A three-dimensional LUR framework for PM2.5 exposure assessment based on mobile unmanned aerial vehicle monitoring-Reference-Cited by-同舟云学术

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A three-dimensional LUR framework for PM2.5 exposure assessment based on mobile unmanned aerial vehicle monitoring

Published:2022-05 Issue: Volume:301 Page:118997
ISSN:0269-7491
Container-title:Environmental Pollution
language:en
Short-container-title:Environmental Pollution

Author:

Xu Xiangyu,Qin Ning,Zhao Wenjing,Tian Qi,Si Qi,Wu Weiqi,Iskander Nursiya,Yang Zhenchun^ORCID,Zhang Yawei,Duan Xiaoli^ORCID

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Toxicology,General Medicine

Reference66 articles.

1. Land use regression models for crustal and traffic-related PM2.5 constituents in four areas of the SAPALDIA study;Aguilera;Environ. Res.,2015

2. Spatial-temporal variation characteristics of air pollution and apportionment of contributions by different sources in Shanxi province of China;Bai;Atmos. Environ.,2021

3. Natural-cause mortality and long-term exposure to particle components: an analysis of 19 European cohorts within the multi-center ESCAPE project;Beelen;Environ. Health Perspect.,2015

4. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter;Burnett;Proc. Natl. Acad. Sci. U. S. A.,2018

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1. Integrating Doppler LiDAR and machine learning into land-use regression model for assessing contribution of vertical atmospheric processes to urban PM2.5 pollution;Science of The Total Environment;2024-11

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3. Enhancing spatial modeling and risk mapping of six air pollutants using synthetic data integration with convolutional neural networks;Frontiers in Environmental Science;2024-07-09

4. Development of land use regression models to characterise spatial patterns of particulate matter and ozone in urban areas of Lanzhou;Urban Climate;2024-05

5. A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023;Environment International;2024-01

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