Machine learning-enhanced high-resolution exposure assessment of ultrafine particles
Abstract Ultrafine particles (UFPs) under 100 nm pose significant health risks inadequately addressed by traditional mass-based metrics. The WHO emphasizes particle number concentration (PNC) for assessing UFP exposure, but large-scale evaluations remain scarce. In this study, we developed a stackin...
Saved in:
Main Authors: | Yudie Jianyao, Hongyong Yuan, Guofeng Su, Jing Wang, Wenguo Weng, Xiaole Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-025-56581-8 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Characterizations of Size-segregated Ultrafine Particles in Diesel Exhaust
by: Jaehyun Lim, et al.
Published: (2020-12-01) -
A molecular toxicological study to explore potential health risks associated with ultrafine particle exposure in cold and humid indoor environments
by: Ziyu Shu, et al.
Published: (2025-01-01) -
Ultrafine Resveratrol Particles: Supercritical Antisolvent Preparation and Evaluation In Vitro and In Vivo
by: Kunlun Wang, et al.
Published: (2015-01-01) -
Seasonal investigation of ultrafine-particle organic composition in an eastern Amazonian rainforest
by: A. E. Thomas, et al.
Published: (2025-01-01) -
APPLICATION OF WASTES, CONTAINING ULTRAFINE AND NANOSIZED PARTICLES IN THE MODIFIER CONSUMPTION OF GRAY IRON
by: K. E. Baranowski, et al.
Published: (2013-09-01)