Prediction of developmental toxic effects of fine particulate matter (PM2.5) water-soluble components via machine learning through observation of PM2.5 from diverse urban areas-Reference-Cited by-同舟云学术

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Prediction of developmental toxic effects of fine particulate matter (PM2.5) water-soluble components via machine learning through observation of PM2.5 from diverse urban areas

Published:2024-10 Issue: Volume:946 Page:174027
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Fan Yang,Sun Nannan,Lv Shenchong,Jiang Hui,Zhang Ziqing,Wang Junjie,Xie Yiyi,Yue Xiaomin,Hu Baolan,Ju Bin,Yu Peilin

Funder

Republic of China Ministry of Science and Technology

National Natural Science Foundation of China

Zhejiang Province Natural Science Foundation

Publisher

Elsevier BV

Reference93 articles.

1. Acute effects of fine particulate matter constituents on mortality: a systematic review and meta-regression analysis;Achilleos;Environ. Int.,2017

2. Barium;Agneta,2022

3. Insights into elemental composition and sources of fine and coarse particulate matter in dense traffic areas in Toronto and Vancouver, Canada;Celo;Toxics,2021

4. Development of a prediction model for demolition waste generation using a random forest algorithm based on small datasets;Cha;Int. J. Environ. Res. Public Health,2020

5. Application of cell-based biological bioassays for health risk assessment of PM2.5 exposure in three megacities, China;Chen;Environ. Int.,2020

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