Deep Learning Projects Europe Will Miss 2030 Climate Target

The European Union has set an ambitious goal to reduce greenhouse gas emissions by 55% below 1990 levels by 2030. However, this study casts doubt on whether current trends are sufficient to meet this commitment. Researchers applied deep learning techniques to high-resolution socioeconomic and sectoral data across the EU27 member states up to 2023. This allowed them to project sectoral CO2 trajectories based on observed momentum, without assuming any changes in policy effectiveness beyond what is already reflected in historical data.The projections indicate that the EU27's emissions will exceed the 2030 target by a substantial 35%, translating to a 620 Mt CO2 shortfall. Only a small number of countries appear to be on track to meet the bloc's commitments. While the Power sector is projected to achieve target-consistent reductions, largely due to the transition to renewables, the Mobility sector shows minimal progress and is expected to account for over a third of total emissions by 2030. This inertia in Mobility is identified as a structural issue across member states, rather than being concentrated geographically.These findings highlight a significant gap between Europe's climate ambition and its current implementation trajectory. The research strongly suggests that substantial additional interventions are necessary to bridge this gap and calls for the establishment of up-to-date energy information systems across Europe to better inform policy decisions.