Economic analysis of Climate Impacts and Policy Division
Edificio Porta dell'Innovazione - Piano 2 - via della Libertà 12 - 30175 Venezia Marghera (VE), Italy
Lorenza Campagnolo holds a Ph.D. in Economics from Graduate School of Economics and Management in Venice. She joined CMCC in 2012 and her work focuses on economic assessment of climate change impacts and mitigation policies in a General Equilibrium framework. She contributed to model energy sectors, in particular renewable and alternative energies, and to develop adaptation options in agriculture. In addition, she has worked on several projects regarding the measurement of current wellbeing and future sustainability with indicators and indices (PARIS REINFORCE, APPS, FEEM Sustainability Index and E-Frame), and collaborates with ASVIS (Alleanza Italiana per lo Sviluppo Sostenibile). Her personal interests include the assessment of climate change impacts on human health, and integrating empirical and macroeconomic approaches for the analysis of poverty, inequality and energy access in developing countries.
LATEST PUBLICATIONS
- The impacts of decarbonization pathways on Sustainable Development Goals in the European Union
- The cost of climate change on households and families in the EU
- A multi-model analysis of the EU's path to net zero
- A multi-model analysis of the EU’s path to net zero.
- Navigating through an energy crisis: challenges and progress towards electricity decarbonisation, reliability, and affordability in Italy
- Climate and sustainability co-governance in Kenya: A multi-criteria analysis of stakeholders' perceptions and consensus
- Distributional consequences of climate change impacts on residential energy demand across Italian households
- A multi-model analysis of long-term emissions and warming implications of current mitigation efforts
- Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison
- Challenges in the harmonisation of global integrated assessment models: A comprehensive methodology to reduce model response heterogeneity