Simulating the air quality impact of prescribed fires using graph neural network-based PM2.5 forecasts
The increasing size and severity of wildfires across the western United States have generated dangerous levels of PM2.5 concentrations in recent years. In a changing climate, expanding the use of prescribed fires is widely considered to be the most robust fire mitigation strategy. However, reliably...
Saved in:
Main Authors: | Kyleen Liao, Jatan Buch, Kara D. Lamb, Pierre Gentine |
---|---|
Format: | Article |
Language: | English |
Published: |
Cambridge University Press
2025-01-01
|
Series: | Environmental Data Science |
Subjects: | |
Online Access: | https://www.cambridge.org/core/product/identifier/S2634460225000044/type/journal_article |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hurricane and Tropical Storm Impacts on Prescribed Fire and Wildfire Management Practices
by: David R. Godwin, et al.
Published: (2022-03-01) -
Assessment of the Contribution of Local and Regional Biomass Burning on PM2.5 in New York/New Jersey Metropolitan Area
by: Subraham Singh, et al.
Published: (2022-06-01) -
Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting
by: Ang Guo, et al.
Published: (2025-01-01) -
Short-term urban traffic forecasting in smart cities: a dynamic diffusion spatial-temporal graph convolutional network
by: Xiang Yin, et al.
Published: (2025-01-01) -
Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model
by: Amir Miraki, et al.
Published: (2025-01-01)