Integrated assessment model-based scenarios are commonly used to project future emission pathways but suffer from submission biases and high computational cost. Here researchers develop a deep learning framework to generate synthetic scenarios and replicate key variables across a wide range of mitigation ambitions.
- Peijin Li
- Rongqi Zhu
- Yang Ou
