[HTML][HTML] Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives

Y Zhang, Z Li, K Bai, Y Wei, Y ** the mass concentration of near-surface atmospheric particulate matter (PM) using
satellite observations has become a popular research niche, leading to the development of …

Estimating ground-level particulate matter concentrations using satellite-based data: a review

M Shin, Y Kang, S Park, J Im, C Yoo… - GIScience & Remote …, 2020‏ - Taylor & Francis
Particulate matter (PM) is a widely used indicator of air quality. Satellite-derived aerosol
products such as aerosol optical depth (AOD) have been a useful source of data for ground …

A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2. 5

R Zhao, L Zhan, M Yao, L Yang - Sustainable Cities and Society, 2020‏ - Elsevier
This study develops an augmented geographically weighted regression (GWR) model to
analyze the spatial distribution of PM 2.5 concentrations through the incorporation of …

Dynamic assessment of PM2. 5 exposure and health risk using remote sensing and geo-spatial big data

Y Song, B Huang, Q He, B Chen, J Wei… - Environmental …, 2019‏ - Elsevier
In the past few decades, extensive epidemiological studies have focused on exploring the
adverse effects of PM 2.5 (particulate matters with aerodynamic diameters less than 2.5 μm) …

Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM2. 5

Y Xu, HC Ho, MS Wong, C Deng, Y Shi, TC Chan… - Environmental …, 2018‏ - Elsevier
Abstract Fine particulate matter (PM 2.5) has been recognized as a key air pollutant that can
influence population health risk, especially during extreme cases such as wildfires. Previous …

Evaluation of different machine learning approaches and aerosol optical depth in PM2. 5 prediction

H Karimian, Y Li, Y Chen, Z Wang - Environmental Research, 2023‏ - Elsevier
Abstract Atmospheric Aerosol Optical Depth (AOD), derived from polar-orbiting satellites,
has shown potential in PM 2.5 predictions. However, this important source of data suffers …

Exploring common factors influencing PM2. 5 and O3 concentrations in the Pearl River Delta: Tradeoffs and synergies

J Wu, Y Wang, J Liang, F Yao - Environmental pollution, 2021‏ - Elsevier
Particulate matter with an aerodynamic equivalent dimeter less than 2.5 μm (PM 2.5) and
ozone (O 3) are major air pollutants, with coupled and complex relationships. The control of …

[HTML][HTML] Application of land use regression model to assess outdoor air pollution exposure: A review

WNFW Azmi, TR Pillai, MT Latif, S Koshy… - Environmental …, 2023‏ - Elsevier
In this study, we reviewed the application of land use regression (LUR) models in various
regions worldwide to provide insight into approaches utilized for LUR models. We also …

Effectiveness and heterogeneity evaluation of regional collaborative governance on haze pollution control: Evidence from 284 prefecture-level cities in China

Y Chang, P Hu, Y Huang, Z Duan - Sustainable Cities and Society, 2022‏ - Elsevier
The impact of collaborative governance on the reduction of haze pollution has always been
a hotly debated topic in environmental protection research. First, the present study aims to …

A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5

L Li - Remote Sensing, 2020‏ - mdpi.com
Accurate estimation of fine particulate matter with diameter≤ 2.5 μm (PM2. 5) at a high
spatiotemporal resolution is crucial for the evaluation of its health effects. Previous studies …