Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6787-2024
© 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/acp-24-6787-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Jun 2024
Research article |
| 12 Jun 2024
| 12 Jun 2024
Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants
Wenxuan Hua
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Sijia Lou
CORRESPONDING AUTHOR
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
Xin Huang
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
Zilin Wang
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Aijun Ding
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
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Cited
20 citations as recorded by crossref.
- Analysis of Forest Fire Emissions and Meteorological Impacts in Southwestern China Based on Multi-Source Satellite Observations L. Fang et al. https://doi.org/10.3390/atmos16101187
- Revisiting black carbon emission estimates in the Third Pole: a hierarchical Bayesian synthesis inversion perspective C. Roychoudhury et al. https://doi.org/10.1088/2515-7620/ae4858
- Biomass Burning over Africa: How to Explain the Differences Observed Between the Different Emission Inventories? T. N’Datchoh et al. https://doi.org/10.3390/atmos16040440
- Regional diversity in black carbon emissions, size, and mixing state across Asia: Implications for climate and public health S. Mishra et al. https://doi.org/10.1016/j.earscirev.2026.105578
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- Future climate-driven fires may boost ocean productivity in the iron-limited North Atlantic E. Bergas-Masso et al. https://doi.org/10.1038/s41558-025-02356-4
- Anthropogenic black carbon as short-lived climate pollutants: Critical advancements in global-regional monitoring, characterization, emission inventory, and impact analysis S. Abdillah et al. https://doi.org/10.1016/j.rser.2025.116284
- 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
- Using geostationary-satellite-derived sub-daily fire radiative power variability versus prescribed diurnal cycles to assess the impact of African fires on tropospheric ozone H. Wang et al. https://doi.org/10.5194/acp-25-17501-2025
- Refined source apportionment of nitrate aerosols based on isotopes and emission inventories in coastal city of northern China Y. Ni et al. https://doi.org/10.1016/j.scitotenv.2024.177388
- Evaluating the effects of COVID-19 lockdowns on air quality across some African countries Z. Han et al. https://doi.org/10.1039/D5EA00111K
- The Influence of Australian Bushfire on the Upper Tropospheric CO and Hydrocarbon Distribution in the South Pacific D. Lee et al. https://doi.org/10.3390/rs17122092
- Improving real-time high-resolution estimates of PM2.5 concentration fields in urban areas by the SmartAQ+ system with data fusion and machine learning I. Apostolopoulos et al. https://doi.org/10.1016/j.atmosenv.2025.121665
- Substantial discrepancies across global fire emissions inventories: a systematic intercomparison J. Yang et al. https://doi.org/10.1016/j.jes.2026.105563
- Near Real-Time Biomass Burning PM2.5 Emission Estimation to Support Environmental Health Risk Management in Northern Thailand Using FINNv2.5 C. Chotamonsak et al. https://doi.org/10.3390/toxics14010084
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- Measurement report: Characterization of aerosol hygroscopicity over Southeast Asia during the NASA CAMP2Ex campaign G. Lorenzo et al. https://doi.org/10.5194/acp-25-5469-2025
- A comprehensive inventory of China's methane emissions: Insights and changes from 2010 to 2020 Y. Shi et al. https://doi.org/10.1016/j.jclepro.2025.146089
20 citations as recorded by crossref.
- Analysis of Forest Fire Emissions and Meteorological Impacts in Southwestern China Based on Multi-Source Satellite Observations L. Fang et al. https://doi.org/10.3390/atmos16101187
- Revisiting black carbon emission estimates in the Third Pole: a hierarchical Bayesian synthesis inversion perspective C. Roychoudhury et al. https://doi.org/10.1088/2515-7620/ae4858
- Biomass Burning over Africa: How to Explain the Differences Observed Between the Different Emission Inventories? T. N’Datchoh et al. https://doi.org/10.3390/atmos16040440
- Regional diversity in black carbon emissions, size, and mixing state across Asia: Implications for climate and public health S. Mishra et al. https://doi.org/10.1016/j.earscirev.2026.105578
- Implementation of the ORACLE (v1.0) organic aerosol composition and evolution module into the EC-Earth3-AerChem model S. Kakavas et al. https://doi.org/10.5194/gmd-19-4271-2026
- Wildfire Plumes and Airborne Cyanobacterial Metabolites: A Case Study of Long-Range Transport Evidence E. Olonimoyo et al. https://doi.org/10.1021/acsestair.5c00505
- Future climate-driven fires may boost ocean productivity in the iron-limited North Atlantic E. Bergas-Masso et al. https://doi.org/10.1038/s41558-025-02356-4
- Anthropogenic black carbon as short-lived climate pollutants: Critical advancements in global-regional monitoring, characterization, emission inventory, and impact analysis S. Abdillah et al. https://doi.org/10.1016/j.rser.2025.116284
- 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
- Using geostationary-satellite-derived sub-daily fire radiative power variability versus prescribed diurnal cycles to assess the impact of African fires on tropospheric ozone H. Wang et al. https://doi.org/10.5194/acp-25-17501-2025
- Refined source apportionment of nitrate aerosols based on isotopes and emission inventories in coastal city of northern China Y. Ni et al. https://doi.org/10.1016/j.scitotenv.2024.177388
- Evaluating the effects of COVID-19 lockdowns on air quality across some African countries Z. Han et al. https://doi.org/10.1039/D5EA00111K
- The Influence of Australian Bushfire on the Upper Tropospheric CO and Hydrocarbon Distribution in the South Pacific D. Lee et al. https://doi.org/10.3390/rs17122092
- Improving real-time high-resolution estimates of PM2.5 concentration fields in urban areas by the SmartAQ+ system with data fusion and machine learning I. Apostolopoulos et al. https://doi.org/10.1016/j.atmosenv.2025.121665
- Substantial discrepancies across global fire emissions inventories: a systematic intercomparison J. Yang et al. https://doi.org/10.1016/j.jes.2026.105563
- Near Real-Time Biomass Burning PM2.5 Emission Estimation to Support Environmental Health Risk Management in Northern Thailand Using FINNv2.5 C. Chotamonsak et al. https://doi.org/10.3390/toxics14010084
- Understanding drivers and biases of simulated CO emissions from the INFERNO fire model over South America M. Velásquez-García et al. https://doi.org/10.5194/bg-23-1341-2026
- NMVOC emission optimization in China through assimilating formaldehyde retrievals from multiple satellite products C. Xu et al. https://doi.org/10.5194/acp-26-33-2026
- Measurement report: Characterization of aerosol hygroscopicity over Southeast Asia during the NASA CAMP2Ex campaign G. Lorenzo et al. https://doi.org/10.5194/acp-25-5469-2025
- A comprehensive inventory of China's methane emissions: Insights and changes from 2010 to 2020 Y. Shi et al. https://doi.org/10.1016/j.jclepro.2025.146089
Saved (final revised paper)
Latest update: 17 Jul 2026
Short summary
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from four inventories for seven major wildfire-prone regions. Uncertainties in vegetation classification methods, fire detection products, and cloud obscuration effects lead to bias in these biomass burning (BB) emission inventories. By comparing simulations with measurements, we provide certain inventory recommendations. Our study has implications for reducing uncertainties in emissions in further studies.
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from...
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