[HTML][HTML] A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective …

X Ma, B Zou, J Deng, J Gao, I Longley, S Xiao… - Environment …, 2024 - Elsevier
Land use regression (LUR) models are widely used in epidemiological and environmental
studies to estimate humans' exposure to air pollution within urban areas. However, the early …

Stereoscopic hyperspectral remote sensing of the atmospheric environment: Innovation and prospects

C Liu, C Xing, Q Hu, S Wang, S Zhao, M Gao - Earth-Science Reviews, 2022 - Elsevier
Traditional ground-based air sampling measurements of air quality have blind monitoring
areas in the junctions between provinces, cities and urban and rural areas, and they lack the …

The High-Resolution Rapid Refresh (HRRR): An hourly updating convection-allowing forecast model. Part I: Motivation and system description

DC Dowell, CR Alexander, EP James… - Weather and …, 2022 - journals.ametsoc.org
Abstract The High-Resolution Rapid Refresh (HRRR) is a convection-allowing
implementation of the Advanced Research version of the Weather Research and …

[HTML][HTML] Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign

B Guo, H Wu, L Pei, X Zhu, D Zhang, Y Wang… - Environment …, 2022 - Elsevier
Abstract Surface ozone (O 3), one of the harmful air pollutants, generated significantly
negative effects on human health and plants. Existing O 3 datasets with coarse …

PM2. 5 air pollution prediction through deep learning using meteorological, vehicular, and emission data: A case study of New Delhi, India

D Shakya, V Deshpande, MK Goyal… - Journal of Cleaner …, 2023 - Elsevier
Abstract Particulate matter (PM 2.5) concentration is an air pollutant that can lead to serious
health complications in humans. The detection of this air pollutant is essential so that …

Investigating and mapping day-night urban heat island and its driving factors using Sentinel/MODIS data and Google Earth Engine. Case study: greater Cairo, Egypt

RM Abou Samra - Urban Climate, 2023 - Elsevier
Urban heat islands (UHI) represent one of the substantial human-induced challenges
endangering urban livelihoods. UHI and climate change have significant interactions …

Ground-level ozone estimation based on geo-intelligent machine learning by fusing in-situ observations, remote sensing data, and model simulation data

J Chen, H Shen, X Li, T Li, Y Wei - International Journal of Applied Earth …, 2022 - Elsevier
In recent years, near-surface ozone (O 3) pollution has been increasing, seriously
endangering both the ecological environment and human health. Accurately monitoring …

Explainable and spatial dependence deep learning model for satellite-based O3 monitoring in China

N Luo, Z Zang, C Yin, M Liu, Y Jiang, C Zuo… - Atmospheric …, 2022 - Elsevier
Environmental exposure to surface ozone (O 3) has become a major public health concern.
To accurately estimate the spatial-coverage O 3 from sparse ground-truth data, we here …

A review of machine learning for modeling air quality: Overlooked but important issues

D Tang, Y Zhan, F Yang - Atmospheric Research, 2024 - Elsevier
Abstract Machine learning models based on satellite remote sensing have gained
widespread use in estimating ground-level air pollutant concentrations, which overcome the …

Estimated Impacts of Prescribed Fires on Air Quality and Premature Deaths in Georgia and Surrounding Areas in the US, 2015–2020

KJ Maji, Z Li, A Vaidyanathan, Y Hu… - Environmental …, 2024 - ACS Publications
Smoke from wildfires poses a substantial threat to health in communities near and far. To
mitigate the extent and potential damage of wildfires, prescribed burning techniques are …