Evaluation of Greenhouse Gas-Flux-Determination Models and Calculation in Southeast Arkansas Cotton Production
2025
Cassandra Seuferling | Kristofor Brye | Diego Della Lunga | Jonathan Brye | Michael Daniels | Lisa Wood | Kelsey Greub
Greenhouse gas (GHG) emissions evaluations from agroecosystems are critical, particularly as technology improves. Consistent GHG measurement methods are essential to the evaluation of GHG emissions. The objective of the study was to evaluate potential differences in gas-flux-determination (GFD) options and carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes and growing-season-long emissions estimates from furrow-irrigated cotton (Gossypium hirsutum) in southeast Arkansas. Four GFD methods were evaluated [i.e., linear (L) or exponential (E) regression models, with negative fluxes (WNF) included in the dataset or replacing negative fluxes (RNF)] over the 2024 growing season using a LI-COR field-portable chamber and gas analyzers. Exponential regression models were influenced by abnormal CO2 and N2O gas concentration data points, indicating the use of caution with E models. Season-long CH4 emissions differed (p <: 0.05) between the WNF (&minus:0.51 kg ha&minus:1 season&minus:1 for L and&minus:0.54 kg ha&minus:1 season&minus:1 for E) and RNF (0.01 kg ha&minus:1 season&minus:1 for L and E) GFD methods, concluding that RNF options over-estimate CH4 emissions. Gas concentration measurements following chamber closure should remain under 300 s, with one concentration measurement obtained per second. The choice of GFD method needs careful consideration to result in accurate GHG fluxes and season-long emission estimates.
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