基于区块链的同位素大数据驱动的全球PM来源和干预措施的跟踪
Yuming Huang1,2, Xiangyu Li1, Yuehan Wu1
1Key Laboratory of Environmental Chemistry and Toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Nature communications
|April 24, 2025
概括
全球颗粒物 (PM) 同位素的新区块链数据库揭示了动态污染源. 这些同位素大数据对于有效的空气污染控制和未来的干预策略至关重要.
科学领域:
- 环境科学 环境科学
- 大气化学 大气化学
- 数据科学数据科学数据科学
背景情况:
- 控制大气颗粒物 (PM) 污染需要有效的来源追踪和干预评估.
- 同位素技术提供精确的来源追踪,但缺乏全球,长期的多化合物数据.
- 现有的数据限制阻碍了对颗粒污染动态的全面分析.
研究的目的:
- 建立一个全面的,全球范围的颗粒物 (PM) 和其排放的同位素数据库.
- 允许对PM污染源及其贡献进行回顾性和预测性分析.
- 通过同位素大数据,为未来的空气污染干预策略提供信息和指导.
主要方法:
- 汇编了来自66个国家的1890个污染事件的34,815个同位素指纹.
- 开发基于区块链的数据库,以长期,安全的数据存储和可访问性.
- 使用同位素数据估计来源对PM2.5及其化合物的贡献.
主要成果:
- PM来源被确定为不同的,动态变化的,并且通常与实施的干预措施不一致.
- 生物质燃烧被强调为PM污染的重要和日益增长的贡献者.
- 预测显示,在气候缓解下,PM水平可能在2100年减少,但如果没有自然排放控制,风险仍然存在.
结论:
- 基于区块链的同位素数据库为全球PM污染提供了前所未有的见解.
- 了解动态源贡献对于设计有效和及时的空气污染控制措施至关重要.
- 同位素大数据对于指导未来干预和实现与世卫组织指导方针一致的空气质量目标至关重要.
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