Policy-based emissions projections to support the Paris Agreement

Greenhouse gas emissions projections are important tools to evaluate progress in implementing the mitigation component of the Paris Agreement. They support understanding global emissions trajectories under current efforts and assessing progress towards countries’ climate pledges. However, developing these projections is resource-intensive, which results in substantial information gaps for most countries. Lack of information regarding countries’ emissions trajectories hinders international discussions regarding the effectiveness of the Paris Agreement and muddles accountability. We investigate two methods to estimate greenhouse gas emissions projections based on countries’ current effort levels. First, we assume minimal change from historical climate policy patterns. We analyse historical emission change rates to calculate future emissions within defined confidence intervals. Second, we anticipate emissions changes based on countries’ recent developments. We map potential determinants, compile policy-based projections, and employ machine-learning models to estimate emissions change rates. These simplified projections extend insights for the next Nationally Determined Contribution (NDC) updates, support future global stocktake processes and improve information availability for most countries worldwide. These innovative approaches provide concise, systematic methods to explore greenhouse gas emissions projections and contribute to a nuanced assessment of global progress in line with the Paris Agreement. In this conference, we aim to discuss key assumptions underpinning the analysis, identify additional use cases and present initial findings.