Significant spatiotemporal changes in atmospheric particulate mercury pollution in China: Insights from meta-analysis and machine-learning

被引：0
|
作者：
Wang, Haolin [1 ]
Li, Tianshuai [1 ]
Wang, Guoqiang [1 ]
Peng, Yanbo [2 ]
Zhang, Qingzhu [1 ]
Wang, Xinfeng [1 ]
Ren, Yuchao [1 ]
Liu, Ruobing [1 ]
Yan, Shuwan [1 ]
Meng, Qingpeng [1 ]
Wang, Yujia [1 ]
Wang, Qiao [1 ]
机构：
[1] Academician Workstation for Big Data Research in Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao,266237, China
[2] Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan,250101, China
来源：
Science of the Total Environment | 2024年 / 955卷
关键词：
D O I：
10.1016/j.scitotenv.2024.177184
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Alterations of throughfall and stemflow chemistry by vegetation in China: Insights from a machine learning based meta-analysis
    Zhang, Yafeng
    Yao, Weiqi
    Yuan, Chuan
    Chen, Ning
    Levia, Delphis F.
    JOURNAL OF HYDROLOGY, 2024, 641
  • [2] Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis
    Renato Cuocolo
    Maria Brunella Cipullo
    Arnaldo Stanzione
    Valeria Romeo
    Roberta Green
    Valeria Cantoni
    Andrea Ponsiglione
    Lorenzo Ugga
    Massimo Imbriaco
    European Radiology, 2020, 30 : 6877 - 6887
  • [3] Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis
    Cuocolo, Renato
    Cipullo, Maria Brunella
    Stanzione, Arnaldo
    Romeo, Valeria
    Green, Roberta
    Cantoni, Valeria
    Ponsiglione, Andrea
    Ugga, Lorenzo
    Imbriaco, Massimo
    EUROPEAN RADIOLOGY, 2020, 30 (12) : 6877 - 6887
  • [4] ARTIFICIAL INTELLIGENCE TO DIAGNOSE ACUTE CORONARY SYNDROMES: INSIGHTS FROM A META-ANALYSIS OF MACHINE LEARNING
    Thao Huynh
    Iannatonne, Patrick
    Zhao, Xun
    Philippe Minh Tri Nguyen
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2017, 69 (11) : 20 - 20
  • [5] Threats to the soil microbiome from nanomaterials: A global meta and machine-learning analysis
    Chen, Sensen
    Teng, Ying
    Luo, Yongming
    Kuramae, Eiko
    Ren, Wenjie
    SOIL BIOLOGY & BIOCHEMISTRY, 2024, 188
  • [6] Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights
    Pasolli, Edoardo
    Duy Tin Truong
    Malik, Faizan
    Waldron, Levi
    Segata, Nicola
    PLOS COMPUTATIONAL BIOLOGY, 2016, 12 (07)
  • [7] Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis
    Devon Watts
    Rafaela Fernandes Pulice
    Jim Reilly
    Andre R. Brunoni
    Flávio Kapczinski
    Ives Cavalcante Passos
    Translational Psychiatry, 12
  • [8] Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis
    Watts, Devon
    Pulice, Rafaela Fernandes
    Reilly, Jim
    Brunoni, Andre R.
    Kapczinski, Flavio
    Passos, Ives Cavalcante
    TRANSLATIONAL PSYCHIATRY, 2022, 12 (01)
  • [9] Predicting the Role of the Human Gut Microbiome in Constipation Using Machine-Learning Methods: A Meta-Analysis
    Chen, Yutao
    Wu, Tong
    Lu, Wenwei
    Yuan, Weiwei
    Pan, Mingluo
    Lee, Yuan-Kun
    Zhao, Jianxin
    Zhang, Hao
    Chen, Wei
    Zhu, Jinlin
    Wang, Hongchao
    MICROORGANISMS, 2021, 9 (10)
  • [10] Co-exposure to microplastics and soil pollutants significantly exacerbates toxicity to crops: Insights from a global meta and machine-learning analysis
    Wang, Yunsheng
    Feng, Zerui
    Ghani, Muhammad Imran
    Wang, Qiran
    Zeng, Lina
    Yang, Xuqin
    Zhang, Xin
    Chen, Cai
    Li, Shule
    Cao, Pengxi
    Chen, Xiaoyulong
    Cernava, Tomislav
    Science of the Total Environment, 2024, 954
12345