AnaEE Science Conference 2026

When we measure matters: High-frequency monitoring of agricultural GHGs

Not scheduled

15m

Palais de l'Europe

Poster Session 4: Experimental Approaches to Global Change Ecology Session 4: Experimental Approaches to Global Change Ecology

Speaker

Hans Frederik Engvej Hansen (Global Wetland Center, Department of Geosciences and Natural Resource Management, University of Copenhagen)

Description

Accurate quantification of greenhouse gas (GHG) emissions is essential for evaluating the climate impacts of agricultural systems. However, methane (CH₄) and nitrous oxide (N₂O) fluxes often exhibit substantial temporal variability that may not be captured by conventional manual chamber campaigns, which are typically conducted during daytime hours and at relatively low sampling frequencies. This study aimed to evaluate how measurement timing and sampling frequency influence estimated CH₄ and N₂O emissions from an agricultural field.

The study was conducted in a rice-based cropping system in the Red River Delta, Vietnam. Greenhouse gas fluxes were measured continuously for one year using automated chambers designed for rice paddies, generating up to 16 measurements per chamber per day. Measurements covered multiple crop and fallow periods. Fluxes were calculated using the goFlux package in R. The high-frequency dataset was used to investigate diurnal and day-to-day variability and to assess potential biases associated with conventional daytime sampling. In addition, low-frequency sampling campaigns (every 6-8 days) were simulated to evaluate their influence on cumulative emission estimates.

Both CH₄ and N₂O emissions exhibited pronounced diurnal and seasonal variability. Peak emissions frequently occurred outside conventional daytime sampling windows, indicating that commonly used manual chamber schedules may not capture representative daily fluxes. Depending on season and gas, daytime-only sampling resulted in both under- and overestimation of emissions. Simulated low-frequency sampling produced highly variable cumulative emission estimates, with individual sampling campaigns differing substantially from estimates based on the complete dataset. High-frequency measurements more effectively captured episodic events, diurnal dynamics, and cumulative annual emissions, thereby reducing uncertainty in annual GHG budgets.

Keywords: Greenhouse gases; Automated chambers; Sampling frequency; Methane; Nitrous oxide