Thesis: This PhD thesis manuscript presents three research projects focused on key issues related to climate change, policy design, and demographic impacts. It highlights the importance of integrating uncertainty into climate strategies and exploring the relationship between population dynamics and climate change in an innovative way.In the first chapter, the impact of considering climate uncertainties ex ante on optimal greenhouse gas emission trajectories is analyzed. Using a compact climate model, developed from state-of-the-art physics and calibrated Bayesianly with CMIP6 experiments and historical data, the study reveals a more ambitious CO2 mitigation trajectory in cost-benefit analysis. This results in a reduction of the optimal carbon budget and the maximum average temperature, as well as an increase in the carbon price by 2030. This precautionary effect is also observed when considering probabilistic targets related to climate change indicators.The impact of climate change on fertility is poorly understood and under-studied. Most studies focus on specific regions or extreme events. The second chapter addresses this gap by examining the effect of climate change on fertility in low- and middle-income countries using a fertility rate database for 590 regions in 65 countries, representing 3.8 billion people in 2020. Using this data and weather information, the short-term impacts of temperature and precipitation shocks are first estimated: fertility temporarily decreases nine months after exposure to a temperature shock, while it increases following a precipitation shock during pregnancy, possibly due to a rise in premature births. In the longer term, temperature shocks have little impact on fertility, but positive precipitation shocks are correlated with increased fertility. Projecting these results onto SSP-RCP scenarios estimates the future impacts of climate change on global demographics: under these assumptions, climate change would lead to a significant population increase, particularly in scenarios with the highest warming and in regions with the highest fertility rates.Finally, the study decomposes the carbon footprint by age across many countries. Household budget surveys and a statistical model inspired by a collective household model are used to allocate consumption within households. This allows for the construction of age-specific carbon footprint profiles using Input-Output databases. The study identifies a generally increasing age-related emission profile shaped like a camel, with peaks around ages 30 and 60, related to scale effects within households. Moreover, it shows that population aging has had only a marginal impact on the dynamics of France’s carbon footprint. By decomposing carbon footprint profiles by age, period, and cohort, it is found that some generations, especially those born between 1945 and 1950, have had significantly higher lifetime carbon footprints compared to subsequent generations. Ignoring generational effects leads to an estimation of a minor influence of population aging on greenhouse gas emission trajectories, while incorporating them into the model results in a significant reduction in the cumulative carbon footprint by 2100.