Global Ensemble Fire Emission Product Version 1.0 (EnsemFire V1.0)

This paper presents EnsemFire v1.0, a global ensemble fire emission dataset that provides daily emissions at 0.1° × 0.1° spatial resolution for key air pollutants like fine particulate matter (PM₂.₅), black carbon (BC), organic carbon (OC), carbon monoxide (CO), ammonia (NH₃), nitrogen oxides (NO<sub>x</sub>), and sulfur dioxide (SO₂), greenhouse gases including carbon dioxide (CO₂) and methane (CH₄), and fire radiative power (FRP). EnsemFire integrates seven widely used biomass burning emission inventories, including five global datasets (GFAS, FINN, FEER, QFED, GBBEPx) and two regional products (EPA and CFFEPS). Our analysis reveals noticeable inconsistencies among these datasets, reflecting the large uncertainty in biomass burning emission estimates. By applying an ensemble approach, EnsemFire reduces this uncertainty and provides a more robust emission estimate. When used as input to the Unified Forecast System (UFS) model, EnsemFire significantly reduces simulation bias and improves the model performance to predict aerosol optical depth (AOD) compared to the control run that uses the default emission input. This dataset offers a valuable resource for atmospheric modeling, air quality forecasting, and climate research.

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Publication Details

Journal
Scientific Data
Published
2025-12-18
DOI
https://doi.org/10.1038/s41597-025-06429-z
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
0.00

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article

Global Ensemble Fire Emission Product Version 1.0 (EnsemFire V1.0)

Shan Sun, Daniel Tong, Jack Chen, Charles Ichoku et al.
Scientific Data
Atmospheric chemistry and aerosols
article

Global Ensemble Fire Emission Product Version 1.0 (EnsemFire V1.0)

Shan Sun, Daniel Tong, Jack Chen, Charles Ichoku, Yunyao Li, Anton Darmenov, Gonzalo A. Ferrada, Ziheng Sun, Xiaoyang Zhang, Li Zhang
article en

Abstract

This paper presents EnsemFire v1.0, a global ensemble fire emission dataset that provides daily emissions at 0.1° × 0.1° spatial resolution for key air pollutants like fine particulate matter (PM₂.₅), black carbon (BC), organic carbon (OC), carbon monoxide (CO), ammonia (NH₃), nitrogen oxides (NO<sub>x</sub>), and sulfur dioxide (SO₂), greenhouse gases including carbon dioxide (CO₂) and methane (CH₄), and fire radiative power (FRP). EnsemFire integrates seven widely used biomass burning emission inventories, including five global datasets (GFAS, FINN, FEER, QFED, GBBEPx) and two regional products (EPA and CFFEPS). Our analysis reveals noticeable inconsistencies among these datasets, reflecting the large uncertainty in biomass burning emission estimates. By applying an ensemble approach, EnsemFire reduces this uncertainty and provides a more robust emission estimate. When used as input to the Unified Forecast System (UFS) model, EnsemFire significantly reduces simulation bias and improves the model performance to predict aerosol optical depth (AOD) compared to the control run that uses the default emission input. This dataset offers a valuable resource for atmospheric modeling, air quality forecasting, and climate research.

Scientific DataVol. 13(1)
Goddard Space Flight Center (US), Environment and Climate Change Canada (CA), Cooperative Institute for Research in Environmental Sciences (US), George Mason University (US), South Dakota State University (US), University of Colorado Boulder (US), The University of Texas at Arlington (US), University of Maryland, Baltimore County (US), NOAA Earth System Research Laboratory (US)
U.S. Environmental Protection Agency, National Oceanic and Atmospheric Administration, NOAA Weather Program Office
Openalex Percentile: Top 55%
Atmospheric chemistry and aerosols
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