Lawrence Berkeley National Laboratory

The eddy covariance technique (EC) is used at hundreds of field sites worldwide to measure trace gas exchange between the surface and the atmosphere. Data quality and correction methods for EC have been studied empirically and theoretically for many years. The recent development of new gas analyzers has led to an increase in technological options for users. Open-path (no inlet tube) and closed-path (long inlet tube) sensors have been used for a long time, whereas enclosed-path (short inlet tube) sensors are relatively new. We tested the comparability of fluxes calculated from five different gas analyzers including two open-path (LI-7500 A from LI-COR, IRGASON from Campbell), two enclosed-path (CPEC200 from Campbell, LI-7200 from LI-COR), and one closed-path (2311-f from Picarro) analyzers, which were all located on a single tower at an irrigated alfalfa field in Davis, CA. To effectively compare sensors with different tube characteristics we used three different spectral correction methods. We found that all sensors, regardless of type, can be used to measure fluxes if appropriate corrections are applied and quality control measures are taken. However, the comparability strongly depended on the gas (CO2 or H2O) and the correction method. Average differences were below 4% for CO2 fluxes using any spectral correction method, but for H2O average differences were between 4% and 13% for the different methods. The magnitude of corrections also varied strongly, especially for water vapor fluxes. This study does not identify the best sensor, but rather weighs the benefits and difficulties of each sensor and sensor type. Our findings show that enclosed and closed-path gas analyzers that measure water vapor with inlet tubes experience large high frequency attenuation and should be corrected with empirical correction methods. This information presented here about different the diverse sensors be considered by investigators when choosing a sensor for a site or when analyzing EC measurements from multiple sites.