Calculating CO2 and H2O eddy covariance fluxes from an enclosed gas analyzer using an instantaneous mixing ratio

Eddy covariance flux research has relied on open- or closed-path gas analyzers for producing estimates of net ecosystem exchange of carbon dioxide (CO2) and water vapor (H2O). The two instruments have had different challenges that have led to development of an enclosed design that is intended to maximize strengths and minimize weaknesses of both traditional designs. Similar to the closed-path analyzer, the enclosed design leads to minimal data loss during precipitation events and icing, and it does not have surface heating issues. Similar to the open-path design, the enclosed design has good frequency response due to small flux attenuation loss in the short intake tube, does not need frequent calibration, has minimal maintenance requirements, and can be used in a very low power configuration. Another important feature of such a design is the ability to output instantaneous mixing ratio, or dry mole fraction, so that instantaneous thermal and pressure-related expansion and contraction, and water dilution of the sampled air have been accounted for. Thus, no density corrections should be required to compute fluxes during postprocessing. Calculations of CO2 and H2O fluxes via instantaneous mixing ratio from the new enclosed CO2/H2O gas analyzer were tested in nine field experiments during 20092010 in a wide range of ecosystems and setups. Fluxes computed via a mixing ratio output from the instrument without applying density corrections were compared to those computed the traditional way using density corrections. The results suggest that with proper temperature, water vapor, and pressure measurements in the cell, gas fluxes can be computed confidently from raw covariance of mixing ratio and vertical wind speed, multiplied by a frequency response correction. This has important implications for future flux measurements, because avoiding hourly density corrections could have the advantages of increasing flux measurement quality and temporal resolution, reducing the magnitude of minimum detectable flux, unifying data processing steps, and assuring better intercomparison between different sites and networks.