从1967年到2023年,基于文本形式的事件信息的增强全球石油泄漏数据集
Yiming Liu1, Zhuoli Yin2, Hua Cai3,4
1School of Sustainability Engineering and Environmental Engineering, Purdue University, West Lafayette, Indiana, 47907, USA.
Scientific data
|August 8, 2025
概括
本研究从非结构化文本中提取实际的石油释放量 (RAs),提高了全球石油泄漏数据的准确性. 增强的数据集有助于更准确地评估环境和经济影响.
科学领域:
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 准确的石油释放量 (RAs) 对于评估石油泄漏对环境,生态和经济的影响至关重要.
- 现有的全球漏油数据库往往缺乏结构化的RA数据,依赖于最坏情况下的估计.
- 更精确的RA值经常嵌入非结构化文本中,阻碍了大规模分析.
研究的目的:
- 开发一个框架,从文本数据中提取石油泄漏事件的实际RA.
- 增强全球油污数据集以准确的,文本衍生RA信息.
- 提高用于石油泄漏影响评估的数据的可靠性.
主要方法:
- 开发了一个框架,从非结构化的事件描述和更新中提取实际释放量 (RAs).
- 在提取过程中包含了泄漏确认和信息及时性的标准.
- 从1967年到2023年,对3,550起油污事件的验证和更新的RA数据.
主要成果:
- 对于大量的油污事件,成功地提取和结合了实际的RA.
- 创建了一个增强的数据集,提高了漏油释放数据的准确性.
- 增强的数据集现在包括1967年至2023年跨越3,550起事件的确认或更新的RA.
结论:
- 开发的框架有效地从文本数据中提取准确的石油释放量.
- 增强的数据集为研究石油泄漏影响提供了更可靠的基础.
- 这项工作通过补充现有数据以实际的RA信息来支持更准确的风险和环境影响评估.
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