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全球集团火灾排放产品版本1.0 (EnsemFire V1.0) 版本
Yunyao Li1,2,3, Daniel Tong4,5, Ziheng Sun6
1Department of Earth and Environmental Sciences, The University of Texas at Arlington, Arlington, TX, 76019, USA. yunyao.li@uta.edu.
Scientific data
|December 18, 2025
概括
EnsemFire v1.0是一个新的全球火灾排放数据集,可以减少生物质燃烧估计的不确定性. 这种增强的数据集改善了空气质量和气候模型预测.
科学领域:
- 大气科学 大气科学
- 环境科学 环境科学
- 地球系统科学 地球系统科学
背景情况:
- 生物质燃烧是空气污染物和温室气体的重要来源.
- 现有的排放库存显示出相当大的不一致性,导致排放估计的不确定性很大.
- 准确的火灾排放数据对于大气建模,空气质量预测和气候研究至关重要.
研究的目的:
- 为了介绍EnsemFire v1.0,一个全球集体火灾排放数据集.
- 通过整合多个库存,减少生物质燃烧排放估计的不确定性.
- 评估EnsemFire对大气模型性能的影响.
主要方法:
- 将七个全球和区域生物质燃烧排放清单整合到一个总体数据集中 (EnsemFire v1.0).
- 为各种污染物,温室气体和火灾辐射功率提供0.1° × 0.1°空间分辨率的每日排放量.
- 利用统一预测系统 (UFS) 模型评估EnsemFire对模拟偏差和气溶光学深度预测的影响.
主要成果:
- EnsemFire v1.0 集成了多个数据集,揭示了它们之间的重大不一致性.
- 整体方法有效地减少了生物质燃烧排放估计的不确定性.
- 与默认的排放输入相比,使用EnsemFire作为UFS模型的输入减少了模拟偏差,并改善了气溶光学深度预测.
结论:
- EnsemFire v1.0提供了一个更稳健,更不确定的生物质燃烧排放估计.
- 该数据集是大气建模,空气质量预测和气候研究的宝贵资源.
- EnsemFire提高了大气模型在预测关键环境变量的性能.
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