Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-7679-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-7679-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Nov 2024
Development and technical paper |
| 04 Nov 2024
| 04 Nov 2024
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
Samiha Binte Shahid
Department of Chemical & Environmental Engineering, Center for Environmental Research & Technology, University of California, Riverside, Riverside, CA 92521, United States
Forrest G. Lacey
Research Applications Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
Atmospheric Chemistry Observations and Modeling Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
Christine Wiedinmyer
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, United States
Robert J. Yokelson
Department of Chemistry, University of Montana, Missoula, MT 59812, United States
Department of Chemical & Environmental Engineering, Center for Environmental Research & Technology, University of California, Riverside, Riverside, CA 92521, United States
Atmospheric Chemistry Observations and Modeling Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
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Cited
16 citations as recorded by crossref.
- Biomass burning emission estimation in the MODIS era: State-of-the-art and future directions M. Parrington et al. https://doi.org/10.1525/elementa.2024.00089
- Measurement report: Extreme heat and wildfire emissions enhance volatile organic compounds in a temperate forest C. Salvador et al. https://doi.org/10.5194/acp-25-16611-2025
- Emission factors and optical properties of black and brown carbon emitted at a mixed-conifer forest prescribed burn J. Butler et al. https://doi.org/10.5194/acp-26-839-2026
- Modeling the assessment of the effectiveness of solving aviation management problems in an emergency A. Kalach et al. https://doi.org/10.12737/2219-0767-2025-7-12
- Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 1: system description M. Moran et al. https://doi.org/10.5194/gmd-19-4137-2026
- Subtropical southern Africa fire emissions of nitrogen oxides and ammonia obtained with satellite observations and GEOS-Chem E. Marais et al. https://doi.org/10.1039/D5EA00041F
- Carbon emissions from forest harvest and fire offset approximately half of carbon sequestration of forestation in China during 1986-2020 J. Mai et al. https://doi.org/10.1016/j.agrformet.2025.110830
- Landscape fire emissions from the 5th version of the Global Fire Emissions Database (GFED5) G. van der Werf et al. https://doi.org/10.1038/s41597-025-06127-w
- UFS-RAQMS global atmospheric composition model: TROPOMI CO column assimilation M. Bruckner et al. https://doi.org/10.5194/gmd-18-8109-2025
- Emissions from burned structures in wildfires as significant yet unaccounted sources of US air pollution W. Tang et al. https://doi.org/10.1038/s41467-025-66292-9
- Emission time and amount of crop residue burning play critical role on PM2.5 variability during October–November in northwestern India during 2022–2024 A. Biswal et al. https://doi.org/10.1039/D5EA00052A
- Global Wildland Fire Emissions of Full-Volatility Organic Compounds from 1997 to 2023 L. Huang et al. https://doi.org/10.1021/acs.est.5c10217
- Modeling the assessment of the effectiveness of solving aviation management problems in an emergency A. Kalach et al. https://doi.org/10.12737/2219-0767-2025-18-4-7-12
- Comprehensive Fuel and Emissions Measurements Highlight Uncertainties in Smoke Production Using Predictive Modeling Tools A. Tasnia et al. https://doi.org/10.1021/acsestair.4c00142
- The newly developed Multi-ensemble Biomass-burning Emissions Inventory (MBEI): characterizing and unraveling spatiotemporal uncertainty in global biomass burning emissions X. Liu et al. https://doi.org/10.5194/essd-18-1203-2026
- Incorporating observed fire severity in refined emissions estimates for boreal and temperate forest fires in the carbon budget model CBM-CFS3 v1.2 D. Thompson et al. https://doi.org/10.5194/gmd-19-3617-2026
16 citations as recorded by crossref.
- Biomass burning emission estimation in the MODIS era: State-of-the-art and future directions M. Parrington et al. https://doi.org/10.1525/elementa.2024.00089
- Measurement report: Extreme heat and wildfire emissions enhance volatile organic compounds in a temperate forest C. Salvador et al. https://doi.org/10.5194/acp-25-16611-2025
- Emission factors and optical properties of black and brown carbon emitted at a mixed-conifer forest prescribed burn J. Butler et al. https://doi.org/10.5194/acp-26-839-2026
- Modeling the assessment of the effectiveness of solving aviation management problems in an emergency A. Kalach et al. https://doi.org/10.12737/2219-0767-2025-7-12
- Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 1: system description M. Moran et al. https://doi.org/10.5194/gmd-19-4137-2026
- Subtropical southern Africa fire emissions of nitrogen oxides and ammonia obtained with satellite observations and GEOS-Chem E. Marais et al. https://doi.org/10.1039/D5EA00041F
- Carbon emissions from forest harvest and fire offset approximately half of carbon sequestration of forestation in China during 1986-2020 J. Mai et al. https://doi.org/10.1016/j.agrformet.2025.110830
- Landscape fire emissions from the 5th version of the Global Fire Emissions Database (GFED5) G. van der Werf et al. https://doi.org/10.1038/s41597-025-06127-w
- UFS-RAQMS global atmospheric composition model: TROPOMI CO column assimilation M. Bruckner et al. https://doi.org/10.5194/gmd-18-8109-2025
- Emissions from burned structures in wildfires as significant yet unaccounted sources of US air pollution W. Tang et al. https://doi.org/10.1038/s41467-025-66292-9
- Emission time and amount of crop residue burning play critical role on PM2.5 variability during October–November in northwestern India during 2022–2024 A. Biswal et al. https://doi.org/10.1039/D5EA00052A
- Global Wildland Fire Emissions of Full-Volatility Organic Compounds from 1997 to 2023 L. Huang et al. https://doi.org/10.1021/acs.est.5c10217
- Modeling the assessment of the effectiveness of solving aviation management problems in an emergency A. Kalach et al. https://doi.org/10.12737/2219-0767-2025-18-4-7-12
- Comprehensive Fuel and Emissions Measurements Highlight Uncertainties in Smoke Production Using Predictive Modeling Tools A. Tasnia et al. https://doi.org/10.1021/acsestair.4c00142
- The newly developed Multi-ensemble Biomass-burning Emissions Inventory (MBEI): characterizing and unraveling spatiotemporal uncertainty in global biomass burning emissions X. Liu et al. https://doi.org/10.5194/essd-18-1203-2026
- Incorporating observed fire severity in refined emissions estimates for boreal and temperate forest fires in the carbon budget model CBM-CFS3 v1.2 D. Thompson et al. https://doi.org/10.5194/gmd-19-3617-2026
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive...
