Aerosol optical and radiative properties and their environmental effects in China: A review

H Che, X **a, H Zhao, L Li, K Gui, Y Zheng, J Song… - Earth-Science …, 2024 - Elsevier
Aerosols are important atmospheric constituents with significant impacts on both regional air
quality and the global climate and environment. Aerosol effects on radiation, clouds and …

A systematic review of the physical health impacts from non-occupational exposure to wildfire smoke

JC Liu, G Pereira, SA Uhl, MA Bravo, ML Bell - Environmental research, 2015 - Elsevier
Background Climate change is likely to increase the threat of wildfires, and little is known
about how wildfires affect health in exposed communities. A better understanding of the …

Estimating 1-km-resolution PM2. 5 concentrations across China using the space-time random forest approach

J Wei, W Huang, Z Li, W Xue, Y Peng, L Sun… - Remote Sensing of …, 2019 - Elsevier
Abstract Fine particulate matter (PM 2.5) is closely related to the atmospheric environment
and human life. Satellite-based aerosol optical depth (AOD) products have been widely …

A machine learning method to estimate PM2. 5 concentrations across China with remote sensing, meteorological and land use information

G Chen, S Li, LD Knibbs, NAS Hamm, W Cao… - Science of the Total …, 2018 - Elsevier
Background Machine learning algorithms have very high predictive ability. However, no
study has used machine learning to estimate historical concentrations of PM 2.5 (particulate …

Estimating PM2.5 Concentrations in the Conterminous United States Using the Random Forest Approach

X Hu, JH Belle, X Meng, A Wildani… - … science & technology, 2017 - ACS Publications
To estimate PM2. 5 concentrations, many parametric regression models have been
developed, while nonparametric machine learning algorithms are used less often and …

Spatiotemporal analysis of haze in Bei**g based on the multi-convolution model

L Yin, L Wang, W Huang, S Liu, B Yang, W Zheng - Atmosphere, 2021 - mdpi.com
As a kind of air pollution, haze has complex temporal and spatial characteristics. From the
perspective of time, haze has different causes and levels of pollution in different seasons …

[HTML][HTML] Machine learning in geosciences and remote sensing

DJ Lary, AH Alavi, AH Gandomi, AL Walker - Geoscience Frontiers, 2016 - Elsevier
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a
subdivision of artificial intelligence based on the biological learning process. The ML …

COVID-19 pandemic persuaded lockdown effects on environment over stone quarrying and crushing areas

I Mandal, S Pal - Science of the Total Environment, 2020 - Elsevier
Stone quarrying and crushing spits huge stone dust to the environment and causes threats
to ecosystem components as well as human health. Imposing emergency lockdown to stop …

Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach

T Li, H Shen, Q Yuan, X Zhang… - Geophysical Research …, 2017 - Wiley Online Library
Fusing satellite observations and station measurements to estimate ground‐level PM2. 5 is
promising for monitoring PM2. 5 pollution. A geo‐intelligent approach, which incorporates …

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China, 2004–2013

Z Ma, X Hu, AM Sayer, R Levy, Q Zhang… - Environmental …, 2016 - ehp.niehs.nih.gov
Background Three decades of rapid economic development is causing severe and
widespread PM2. 5 (particulate matter≤ 2.5 μm) pollution in China. However, research on …