Quantifying temporal dynamics of greenhouse gas emissions in lake mesocosms: Deployment of a low-cost measurement system

Abstract

Greenhouse gas (GHG) emissions from freshwater ecosystems contribute significantly to global carbon budgets, yet they remain poorly constrained due to limited high-frequency measurements. We tested a low-cost, high-frequency GHG measurement system in a long-term mesocosm experiment in Lemming, Denmark, over a 7-month period, focusing on CO₂ and CH₄ fluxes. We deployed a methodology for calculating CH₄ diffusive fluxes using high-frequency sensor data and tested the effects of sampling intervals on emission upscaling. Our findings reveal substantial temporal variability in GHG emissions, particularly for CH₄, with ebullitive fluxes dominating and exhibiting large variation. Pronounced diurnal fluctuations were also observed for CO₂ and diffusive CH₄ fluxes, whereas ebullitive CH₄ emissions showed no significant diurnal pattern. Relying solely on daytime measurements led to a significant overestimation of overall CO₂ fluxes and CH₄ diffusive fluxes. Resampling data at lower frequency showed that reduced sampling frequency leads to an underestimation of total emissions, especially for CH₄ ebullitive fluxes. Increasing the sampling interval from daily to monthly markedly increased uncertainty, while weekly sampling better captured overall GHG flux patterns and reduced the uncertainty compared with more infrequent sampling. These results underscore the value of high-frequency GHG measurements in capturing both diurnal and seasonal variations, improving the accuracy of flux estimates, and reducing uncertainties in upscaling emission. We emphasize the need to optimize sampling intervals and incorporate diurnal cycle measurements to enhance the accuracy and reliability of freshwater GHG assessments.