Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023
<p>Fires are a significant disturbance in Earth's systems. Smoke aerosols emitted from fires can cause environmental degradation and climatic perturbations, leading to exacerbated air pollution and posing hazards to public health. However, research on the climatic and health impacts of fi...
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Copernicus Publications
2025-08-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/3741/2025/essd-17-3741-2025.pdf |
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| author | Y. Hu C. Tian X. Yue Y. Lei Y. Cao R. Xu Y. Guo |
| author_facet | Y. Hu C. Tian X. Yue Y. Lei Y. Cao R. Xu Y. Guo |
| author_sort | Y. Hu |
| collection | DOAJ |
| description | <p>Fires are a significant disturbance in Earth's systems. Smoke aerosols emitted from fires can cause environmental degradation and climatic perturbations, leading to exacerbated air pollution and posing hazards to public health. However, research on the climatic and health impacts of fire emissions is severely limited by the scarcity of air pollution data directly attributed to these emissions. Here, we develop a global daily fire-sourced PM<span class="inline-formula"><sub>2.5</sub></span> concentration ([PM<span class="inline-formula"><sub>2.5</sub></span>]) dataset at a spatial resolution of 0.25° for the period 2000–2023, using the GEOS-Chem chemical transport model driven with two fire emission inventories, the Global Fire Emissions Database version 4.1 with small fires (GFED4.1s) and the Quick Fire Emission Dataset version 2.5r1 (QFED2.5). Simulated all-source [PM<span class="inline-formula"><sub>2.5</sub></span>] is bias-corrected using a machine learning algorithm, which incorporates ground observations from over 9000 monitoring sites worldwide. Then the simulated ratios between fire-sourced and all-source [PM<span class="inline-formula"><sub>2.5</sub></span>] at individual grids are applied to derive fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>]. Globally, the average fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>] is estimated to be 2.04 <span class="inline-formula">µg m<sup>−3</sup></span> with GFED4.1s and 3.96 <span class="inline-formula">µg m<sup>−3</sup></span> with QFED2.5. Both datasets show consistent spatial distributions with regional hotspots in central Africa and widespread decreasing trends over most areas. While the mean levels of fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>] are much higher at low latitudes, fire episodes in the boreal regions can cause PM<span class="inline-formula"><sub>2.5</sub></span> levels that are comparable to those of the tropics. This dataset, available at <span class="uri">https://doi.org/10.5281/zenodo.15493914</span> (Hu et al., 2025a) and <span class="uri">https://doi.org/10.5281/zenodo.15496596</span> (Hu et al., 2025b), serves as a valuable tool for exploring the impacts of fire-related air pollutants on climate, ecosystems, and public health, enabling accurate assessments and support for decision-making in environmental management and policy.</p> |
| format | Article |
| id | doaj-art-dd0515b7aaec4f8c9de4ae9832dc9e96 |
| institution | DOAJ |
| issn | 1866-3508 1866-3516 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj-art-dd0515b7aaec4f8c9de4ae9832dc9e962025-08-20T03:18:38ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162025-08-01173741375610.5194/essd-17-3741-2025Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023Y. Hu0C. Tian1X. Yue2Y. Lei3Y. Cao4R. Xu5Y. Guo6State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, ChinaState Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaJiangsu Nanjing Environmental Monitoring Center, Nanjing 210041, ChinaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia<p>Fires are a significant disturbance in Earth's systems. Smoke aerosols emitted from fires can cause environmental degradation and climatic perturbations, leading to exacerbated air pollution and posing hazards to public health. However, research on the climatic and health impacts of fire emissions is severely limited by the scarcity of air pollution data directly attributed to these emissions. Here, we develop a global daily fire-sourced PM<span class="inline-formula"><sub>2.5</sub></span> concentration ([PM<span class="inline-formula"><sub>2.5</sub></span>]) dataset at a spatial resolution of 0.25° for the period 2000–2023, using the GEOS-Chem chemical transport model driven with two fire emission inventories, the Global Fire Emissions Database version 4.1 with small fires (GFED4.1s) and the Quick Fire Emission Dataset version 2.5r1 (QFED2.5). Simulated all-source [PM<span class="inline-formula"><sub>2.5</sub></span>] is bias-corrected using a machine learning algorithm, which incorporates ground observations from over 9000 monitoring sites worldwide. Then the simulated ratios between fire-sourced and all-source [PM<span class="inline-formula"><sub>2.5</sub></span>] at individual grids are applied to derive fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>]. Globally, the average fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>] is estimated to be 2.04 <span class="inline-formula">µg m<sup>−3</sup></span> with GFED4.1s and 3.96 <span class="inline-formula">µg m<sup>−3</sup></span> with QFED2.5. Both datasets show consistent spatial distributions with regional hotspots in central Africa and widespread decreasing trends over most areas. While the mean levels of fire-sourced [PM<span class="inline-formula"><sub>2.5</sub></span>] are much higher at low latitudes, fire episodes in the boreal regions can cause PM<span class="inline-formula"><sub>2.5</sub></span> levels that are comparable to those of the tropics. This dataset, available at <span class="uri">https://doi.org/10.5281/zenodo.15493914</span> (Hu et al., 2025a) and <span class="uri">https://doi.org/10.5281/zenodo.15496596</span> (Hu et al., 2025b), serves as a valuable tool for exploring the impacts of fire-related air pollutants on climate, ecosystems, and public health, enabling accurate assessments and support for decision-making in environmental management and policy.</p>https://essd.copernicus.org/articles/17/3741/2025/essd-17-3741-2025.pdf |
| spellingShingle | Y. Hu C. Tian X. Yue Y. Lei Y. Cao R. Xu Y. Guo Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 Earth System Science Data |
| title | Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 |
| title_full | Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 |
| title_fullStr | Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 |
| title_full_unstemmed | Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 |
| title_short | Global high-resolution fire-sourced PM<sub>2.5</sub> concentrations for 2000–2023 |
| title_sort | global high resolution fire sourced pm sub 2 5 sub concentrations for 2000 2023 |
| url | https://essd.copernicus.org/articles/17/3741/2025/essd-17-3741-2025.pdf |
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