CO2 Emissions and the 🤗 Hub: Leading the Charge

CO₂ Emissions and Models Performance: Insights from the Open LLM Leaderboard

EU-ETS under attack? The impact of carbon price suppression on the decarbonization of the power sector

arXiv:2608. 12363v1 Announce Type: cross Abstract: European countries are debating policies to mitigate the increased energy costs caused by renewed geopolitical tensions, while pursuing decarbonization and electrification.

Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers

arXiv:2606. 05420v1 Announce Type: new Abstract: The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven by the adoption of artificial intelligence, has raised concerns about this industry's environmental footprint.

Closing Gaps in Emissions Monitoring with Climate TRACE

arXiv:2511. 19277v2 Announce Type: replace Abstract: Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning.

Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

Carbon markets put a price on emissions, yet that price remains hard to forecast. Work in this area clusters on the EU and Chinese schemes, compresses regulatory text into a sentiment score, and repor...

Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

The study uses deep learning on high‑resolution socioeconomic and sectoral data to project EU27 CO₂ emissions through 2023 and beyond. It finds that, under current trends, EU emissions will exceed the 2030 target by 35 % (620 Mt CO₂ shortfall), with only a few countries on track. While the power sector is on target thanks to renewables, mobility contributes over a third of emissions and shows little progress, indicating structural inertia across member states.

Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

The paper proposes EPA-CarbonNet, a six‑layer model that fuses carbon market price series with policy text via cross‑attention and calibrated intervals, aiming to provide explainable, policy‑aware predictions for carbon credit prices. It evaluates the approach on eleven years of daily S&P carbon index data, finding that a simple random walk outperforms the model on five‑day RMSE, while the model achieves the best directional accuracy at 58.6%. The study identifies ten recurring gaps in current research and releases all code, data, and results publicly.

Engineering Carbon Credits Towards A Responsible FinTech Era: The Practices, Implications, and Future

arXiv:2501. 14750v3 Announce Type: replace-cross Abstract: Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage their carbon footprint.

Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

The paper uses deep learning on high‑resolution socioeconomic and sectoral data to project EU27 CO₂ emissions through 2030. It finds that emissions will exceed the EU’s 55% reduction target by 35% (620 Mt CO₂ shortfall), with only a few countries on track. While the power sector is on target thanks to renewables, mobility remains a major source of emissions, indicating structural inertia across member states.

Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting

arXiv:2606. 14707v1 Announce Type: cross Abstract: AI training and deployment consume substantial electricity, but carbon outcomes remain weakly integrated into routine model development decisions.

Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand

arXiv:2606. 00811v1 Announce Type: cross Abstract: Data centers now account for 4.

Heterogeneous Effects of Green Finance on Urban Decarbonization: Evidence from 285 Cities in China

arXiv:2606. 06986v1 Announce Type: new Abstract: While green finance has become a key instrument for low-carbon city transitions, its actual decarbonization effects and transmission mechanisms remain unclear.