Transport is the sector with the highest reliance on oil products, and its decarbonization requires a combination of solutions. Planning and deploying effective actions need a precise knowledge of the mobility demand of each area and its expected future evolution. This research work builds on the available data at the NUTS3 level in Italy to provide energy consumption and emissions intensity indicators at different locations to highlight the variability across territories and the range of the indicators that is linked to several factors. The output datasets of the analysis provide the building bricks for the construction of energy-transport models with high resolution at regional scale, enabling the investigation of decarbonisation solutions tailored to local characteristics.

Energy Consumption and Performance of Transport Modes: an Analysis at the Provincial Level / Noussan, M.; Laveneziana, L.; Prussi, M.; Chiaramonti, D.. - ELETTRONICO. - (2024). (Intervento presentato al convegno 19th SDEWES Conference on Sustainable Development of Energy, Water and Environment Systems tenutosi a Roma nel 8-12 September 2024).

Energy Consumption and Performance of Transport Modes: an Analysis at the Provincial Level

M. Noussan;L. Laveneziana;M. Prussi;D. Chiaramonti
2024

Abstract

Transport is the sector with the highest reliance on oil products, and its decarbonization requires a combination of solutions. Planning and deploying effective actions need a precise knowledge of the mobility demand of each area and its expected future evolution. This research work builds on the available data at the NUTS3 level in Italy to provide energy consumption and emissions intensity indicators at different locations to highlight the variability across territories and the range of the indicators that is linked to several factors. The output datasets of the analysis provide the building bricks for the construction of energy-transport models with high resolution at regional scale, enabling the investigation of decarbonisation solutions tailored to local characteristics.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2992404
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