Evaluation of four meteorological reanalysis datasets for satellite-based PM2. 5 retrieval over China

C Zuo, J Chen, Y Zhang, Y Jiang, M Liu, H Liu… - Atmospheric …, 2023 - Elsevier
Meteorological reanalysis data is widely used for satellite-based retrieval of fine particulate
matter (PM 2.5); however, selecting appropriate data for specific regional applications …

Full-coverage estimation of PM2. 5 in the Bei**g-Tian**-Hebei region by using a two-stage model

Q Zeng, Y Li, J Tao, M Fan, L Chen, L Wang… - Atmospheric …, 2023 - Elsevier
The accurate estimation of fine particulate matter (PM 2.5) is significant for both
environmental protection and health assessment. However, the sparsity of monitoring …

Spatial weighting EMD-LSTM based approach for short-term PM2. 5 prediction research

Q Yu, H Yuan, Z Liu, G Xu - Atmospheric Pollution Research, 2024 - Elsevier
Given the significant health and environmental risks posed by atmospheric PM 2. 5 pollution,
accurately predicting its concentration changes is especially important. Current models fall …

Forecasting hourly PM2. 5 concentration with an optimized LSTM model

HD Tran, HY Huang, JY Yu, SH Wang - Atmospheric Environment, 2023 - Elsevier
Abstract Machine learning has become a powerful tool in air quality assessment which can
provide timely and predictable information, alert the public, and take timely measures to …

A hybrid PM2. 5 interval concentration prediction framework based on multi-factor interval decomposition reconstruction strategy and attention mechanism

J Zhu, L Niu, P Zheng, H Chen, J Liu - Atmospheric Environment, 2024 - Elsevier
With the acceleration of urban modernization, the temporal variability in air pollution has
become increasingly significant. Predicting average daily pollutant concentrations no longer …

Evaluation of different machine learning approaches for predicting high concentration episodes of ground-level ozone: A case study in Catalonia, Spain

DJ Vicente, F Salazar, SR López-Chacón… - Atmospheric Pollution …, 2024 - Elsevier
Abstract Ground-level ozone (O 3) is a pollutant with a great impact on human health and
the environment. As a secondary air contaminant of photochemical origin, those areas with …

Unveiling global land fine-and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data

N Luo, Y Zhang, Y Jiang, C Zuo, J Chen, W Zhao… - Environmental …, 2024 - Elsevier
Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their
impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode …

Estimating Daily Concentrations of Near-Surface CO, NO2, and O3 Simultaneously Over China Based on Spatiotemporal Multi-Task Transformer Model

Q Zeng, L Wang, H Zhu, S Liu, C Wang, L Chen… - Atmospheric …, 2024 - Elsevier
Accurate and efficient estimation of near-surface air pollutant concentrations holds
significant practical importance. Current models for estimating near-surface concentrations …

Diurnal hourly near-surface ozone concentration derived from geostationary satellite in China

Y Zhang, L Zang, J Song, J Yang, Y Yang… - Science of The Total …, 2024 - Elsevier
Near-surface O 3 is a harmful atmospheric pollutant and a key component of urban
photochemical pollution. The availability of satellite ozone concentration products is …

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Z Mushtaq, P Bangotra, AS Gautam, M Sharma… - Environmental …, 2024 - Springer
Air pollution is growing at alarming rates on regional and global levels, with significant
consequences for human health, ecosystems, and change in climatic conditions. The …