Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data

Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data

Introduction: Traditional methods to estimate exposure to PM2.5 (particulate matter with less than 2.5 µm in diameter) have typically relied on limited regulatory monitors and do not consider human mobility and travel. However, the limited spatial coverage of regulatory monitors and the lack of cons...

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Bibliographic Details
Main Authors: Manzhu Yu, Shiyan Zhang, Kai Zhang, Junjun Yin, Matthew Varela, Jiheng Miao
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Environmental Science
Subjects:
machine learning
land use regression
human mobility
low-cost sensors
PM2.5
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2023.1223160/full

Internet

https://www.frontiersin.org/articles/10.3389/fenvs.2023.1223160/full

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