arXiv AI By Timothy C. Pearce, David J. T. Smith, Alec Dobney, Alessia Freddo

Meteorology-driven Causal Nowcasting of Fugitive Landfill Emissions Enables Proactive Public Health Response

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arXiv:2608. 14254v1 Announce Type: cross Abstract: Fugitive emissions from waste sites increasingly expose communities to toxic and odorous gases, yet public-health responses remain largely retrospective, with episodes investigated only after residents have been exposed.

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arXiv Machine Learning
Jul 24

Climate-resilient electric vehicle charging infrastructure for sustainable cities: An interpretable causal-ensemble framework for preventive maintenance and low-carbon mobility

arXiv:2607. 21444v1 Announce Type: cross Abstract: Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme heat, heavy precipitation, and humidity increasingly raises equipment fault risk and undermines the resilience of urban energy and mobility services.

By Cande Lian (School of Management, Foshan University, Foshan, China), Wentao Zeng (School of Management, Foshan University, Foshan, China), Jiabin Wu (School of Management, Foshan University, Foshan, China), Yiming Bie (School of Transportation, Jilin University, Changchun, China), Wei Zhou (Department of Civil and Environmental Engineering, National University of Singapore)
Hugging Face Trending Papers
Jul 23

Climate-resilient electric vehicle charging infrastructure for sustainable cities: An interpretable causal-ensemble framework for preventive maintenance and low-carbon mobility

Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme heat, heavy precipitation, and humidity increasingly raises equipment fault risk and undermines the resilience of urban energy and mobility services. Shifting operation from reactive repair to preventive maintenance depends on accurate, forward-looking fault-risk prediction, a task complicated by the heterogeneous time scales of physical, behavioral, contextual, and historical signals and by forecasting over a multi-week horizon.

arXiv Machine Learning
Jul 24

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry

arXiv:2607. 20778v1 Announce Type: new Abstract: Weather forecasting foundation models (FMs) are increasingly fine-tuned to predict air quality, offering fast global pollution forecasts at lower computational cost than conventional chemical transport models.

By Jason Y. Hu, Ivan Higuera-Mendieta, Patrick Obin Sturm, Makoto M. Kelp
arXiv Machine Learning
Jul 7

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.

By 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