Eddy covariance CO2 flux data for supporting local climate change mitigation policies.

Under the Paris Agreement, countries are encouraged to preserve and enhance existing carbon sinks, especially forests, thereby including the LULUCF (Land Use, Land Use Change and Forestry) sector in international climate mitigation targets. In particular, Europe has set the target to reach climate neutrality, i.e. a balance between anthropogenic emissions by sources and removals by sinks, by 2050. A prerequisite to reach these goals is an accurate and credible estimation of both these large fluxes. However, recent works highlighted the uncertainty related to the quantification of the land sector mitigation potential, one of the most challenging emission sectors. Moreover, the definition of climate mitigation policies often occur at the local level, where details on CO₂ removals from forests and other land uses are traditionally lacking. Indeed, local authorities  (e.g. cities and Regions) can be more effective in the transition to a sustainable economy compared to higher level authorities such as Nations.

In this study, we tested a data-driven method based on eddy covariance (EC) data to quantify the current LULUCF role to the regional carbon sink of the Aosta Valley Region (Italy), by the integration of different approaches. Our model is based on eddy covariance measurements of CO₂ fluxes, MODIS NDVI (250m), daily gridded meteorological variables at 100m spatial resolution, and a land cover map at 250m spatial resolution. A Random Forest model was used to up-scale the point eddy covariance data to the Regional level, by testing different sets of drivers (air temperature, VPD, Snow (presence/absence), NDVI, solar radiation,...). Our model was then compared to independent data derived from the National Forest Inventory (NFI), and a process-based model. Preliminary results show that forests and other ecosystems of the Region remove nearly 70% of the total anthropogenic emissions in this area. The discrepancies between the different methods will be discussed by exploring the different advantages and flaws and the spatio-temporal variability of the different approaches. Such an assessment of the local carbon budget and its uncertainties will provide a solid base for Climate-smart management of the territory and thus for reaching the carbon neutrality targets.