Nicolò Golinucci

The photovoltaic supply chain is complex and geographically concentrated. Assessing the impacts of policies targeting it requires models that explicitly represent supply-chain structure. While process-based life-cycle assessment truncates economy-wide effects and top-down input–output models are too aggregated to resolve individual manufacturing stages, our study develops a hybrid framework integrating a process-based PV supply chain model into the multi-regional input–output accounting structure of EXIOBASE. The model is first verified against reference literature ranges of solar electricity carbon footprints and producer prices, showing literature-consistent results that purely top-down models miss by omitting productive capital. The framework is applied to the Net Zero Industry Act, a major European Union (EU) reshoring policy, under a scenario where 40% of module demand is supplied domestically. Results show that reshoring mainly affects downstream stages, while upstream production remains largely external, leading to moderate changes in consumption-based emissions and limited gains in EU value-added and employment.

The carbon footprint of electricity is a critical metric for climate policy and corporate sustainability reporting, yet its quantification is hampered by a lack of methodological consensus and a fragmented evidence base. This fragmentation reflects a central debate in industrial ecology regarding the consistency and comparability of life-cycle-based emission factors across different modelling paradigms. This study addresses this gap by performing a systematic, quantitative comparison of electricity emission factors from a wide range of authoritative sources, including process-LCA databases (Ecoinvent), environmentally extended input–output tables (EXIOBASE, EMERGING, EORA, GLORIA, GTAP), primary agency data (IEA), and others. We harmonize technology taxonomies and GHG characterization factors to compare technology-level and national-level emission factors for the EU and the US. Our findings indicate that, for technology-specific emission factors, there is a moderate level of agreement regarding direct operational emissions (direct carbon intensity). However, we observe substantial and systematic variation when it comes to full life-cycle carbon intensity. These discrepancies propagate to national-level estimates, where a country’s calculated carbon intensity can significantly vary, solely based on the data source chosen. This paper provides a useful reference to deconstruct and understand such divergences. We operationalize these findings into a set of practical selection criteria that enable analysts and decision-makers to make transparent and context-appropriate choices. We conclude that a more transparent and critical approach to sourcing emission data is fundamental to the credibility of carbon accounting and the broader energy transition.