| Autor: |
Hu, Yonghang, Tian, Chenguang, Yue, Xu, Lei, Yadong, Cao, Yang, Xu, Rongbin, Guo, Yuming |
| Předmět: |
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| Zdroj: |
Earth System Science Data Discussions; 10/21/2024, p1-24, 24p |
| Abstrakt: |
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 PM2.5 concentration ([PM2.5]) 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 [PM2.5] are bias-corrected using a machine learning algorithm, which incorporates ground observations from over 9000 monitoring sites worldwide. Then the simulated ratios between fire- and all-source [PM2.5] at individual grids are applied to derive fire-sourced [PM2.5]. Globally, the average fire-sourced [PM2.5] is estimated to be 1.94 μg m-3 with GFED4.1s and 3.74 μg m-3 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 [PM2.5] are much larger at low latitudes, fire episodes at the boreal regions can cause comparable PM2.5 levels as in the tropics. This dataset serves as a valuable tool for exploring the impacts of fire-related air pollutants on climate, ecosystems, and public health, enabling accurate assessments and supports for decision-making in environmental management and policy. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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