Numerical prediction of aerosol particle properties has become an important activity at many
research and operational weather centers. This development is due to growing interest from …

The accurate measurements of natural and anthropogenic aerosol particulate matter (PM) is
important in managing both environmental and health risks; however, limited monitoring in …

The trend of air pollutant concentrations in the Seoul Metropolitan Area (SMA)—particularly
the city of Seoul—in the Republic of Korea, is shown and analyzed along with applied …

Aerosol optical properties are among the most fundamental parameters in atmospheric
environmental studies. Satellite aerosols retrievals that are based on deep learning or …

Precise and timely lightning nowcasting is still a great challenge for meteorologists. In this
study, a new semantic segmentation deep learning network for cloud-to-ground (CG) …

Monitoring fine particulate matter with diameters of less than 2.5 μm (PM2. 5) is a critical
endeavor in the Beijing–Tianjin–Hebei (BTH) region, which is one of the most polluted areas …

Satellite-based aerosol optical depth (AOD) has gained popularity as a powerful data source
for calibrating aerosol models and correcting model errors through data assimilation …

The continuous distributions of PM 2.5 concentrations and predictor variables in the
surrounding regions influence the PM 2.5 concentrations in the prediction positions notably …

High temporal resolution (every 10 min) aerosol observations are rarely provided by satellite
sensors. The Advanced Himawari Imager (AHI) aboard Himawari-8 can provide aerosol …

High concentrations of particulate matter with diameter of< 2.5 μm (PM2. 5) demonstrate
severe effects on human health, especially in the metropolitan agglomerations of China …