ABSTRACT
The present work provides an analysis of the potential impact of fossil-based Low Carbon Aviation Fuels (LCAF) for the European aviation sector, with a time horizon to 2050. LCAF are a crude-derived alternative to kerosene, offering some Green House Gas (GHG) savings, and have been defined by ICAO as eligible fuels for mitigating the environmental impact of aviation. A methodological framework to evaluate the EU technical potential for LCAF production is developed, based on data on crude utilization for jet fuel production in EU refineries, relevant carbon intensity reduction technologies, market prices, and aviation fuel volumes. Two different baselines for fossil-derived kerosene carbon intensity (CI) are considered: a global figure of 89 gCO2e/MJ and an EU-27-specific one of 93.1 gCO2eq/MJ. Three scenarios considering increasing levels of CI reduction are then defined, taking into account the current and potential commercial availability of some of the most relevant carbon intensity reduction technologies. The analysis demonstrates that, even if LCAF could offer GHG saving opportunities, their possible impact, especially when compared to the ambition level set in the most recent European legislative proposals, is very limited in most of the analysed scenarios, with the exception of the most ambitious ones. At 2030, a non-zero technical potential is projected only in the higher CI reduction scenario, ranging between 1.8% and 14.2% of LCAF market share in the EU-27 (equal to 0.6 to 4.75 Mtoe), depending on the considered Baseline for CI. At 2050, almost all considered scenarios project a larger technical potential, ranging between 6.9% and 22.2% for the global Baseline (2.21 to 7.13 Mtoe), and between 1.8% and 16.2% for the EU-27 Baseline (0.58 to 5.2 Mtoe). LCAF additional costs to current production costs are also discussed, given their relevance in large-scale deployment of these technologies, and are projected to range between 39 and 46.8 USD/toe.
ABSTRACT
We investigate patterns of COVID-19 mortality across 20 Italian regions and their association with mobility, positivity, and socio-demographic, infrastructural and environmental covariates. Notwithstanding limitations in accuracy and resolution of the data available from public sources, we pinpoint significant trends exploiting information in curves and shapes with Functional Data Analysis techniques. These depict two starkly different epidemics; an "exponential" one unfolding in Lombardia and the worst hit areas of the north, and a milder, "flat(tened)" one in the rest of the country-including Veneto, where cases appeared concurrently with Lombardia but aggressive testing was implemented early on. We find that mobility and positivity can predict COVID-19 mortality, also when controlling for relevant covariates. Among the latter, primary care appears to mitigate mortality, and contacts in hospitals, schools and workplaces to aggravate it. The techniques we describe could capture additional and potentially sharper signals if applied to richer data.