Essays on optimal emissions control and environmental policy under stochastic dynamics

Resumo

This thesis develops mathematical models to analyze environmental policies under uncertainties, focusing on carbon capture and storage (CCS) and NetZero strategies. The first model introduces a continuous-time optimal stopping and control framework, integrating CCS into decision-making process. Using neural networks to approximate the value function and the FischerBurmeister function to handle non-linearities, the model captures complex behavior and boundary conditions. The results show that emissions capture slows pollutant accumulation and delays optimal policy adoption, emphasizing trade-offs between immediate action and long-term impacts. The second model extends the analysis to NetZero policies, modeling the stochastic dynamics of pollution and emissions. A linear-quadratic optimal control problem leads to a system of ordinary differential equations (ODEs) that characterize optimal control policies, incorporating long-term pollution costs through terminal conditions. The findings highlight the interplay between emissions, costs, and uncertainties, providing insights into sustainable policy design. This thesis advances the understanding of environmental policy timing and control, offering tools to balance economic and environmental trade-offs and guide sustainable decision-making.

Ficha do documento

Tipo

Tese

Ano

2025

Instituição

Fundação Getulio Vargas

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Acesso aberto

Identificador

oai:repositorio.fgv.br:10438/36524

Temas

Meio Ambiente

Palavras-chave

Modelos matemáticosSustentabilidadeProcesso estocásticoPolítica ambientalFinanças