中国337个城市的工业固体废物清单:应用机器学习来完成数据处理
Qian Jia1,2, Kunsen Lin1,3, Jiawei Zhuang3
1College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, P.R. China.
Scientific data
|July 15, 2025
概括
中国中国中国中国.
科学领域:
- 环境科学 环境科学
- 数据科学数据科学数据科学
- 工业生态学 工业生态学
背景情况:
- 中国的快速工业化导致了大量的工业固体废物产生,在过去二十年中估计达到60千兆 (Gt).
- 由于来源众多,统计覆盖范围有限,许多中国地区缺乏对工业废物的全面时空数据集.
研究的目的:
- 从1990年到2022年,为中国所有337个城市开发一个完整的工业固体废物时空数据集.
- 在2022年为超过一半的中国城市提供六个主要工业废物子类别的详细数据.
主要方法:
- 从数千个来源收集数据,创建初始数据集.
- 开发并使用了六个机器学习模型,利用贝叶斯优化来为每个城市选择表现最佳的模型.
- 通过优化技术确保模型性能和弹性.
主要成果:
- 创建了一个涵盖所有337个中国城市 (1990-2022) 工业固体废物数量的综合数据集.
- 量化了2022年许多城市的六个主要工业废物子类别 (金渣,飞灰,炉渣,煤炭,尾矿,脱硫石膏) 的产量.
结论:
- 创建的数据集解决了中国工业废物的关键数据缺口.
- 该资源将帮助研究人员和政策制定者了解和管理工业废物挑战.
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