arXiv Machine LearningBy Brittany V. Lancellotti, Jordan M. Malof, Aaron Davitt, Gavin McCormick, Shelby Anderson, Pol Carb\'o-Mestre, Gary Collins, Verity Crane, Zoheyr Doctor, George Ebri, Kevin Foster, Trey M. Gowdy, Michael Guzzardi, John Heal, Heather Hunter, David Kroodsma, Khandekar Mahammad Galib, Paul J. Markakis, Gavin McDonald, Daniel P. Moore, Eric D. Nguyen, Sabina Parvu, Michael Pekala, Christine D. Piatko, Amy Piscopo, Mark Powell, Krsna Raniga, Elizabeth P. Reilly, Michael Robinette, Ishan Saraswat, Patrick Sicurello, Isabella S\"oldner-Rembold, Raymond Song, Charlotte Underwood, Kyle Bradbury
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.
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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.
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.
By Jacopo Ghirri, Carlos Rodriguez-Pardo, Lara Aleluia Reis, Massimo Tavoni
arXiv:2606. 10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Category 1 under the Corporate Sustainability Reporting Directive (CSRD), which requires disclosure for fiscal years starting January 2024.
arXiv:2609.24634v1 Announce Type: new
Abstract: Nitrogen dioxide (NO2) is a common air pollutant, released into the atmosphere through the incomplete burning of fossil fuels, and associated with resp...
arXiv:2607. 03298v1 Announce Type: cross Abstract: Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human systems that both drive and respond to environmental change.