arXiv:2608.14254v2 Announce Type: replace-cross
Abstract: Which meteorological processes control exposure to fugitive gases downwind of a source, and on what timescales, have largely been inferred fr...
By Timothy C. Pearce, David J. T. Smith, Alec Dobney, Alessia Freddo
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)
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.
The paper proposes an event-based approach to predict transitions into vineyard disease‑risk periods within a 3–7 day window, rather than daily disease status. It defines events only after a minimum disease‑free gap to reduce label fragmentation and uses multi‑year agro‑meteorological data to capture humidity, rainfall, temperature, and seasonal patterns. Experiments with XGBoost, LSTM, and TCN models show that this formulation improves short‑horizon warning, highlighting trade‑offs among recall, lead time, and false alerts.
By Ivica Dimitrovski, Ivan Kitanovski, Danco Davcev, Slobodan Kalajdziski, Kosta Mitreski
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:2607. 19381v1 Announce Type: new Abstract: Air pollution causes an estimated 7.
By Rishi Bharadwaj, Manik Gupta, Pandarasamy Arjunan