A simple calculation algorithm to separate high-resolution CH<sub>4</sub> flux measurements into ebullition and diffusion-derived components

Abstract

Abstract. Processes driving the production, transformation and transport of methane (CH4) in wetland ecosystems are highly complex. We present a simple calculation algorithm to separate open-water CH4 fluxes measured with automatic chambers into diffusion- and ebullition-derived components. This helps to reveal underlying dynamics, to identify potential environmental drivers, and thus, calculate reliable CH4 emission estimates. The flux separation is based on identification of ebullition-related sudden concentration changes during single measurements. Therefore, a variable ebullition filter is applied, using the lower and upper quartile and the interquartile range (IQR). Automation of data processing is achieved by using an established R-script, adjusted for the purpose of CH4 flux calculation. The algorithm was tested using flux measurement data (July to September 2013) from a former fen grassland site, converted into a shallow lake as a result of rewetting. Ebullition and diffusion contributed equally (46 % and 55 %) to total CH4 emissions, which is comparable to ratios given in literature. Moreover, the separation algorithm revealed a concealed shift in the diurnal trend of diffusive fluxes throughout the measurement period. The water temperature gradient was identified as one of the major drivers of diffusive CH4 emissions, whereas no significant driver was found in case of erratic CH4 ebullition events.

Stable Carbon Isotope Studies of CH4 Dynamics Via Water and Plant Pathways in a Tropical Thai Paddy: Insights Into Diel CH4 Transportation

“…There was usually only a gradual increase in CH 4 concentration during a chamber closure period due to diffusion (δ 13 CH 4_emit > −53.6‰), with almost all CH 4 flux rates of less than 5 mg m −2 hr −1 , significantly lower than bubble ebullition (Figure 5a, Welch's t test, p < 0.001). The upper value of the diffusive CH 4 flux rate (5 mg m −2 hr −1 ) agrees with the mean diffusive CH 4 flux rate at the water‐atmosphere interface in a flooded fen site (Hoffmann et al, 2017), so the value was considered as the upper threshold diffusive CH 4 flux rate. Furthermore, in another flooded wetland study (Poindexter et al, 2016), the maximum diffusive CH 4 flux rate by hydrodynamic transport was 200 nmol m −2 s −1 (=11.52 mg m −2 hr −1 ), which covers the maximum outlier diffusive CH 4 flux rates in our study (Figure 5a).…”

A simple calculation algorithm to separate high-resolution CH&lt;sub&gt;4&lt;/sub&gt; flux measurements into ebullition- and diffusion-derived components

“…The presented simple calculation algorithm, a test data set and manual, as well as all raw data sets of automatic chamber flux measurements shown in this study, are available at https: //zenodo.org (Hoffmann and Jurisch, 2016;Hoffmann et al, 2017).…”

A Modeling Approach for Addressing Sensitivity and Uncertainty of Estuarine Greenhouse Gas (CO2 and CH4) Dynamics

“…This method was developed for parameter optimization, which is not ideal for testing the discrete k 600 options, and future studies may seek to include capability to consider different algorithms and competing model structural assumptions in the uncertainty analysis. Water‐air transfer rates are further complicated for CH 4 , as its relatively low solubility means that nondiffusive ebullition fluxes can contribute a substantial fraction to CH 4 emissions in some aquatic environments (e.g., Baron et al., 2022; Hoffmann et al., 2017; Schmid et al., 2017). However, our understanding of ebullition's drivers remains incomplete and empirical data on its spatial and temporal variability within estuaries is also too limited (Chen et al., 2017) to meaningfully incorporate it here.…”