Study of the daily and seasonal atmospheric CH₄ mixing ratio variability in a rural Spanish region using 222Rn tracer

Atmospheric concentrations of the two main greenhouse gases (GHGs), carbon dioxide (CO₂) and methane (CH₄), are continuously measured since November 2012 at the Spanish rural station of Gredos (GIC3), within the climate network ClimaDat, together with atmospheric radon (²²²Rn) tracer and meteorological parameters. The atmospheric variability of CH₄ concentrations measured from 2013 to 2015 at GIC3 has been analyzed in this study. It is interpreted in relation to the variability of measured 222Rn concentrations, modelled ²²²Rn fluxes and modelled heights of the planetary boundary layer (PBLH) in the same period. In addition, nocturnal fluxes of CH4 were estimated using two methods: the Radon Tracer Method (RTM) and one based on the EDGARv4.2 bottom-up emission inventory. Both previous methods have been applied using the same footprints, calculated with the atmospheric transport model FLEXPARTv6.2. Results show that daily and seasonal changes in atmospheric concentrations of ²²²Rn (and the corresponding fluxes) can help to understand the atmospheric CH₄ variability. On daily basis, the variation in the PBLH mainly drives changes in ²²²Rn and CH₄ concentrations while, on monthly basis, their atmospheric variability seems to depend on changes in their emissions. The median value of RTM based methane fluxes (FR_CH₄) is 0.17 mg CH₄ m−2 h−1 with an absolute deviation of 0.08 mg CH₄ m⁻² h⁻¹. Median methane fluxes based on bottom-up inventory (FE_CH₄) is of 0.32 mg CHv m⁻² h⁻¹ with an absolute deviation of 0.06 mg CH₄ m⁻² h⁻¹. Monthly FR_CH₄ flux shows a seasonality which is not observed in the monthly FE_CH₄ flux. During January-May FR_CH₄ fluxes present a median value of 0.08 mg CH₄ m⁻² h⁻¹ with an absolute deviation of 0.05 mg CH₄ m⁻² h⁻¹ and a median value of 0.19 mg CH₄ m⁻² h⁻¹ with an absolute deviation of 0.06 mg CH₄ m⁻² h⁻¹ during June-December. This seasonal doubling of the median methane fluxes calculated by RTM at the GIC3 area seems to be mainly related to the alternate presence of transhumant livestock in the GIC3 area. The results obtained in this study highlight the benefit of applying independent RTM to improve the seasonality of the emission factors from bottom-up inventories.