Influence of wildfire emissions to carbon dioxide (CO2) observed at the Mt. Cimone station (Italy, 2165 m asl): A multi-year investigation

Abstract

This work aimed at investigating on a multi-year framework (2015–2021) the contributions of wildfire emissions to atmospheric CO2 observed at the ICOS atmospheric class-2 station Mt. Cimone (CMN, 2165 m a.s.l. - Italy). Based on the analysis of a case study occurred in March 2020, a methodology providing indications about the possible presence of wildfire plumes from different European source regions was implemented. The methodology used observed CO at CMN, active fire detection by MODIS and air mass back-trajectories. An alternative detection method based on the use of a reanalysis dataset (CAMS) providing information about the amount of PM10 tagged to wildfires was also used.The results suggested that CMN could be affected by wildfire plumes for a fraction of time ranging from 1% to 10% (as a function of the adopted methodology setting). Over the studied period, we found a potentially important contribution of plumes from eastern Europe during October–April, while during May–September there was a prevalence from the Mediterranean sectors.Looking at the possible impact of these events to the observed CO2, we detected a notable increase of CO2 residuals with respect to periods not affected by fire perturbations during October–April (from +1.8 to +3.9 ppm, on average). We did not find evident impacts during the summer months, possibly due to a contribution by biospheric uptake during air mass transport to CMN (at least for a fraction of selected events).We discussed the sensitivity of results as a function of the selection methodology settings, suggesting that the strictest set-up based on the detection of large CO excesses could trace “major” events. A medium level of agreement was found when comparing the results of our selection methodology with CAMS reanalysis (fraction of PM10 emitted by wildfires).Even if it is still preliminary, our study indicated that the observations from CMN can represent, if supported by adequate diagnostic tools, a powerful dataset to evaluate the impact of wildfires to the atmospheric CO2 variability.