A5086933378- Environmental Impact and Sustainability
- Global Energy and Sustainability Research
- Hybrid Renewable Energy Systems
- Smart Grid Energy Management
- Energy and Environment Impacts
- Extraction and Separation Processes
- Microgrid Control and Optimization
- Integrated Energy Systems Optimization
- Advanced Battery Technologies Research
- Global Energy Security and Policy
- Electric Vehicles and Infrastructure
- Conferences and Exhibitions Management
- Machine Learning in Materials Science
- Advanced Control Systems Optimization
- Gaussian Processes and Bayesian Inference
- Wind and Air Flow Studies
- Market Dynamics and Volatility
- Air Traffic Management and Optimization
- Safety Systems Engineering in Autonomy
- Agricultural risk and resilience
- Climate Change Policy and Economics
- Russia and Soviet political economy
- Housing Market and Economics
- Nuclear reactor physics and engineering
- Metal Extraction and Bioleaching
Politecnico di Milano
2020-2024
Fondazione Umberto Di Mario
2023
Fondazione Politecnico di Milano
2022-2023
Russia's invasion of Ukraine fuelled an energy crisis, which considerably impacted Europe given its heavy reliance on Russian natural gas imports. This study uses ensemble four global integrated assessment models, are further soft-linked to two sectoral and explores the synergies trade-offs among three approaches living without in Europe: (a) replacing with other imports, (b) boosting domestic production, (c) reducing demand accelerating efficiency. We find that substituting from trade...
The energy transition process calls for striving interventions towards low-carbon technologies. While their deployment is expected to drive down greenhouse gases emissions, it bring along intense critical materials exploitation. This article presents a quantitative framework assess the impact of pathways in terms raw extraction, coupling Input-Output models with modelling methodologies, defined as Dynamic Extraction and Recycling (DYNERIO). analytically formalized tested through conceptual...
We present the results of "Fast Calorimeter Simulation Challenge 2022" - CaloChallenge. study state-of-the-art generative models on four calorimeter shower datasets increasing dimensionality, ranging from a few hundred voxels to tens thousand voxels. The 31 individual submissions span wide range current popular architectures, including Variational AutoEncoders (VAEs), Generative Adversarial Networks (GANs), Normalizing Flows, Diffusion models, and based Conditional Flow Matching. compare all...
The paper explores the multifaceted risks posed by climate change to airport infrastructures and strategic planning required mitigate these risks. Climate change, driven greenhouse gas (GHG) emissions, leads increased global temperatures extreme weather events, which significantly impact critical infrastructure systems, including airports highlights importance of addressing stress on ensure long-term sustainability. Airports are particularly vulnerable weather-related disruptions, such as...
Abstract As a key material for manufacturing clean energy technologies, steel is crucial transition, but its production causes 2.6 Gton of CO 2 emissions at global level each year. In 2020 the European Union (EU) set net-zero target by 2050, fostering innovation in industry to reduce environmental impact. However, scenario-oriented and technologically comprehensive analysis assessing prospected market implications decarbonisation strategies remains gap, which addressed this paper. The adopts...
Energy system models for off-grid systems usually tend to focus solely on the provision of electricity powering simple appliances, thus neglecting more energy-intensive and critical needs, such as water heating. The adoption a Multi-Energy System (MES) perspective would allow us not only provide comprehensive solutions addressing all types energy demand, but also exploit synergies between electric thermal sectors. To this end, we expand an existing open-source micro-grid optimization model...
MARIO (Multi-Regional Analysis of Regions through Input-Output) is a Python-based framework for building input-output models. It automates the parsing well-known databases (e.g. EXIOBASE, EORA, Eurostat) and customized tables. With respect to similar tools, like pymrio, it broadens scope application supply-use tables handles both monetary physical units. Employing an intuitive Excel-based API, facilitates advanced table manipulations allows modelling additional supply chains hybrid LCA...
Abstract Steel production is one of the most carbon-intensive industrial sectors, responsible for 8% European CO2 emissions. While traditional furnaces strongly rely on consumption coal or natural gas, potential opportunities decarbonization stand in adoption alternative technologies such as hydrogen-based Direct Reduction Iron (DRI) coupled with Electric Arc Furnaces (EAF). This work focuses Italian steel sector and aims at assessing economic environmental impact a switch towards...
The organization of seminars and conferences was strongly influenced by the covid-19 pandemic. In early period pandemic, many events were canceled or held completely online, using video conferencing tools such as ZOOM MS Teams Google Meet. Later, thanks to large-scale vaccination immunization, it possible organize again large in person. Nevertheless still necessary provide online modalities for participants who could not participate person, having fact hybrid with both remote person...
Russia’s invasion of Ukraine fuelled an energy crisis, considerably impacting Europe given its heavy reliance on Russian natural gas. Based four global integrated assessment models that are further soft-linked to two sectoral models, our study explores the trade-offs among three approaches living without gas in Europe: replacing with other imports, boosting domestic production, and accelerating efficiency. We find substituting from trade partners would miss opportunity accelerate...
To grant a reliable and affordable electricity provision to non-electrified communities, proper system sizing, based on accurate demand estimation is crucial. However, the absence of historical data, coupled with scarce, scattered often unreliable pre-electrification surveys, makes this process particularly prone errors. Acquiring especially high quality detail, difficult, time consuming expensive. Even though, in few site-specific cases limited data collected have allowed researchers...
Investing in low-carbon technologies, including light-duty vehicles, is a strategy to decarbonize residential sector and private mobility. This work aims at assessing the parameters driving economic convenience of battery electric vehicles (BEVs) for household, what are implications BEV adoption on total cost energy system case house renovation. An archetypal household has been modelled Italian context, where strong efficiency incentives have put place recent years. Adopting least-cost...
The energy transition process calls for striving interventions towards low-carbon technologies. While their deployment is expected to drive down greenhouse gases emissions, it bring along intense critical materials exploitation. This article presents a quantitative framework assess the impact of pathways in terms raw extraction, coupling Input-Output models with modelling methodologies, defined as Dynamic Extraction and Recycling (DYNERIO). analytically formalized tested through conceptual...