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

H Che, X ** large-scale and long-term PM2. 5 models from satellite data
Z Ma, S Dey, S Christopher, R Liu, J Bi, P Balyan… - Remote Sensing of …, 2022 - Elsevier
Research of PM 2.5 chronic health effects requires knowledge of large-scale and long-term
exposure that is not supported by newly established monitoring networks due to their sparse …

[HTML][HTML] An ensemble-based model of PM2. 5 concentration across the contiguous United States with high spatiotemporal resolution

Q Di, H Amini, L Shi, I Kloog, R Silvern, J Kelly… - Environment …, 2019 - Elsevier
Various approaches have been proposed to model PM 2.5 in the recent decade, with
satellite-derived aerosol optical depth, land-use variables, chemical transport model …

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 …

Aerosol and boundary-layer interactions and impact on air quality

Z Li, J Guo, A Ding, H Liao, J Liu, Y Sun… - National Science …, 2017 - academic.oup.com
Air quality is concerned with pollutants in both the gas phase and solid or liquid phases. The
latter are referred to as aerosols, which are multifaceted agents affecting air quality, weather …

[HTML][HTML] A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen …

J Chen, K de Hoogh, J Gulliver, B Hoffmann… - Environment …, 2019 - Elsevier
Empirical spatial air pollution models have been applied extensively to assess exposure in
epidemiological studies with increasingly sophisticated and complex statistical algorithms …

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 …

Separating emission and meteorological contribution to PM2.5 trends over East China during 2000–2018

Q **ao, Y Zheng, G Geng, C Chen… - Atmospheric …, 2021 - acp.copernicus.org
The contribution of meteorology and emissions to long-term PM 2.5 trends is critical for air
quality management but has not yet been fully analyzed. Here, we used a combination of …

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 …