Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N ₂ O

Abstract Fluxes of the powerful greenhouse gas nitrous oxide (N 2 O) are mainly quantified using manually operated or automatic non‐steady‐state chambers. With both systems, fluxes are calculated as the change in N 2 O concentration over time using linear or non‐linear regression, but the type of regression selected can have a strong influence on the N 2 O flux magnitude. The HMR package, a regression‐based implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters were recently introduced which allow for pre‐filtering based on sample variance ( pfvar and pfalpha) , and for constraining the curvilinearity of concentration‐time series( SatPct and SatTimeMin) . Currently, there are no guidelines on how to choose the best parameters for specific user conditions. Here we address this knowledge gap using datasets from manual and automatic chambers, and sensitivity analyses. We found that the effect of parameter settings on the cumulative fluxes was greater for manual chamber data compared to the automatic chamber data, with ranges of up to 67.3% and 1.5%, respectively. The parameter pfvar was identified as highly sensitive for both manual and automatic chambers; it is, therefore, critical to select a threshold for when to allow for non‐linear flux calculation that accurately represents the given measurement precision. This can be estimated from the variance of N 2 O measurements at ambient concentration levels. The parameter SatTimeMin was critical for manual chamber data where the curvature is much less constrained due to the lower number of observations. The parameter pfalpha was the least sensitive and can be set at a p ‐value equal to 0.05 following common statistical practice. Parameter values depend on the expected flux characteristics with a given chamber design and are currently best selected based on visual inspection of the data. This study identifies where and how specific care should be taken for the selection of parameters in the HMR package, which may contribute to standardizing the methodologies used worldwide for N 2 O flux calculations, supporting initiatives in which data from many studies need to be combined. Highlights The HMR package, an implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters in the updated HMR package constrains the use of nonlinear flux calculation and inclusion of outliers. The new parameters affect the cumulative emissions of N 2 O obtained with manual and automated chambers differently. We found that the choice of parameter values led to differences in cumulative N 2 O emissions of up to 67.3% This study identifies where and how specific care should be taken for the selection of parameters.