Methodology for selecting near-surface CH4, CO, and CO2 observations reflecting atmospheric background conditions at the WMO/GAW station in Lamezia Terme, Italy

Abstract

Since 2015, the permanent World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) station of Lamezia Terme (LMT) in Calabria, Southern Italy, has been performing continuous measurements of atmospheric greenhouse gases (GHGs). As a coastal monitoring station, LMT allowed continuous data gathering of carbon dioxide (CO₂), carbon monoxide (CO) and methane (CH₄) mole fractions in a region characterized by a Mediterranean climate. This work aims to test the adoption of three different methods in the selection of observations representative of the atmospheric background conditions at LMT. In particular, we applied the Background Data Selection (BaDS) method, the smoothed minima baseflow separation method (SM), and the new “Wind” method. All the three selection methods appeared to be effective in retaining the background CH₄, CO, and CO₂ data. Wind, based on the analysis of the local wind regime, selected the lowest number of data. For all the gases considered, the monthly mean values obtained after the implementation of BaDS (SM) were the highest (lowest). Taking into account the complete datasets over the 2015–2023 period, Mann-Kendall and Sen's slope showed annual and seasonal increasing tendencies for CH₄ and CO₂ with significance levels of α = 0.05 and α = 0.001, respectively. For CO, a decreasing tendency was only observed for the winter season level of α = 0.05. The application of the three selection methods resulted in changes in the calculated annual and seasonal growth rates and non-negligible deviations were also found for the average annual growth rates calculated for the three background datasets. This indicates that growth rate calculations are sensitive to the choice of background selection methods, and we recommend that multiple selection methods could be applied to resolve the associated uncertainties.