Comment on bg-2021-166 Article Swipe
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·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5194/bg-2021-166-rc1
Surface ocean CO2 measurements are used to compute the oceanic air–sea CO2 flux. The CO2 flux component from rivers and estuaries is uncertain. Estuarine and coastal water carbon dioxide (CO2) observations are relatively few compared to observations in the open ocean. The contribution of these regions to the global air–sea CO2 flux remains uncertain due to systematic under-sampling. Existing high-quality CO2 instrumentation predominantly utilise showerhead and percolating style equilibrators optimised for open ocean observations. The intervals between measurements made with such instrumentation make it difficult to resolve the fine-scale spatial variability of surface water CO2 at timescales relevant to the high frequency variability in estuarine and coastal environments. Here we present a novel dataset with unprecedented frequency and spatial resolution transects made at the Western Channel Observatory in the south west of the UK from June to September 2016, using a fast response seawater CO2 system. Novel observations were made along the estuarine–coastal continuum at different stages of the tide and reveal distinct spatial patterns in the surface water CO2 fugacity (fCO2) at different stages of the tidal cycle. Changes in salinity and fCO2 were closely correlated at all stages of the tidal cycle and suggest that the mixing of oceanic and riverine end members determines the variations in fCO2. The observations demonstrate the complex dynamics determining spatial and temporal patterns of salinity and fCO2 in the region. Spatial variations in observed surface salinity were used to validate the output of a regional high resolution hydrodynamic model. The model enables a novel estimate of the air–sea CO2 flux in the estuarine–coastal zone. Air–sea CO2 flux variability in the estuarine–coastal boundary region is dominated by the state of the tide because of strong CO2 outgassing from the river plume. The observations and model output demonstrate that undersampling the complex tidal and mixing processes characteristic of estuarine and coastal environment bias quantification of air-sea CO2 fluxes in coastal waters. The results provide a mechanism to support critical national and regional policy implementation by reducing uncertainty in carbon budgets.
Related Topics
- Type
- peer-review
- Language
- en
- Landing Page
- https://doi.org/10.5194/bg-2021-166-rc1
- https://bg.copernicus.org/preprints/bg-2021-166/bg-2021-166.pdf
- OA Status
- gold
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4210555585
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4210555585Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5194/bg-2021-166-rc1Digital Object Identifier
- Title
-
Comment on bg-2021-166Work title
- Type
-
peer-reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-08-31Full publication date if available
- Authors
-
Richard Sims, Michael Bedington, Ute Schuster, Andrew Watson, Vassilis Kitidis, Ricardo Torres, Helen S. Findlay, James Fishwick, Ian Brown, Thomas G. BellList of authors in order
- Landing page
-
https://doi.org/10.5194/bg-2021-166-rc1Publisher landing page
- PDF URL
-
https://bg.copernicus.org/preprints/bg-2021-166/bg-2021-166.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://bg.copernicus.org/preprints/bg-2021-166/bg-2021-166.pdfDirect OA link when available
- Concepts
-
Transect, Oceanography, Estuary, Salinity, Environmental science, Flux (metallurgy), Spatial variability, Seawater, Sampling (signal processing), Water column, Surface water, Geology, Climatology, Environmental engineering, Filter (signal processing), Materials science, Statistics, Computer science, Metallurgy, Computer vision, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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