The comparison of AOD-based and non-AOD prediction models for daily PM2.5 estimation in Guangdong province, China with poor AOD coverage-Reference-Cited by-同舟云学术

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The comparison of AOD-based and non-AOD prediction models for daily PM2.5 estimation in Guangdong province, China with poor AOD coverage

Published:2021-04 Issue: Volume:195 Page:110735
ISSN:0013-9351
Container-title:Environmental Research
language:en
Short-container-title:Environmental Research

Author:

Chen Gongbo,Li Yingxin,Zhou Yun,Shi Chunxiang,Guo Yuming,Liu Yuewei

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Environmental Science,Biochemistry

Reference36 articles.

1. A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information;Chen;Sci. Total Environ.,2018

2. Is long-term exposure to air pollution associated with poor sleep quality in rural China?;Chen;Environ. Int.,2019

3. Urban air quality evaluations under two versions of the national ambient air quality standards of China;Chen;Atmos. Pollut. Res.,2016

4. Estimating PM2.5 concentrations based on non-linear exposure-lag-response associations with aerosol optical depth and meteorological measures;Chen;Atmos. Environ.,2018

5. Extreme gradient boosting model to estimate PM2.5 concentrations with missing-filled satellite data in China;Chen;Atmos. Environ.,2019

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3. Association of Air Quality Improvement and Frailty Progression: A National Study across China;Toxics;2024-06-27

4. Characterization of the major aerosol species over Egypt based on 10 years of CAMS reanalysis data;Atmospheric Pollution Research;2024-05

5. Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations;Geoscience Frontiers;2024-01

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