Quantifying the contribution of environmental variables to cyclists’ exposure to PM2.5 using machine learning techniques

Quantifying the contribution of environmental variables to cyclists’ exposure to PM2.5 using machine learning techniques

Cyclists are particularly vulnerable to travel-related exposure to air pollution. Understanding the factors that increase exposure is crucial for promoting healthier urban environments. Machine learning models have successfully predicted air pollutant concentrations, but they tend to be less interpr...

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Bibliographic Details
Main Authors: Martín Rodríguez Núñez, Iván Tavera Busso, Hebe Alejandra Carreras
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Heliyon
Subjects:
PM2.5
Cyclist
Machine learning
Exposure models
Urban environments
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024007552

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024007552

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