ArticleInternational journal of wildland fire2025
Enhancing Fire Emissions Inventories for Acute Health Effects Studies: Integrating High Spatial and Temporal Resolution Data.
Article in International journal of wildland fire, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Improved wildfire smoke exposure estimates for human health studies in the western United States.Air pollution modeling and its application · 2026Article
- Modeling Daily Plume Specific Smoke Concentrations for Health Effects Studies with Estimates of Fire Size, Plume Age, and Fuel Type.ACS ES&T air · 2025Article
- The Impact of Fire Emissions Inputs on Smoke Plume Dispersion Modeling Results.Fire (Basel, Switzerland) · 2025Article
- Influence of fire characteristics on the associations between smoke PMEnvironment international · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Background: Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies. Aims: This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression. Methods: High temporal and spatial resolution burned area information from two FEI products are combined into a single dataset, and a linear regression model fills gaps in daily fire progression. Key Results: The combined dataset provides up to 71% more PM Conclusions: The FEI combination method results in improved FEI information with no gaps in daily fire emissions estimates. Implications: The combined dataset provides a functional improvement to FEI data that can be achieved with currently available data.
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Registered trials
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