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A platform for research: civil engineering, architecture and urbanism
Quantification of Non-linearities in the Consequential Life Cycle Assessment of the Use Phase of Battery Electric Vehicles
The diffusion of Battery Electric Vehicles (BEVs) is projected to influence the electricity grid operation, potentially offering opportunities for load-shifting policies aimed at higher integration of renewable energy technologies in the electricity system. Moreover, the examined literature emphasizes electricity as a relevant driver of BEVs Life Cycle Assessment (LCA) results. To evaluate LCA impacts associated to future BEVs diffusion scenarios in Italy, we adopt the Consequential Life Cycle Assessment (CLCA) methodology. LCA conventionally assumes a proportional relation between environmental impact indicators and the functional unit. However, such relation may not be representative if the electricity system is significantly affected by the large-scale diffusion of BEVs. Our study couples the conventional CLCA methodology with the EnergyPLAN model through three different approaches, which progressively include BEV-specific dynamics, to capture correlations between additional BEVs fleets and the electricity grid operation, that affectthe mix of electricity consumed in the use phase by BEVs, in Italy in 2030. Here we show that if renewables capacity is not additionally installed in response to additional BEVs electricity demand, the marginal Climate change total indicator of BEVs may increase up to ~40%, with respect to a business-as-usual scenario. Moreover, we quantitatively support the literature indications on how to properly estimate BEVs LCA impacts. Indeed, we weight electricity LCA impacts on hourly BEV charge profiles, finding that this approach best captures BEVs interdependence with the electricity system. At low BEVs diffusion, this approach clearly shows the potential BEVs capability to increase exploitation of renewable energy, whereas at high BEVs diffusion, it fully highlights potential responses of fossil fuel power plants to additional electricity demand. Due to these dynamics, we find that linearly scaling the business-as-usual scenario results would lead to an underestimation of 12.45 Mton ...
Quantification of Non-linearities in the Consequential Life Cycle Assessment of the Use Phase of Battery Electric Vehicles
The diffusion of Battery Electric Vehicles (BEVs) is projected to influence the electricity grid operation, potentially offering opportunities for load-shifting policies aimed at higher integration of renewable energy technologies in the electricity system. Moreover, the examined literature emphasizes electricity as a relevant driver of BEVs Life Cycle Assessment (LCA) results. To evaluate LCA impacts associated to future BEVs diffusion scenarios in Italy, we adopt the Consequential Life Cycle Assessment (CLCA) methodology. LCA conventionally assumes a proportional relation between environmental impact indicators and the functional unit. However, such relation may not be representative if the electricity system is significantly affected by the large-scale diffusion of BEVs. Our study couples the conventional CLCA methodology with the EnergyPLAN model through three different approaches, which progressively include BEV-specific dynamics, to capture correlations between additional BEVs fleets and the electricity grid operation, that affectthe mix of electricity consumed in the use phase by BEVs, in Italy in 2030. Here we show that if renewables capacity is not additionally installed in response to additional BEVs electricity demand, the marginal Climate change total indicator of BEVs may increase up to ~40%, with respect to a business-as-usual scenario. Moreover, we quantitatively support the literature indications on how to properly estimate BEVs LCA impacts. Indeed, we weight electricity LCA impacts on hourly BEV charge profiles, finding that this approach best captures BEVs interdependence with the electricity system. At low BEVs diffusion, this approach clearly shows the potential BEVs capability to increase exploitation of renewable energy, whereas at high BEVs diffusion, it fully highlights potential responses of fossil fuel power plants to additional electricity demand. Due to these dynamics, we find that linearly scaling the business-as-usual scenario results would lead to an underestimation of 12.45 Mton ...
Quantification of Non-linearities in the Consequential Life Cycle Assessment of the Use Phase of Battery Electric Vehicles
Rovelli, Davide (author) / Cornago, Simone (author) / Scaglia, Pietro (author) / Brondi, Carlo (author) / Low, Jonathan Sze Choong (author) / Ramakrishna, Seeram (author) / Dotelli, Giovanni (author) / Rovelli, Davide / Cornago, Simone / Scaglia, Pietro
2021-01-01
Article (Journal)
Electronic Resource
English
DDC:
690
Consequential environmental life cycle assessment of a farm-scale biogas plant
| Online Contents | 2016