Atmospheric Methane and Carbon Dioxide Background Levels Computed by Modeling at Three WMO/GAW Stations in the Mediterranean Basin

Due to the increasing concern over climate change and its environmental impacts, effective greenhouse gases (GHG) control strategies are of pivotal importance. The use of models such as STILT (Stochastic Time Inverted Lagrangian Transport), statistical techniques, and experimental data analysis provide valuable tools to quantify emissions and identify GHG tendencies. The Mediterranean basin is considered a global hotspot for air-quality and climate change: here, we combine experimental datasets of atmospheric methane (CH4) and carbon dioxide (CO2) with atmospheric transport models to present an atmospherically-based framework for monitoring GHG emissions. We applied methodologies, i.e., the Smoothed Minima (SM) and STILT, to extract background concentration data from the time series of atmospheric gases and identify measurements deemed representative of atmospheric background (GRD) levels. At the Lamezia Terme (Global Atmosphere Watch, GAW code: LMT), Capo Granitola (GAW code: CGR), and Lampedusa (GAW code: LMP) observation sites, GHG measurements were performed with specific calibration routines carried out using primary standards of calibration from the National Oceanic and Atmospheric Administration – Global Monitoring Laboratory (NOAA–GML), with secondary standards used to evaluate possible drifts and calibration factors stability. The first two are coastal stations and the third is an island station. At these sites, atmospheric CH4 and CO2 mole fractions can be evaluated at local and continental scales, in locations with specific Mediterranean climatic characteristics. This paper presents the variability of CH4 and CO2 in the central Mediterranean basin by analyzing hourly GHG concentrations over a 9-year period (2015-2023) for LMT, a 8-year period (2015-2022) for CGR, and a 19-year period (2006-2024) for CO2 and 5-year period (2020-2024) for CH4 at LMP. STILT provides 3-hourly results for methane and carbon dioxide concentrations that correlate well with surface measurements at LMT, CGR, and LMP. These analyses are aimed at relevant long-term datasets of GHG over southern Italy. This work would provide a useful contribution to comparing the observed concentrations of gases measured at three sites in the central Mediterranean with those predicted by models such as STILT.