. This corresponds to a 28% higher uptake of CO2 compared with the flux calculated from a parameterization with a nonzero intercept. The differences in FCO2 were higher in the case of low wind conditions and large ΔpCO2 between the ocean and atmosphere. Such conditions occur frequently in the Tropics.

The Sydney Harbour Estuary is a large drowned river valley adjacent to Sydney, a large urban metropolis on track to become a megacity; estimated to reach a population of 10 million by 2100. Monthly underway surveys of surface water p CO 2 were undertaken along the main channel and tributaries, from January to December 2013. p CO 2 showed substantial spatio-temporal variability in the narrow high residence time upper and mid sections of the estuary, with values reaching a maximum of 5650 μatm in the upper reaches and as low as 173 μatm in the mid estuary section, dominated by respiration and photosynthesis respectively. The large lower estuary displayed less variability in pCO 2 with values ranging from 343 to 544 μatm controlled mainly by tidal pumping and temperature. Air-water CO 2 emissions reached a maximum of 181 mmol C m −2 d −1 during spring in the eutrophic upper estuary. After a summer high rainfall event nutrient-stimulated biological pumping promoted a large uptake of CO 2 transitioning the Sydney Harbour Estuary into a CO 2 sink with a maximum uptake of rate of −10.6 mmol C m −2 d −1 in the mid-section of the estuary. Annually the Sydney Harbour Estuary was heterotrophic and a weak source of CO 2 with an air-water emission rate of 1.2–5 mmol C m −2 d −1 (0.4–1.8 mol C m −2 y −1 ) resulting in a total carbon emission of around 930 tonnes per annum. CO 2 emissions (weighted m 3 s −1 of discharge per km 2 of estuary surface area) from Sydney Harbour were an order of magnitude lower than other temperate large tectonic deltas, lagoons and engineered systems of China, India, Taiwan and Europe but were similar to other natural drowned river valley systems in the USA. Discharge per unit area appears to be a good predictor of CO 2 emissions from estuaries of a similar climate and geomorphic class. [ABSTRACT FROM AUTHOR]

There is the need for further study of whether global estimates of air-sea CO 2 exchange in estuarine systems capture the relevant temporal variability and, as such, the temporal variability of bulk parameterized and directly measured CO 2 fluxes was investigated in the Danish estuary, Roskilde Fjord. The air-sea CO 2 fluxes showed large temporal variability across seasons and between days and that more than 30% of the net CO 2 emission in 2013 was a result of two large fall and winter storms. The diurnal variability of ΔpCO 2 was up to 400 during summer changing the estuary from a source to a sink of CO 2 within the day. Across seasons the system was suggested to change from a sink of atmospheric CO 2 during spring to near neutral during summer and later to a source of atmospheric CO 2 during fall. Results indicated that Roskilde Fjord was an annual low-emission estuary, with an estimated bulk parameterized release of 3.9 ± 8.7 mol CO 2 m −2 y −1 during 2012–2013. It was suggested that the production-respiration balance leading to the low annual emission in Roskilde Fjord, was caused by the shallow depth, long residence time and high water quality in the estuary. In the data analysis the eddy covariance CO 2 flux samples were filtered according to the H 2 O CO 2 cross-sensitivity assessment suggested by Landwehr et al. (2014). This filtering reduced episodes of contradicting directions between measured and bulk parameterized air-sea CO 2 exchanges and changed the net air-sea CO 2 exchange from an uptake to a release. The CO 2 gas transfer velocity was calculated from directly measured CO 2 fluxes and ΔpCO 2 and agreed to previous observations and parameterizations. [ABSTRACT FROM AUTHOR]

Wave breaking is known to cause air entrainment and enhancement of the near-surface turbulence. Thus, it intensifies the gas exchange across the air sea interface. Based on the combination of the vertical distribution of the turbulence in the wave-affected layer and the breaking wave-energy dissipation rate in the wave-breaking layer, we proposed a composite model for the gas transfer velocity in the presence of wave breaking. The gas transfer velocity was calculated as a function of the air frictional velocity, wave age, and whitecap coverage. The model was validated by the dependences on winds and wave ages by field and laboratory measurements. The results supported the hypothesis that the large uncertainties in the traditional gas transfer velocities based on wind speed alone at moderate-to-high wind speeds can be ascribed to the neglect of the wind wave effect, which is mainly attributed to the whitecap coverage as a function of the wind sea Reynolds number. [ABSTRACT FROM AUTHOR]

• Differences in methods in published eddy covariance studies make results difficult to compare. • Including ancillary datasets and their uncertainties will help to clarify study conclusions. • Heterogeneous sea-ice environments should be a major focus for future eddy covariance studies. Sparse in situ measurements and poor understanding of the impact of sea ice on air-sea gas exchange introduce large uncertainties to models of polar oceanic carbon uptake. The eddy covariance technique can be used to produce insightful air-sea gas exchange datasets in the presence of sea ice, but results differ between studies. We present a critical review of historical polar eddy covariance studies and can identify only five that present comparable flux datasets. Assessment of ancillary datasets, including sea-ice coverage and type and air-sea concentration gradient of carbon dioxide, used to interpret flux datasets (with a specific focus on their role in estimating and interpreting sea ice zone gas transfer velocities) identifies that standardised methodologies to characterise the flux footprint would be beneficial. In heterogeneous ice environments both ancillary data uncertainties and controls on gas exchange are notably complex. To address the poor understanding, we highlight how future efforts should focus on the collection of robust gas flux datasets within heterogeneous sea ice regions during key seasonal processes alongside consistent ancillary data with a full characterisation of their associated uncertainties. [ABSTRACT FROM AUTHOR]

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as 〈 U 〉 , where 〈. 〉   indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σ U around 〈 U 〉 or, more preferably, a dimensionless coefficient of variation I u = σ U / 〈 U 〉 . The proposed correction outperforms previous methodologies that adjusted k when using 〈 U 〉 only. An unexpected outcome was that upon setting I u 2 = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating I u 2 to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO2, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models. [ABSTRACT FROM AUTHOR]