Global navigation satellite system precipitable water vapour combined with other atmospheric factors to predict the short-term change of PM2.5 mass concentration

A novel approach using Global Navigation Satellite System (GNSS) precipitable water vapour (PWV) data, combined with other atmospheric factors, can effectively predict short-term changes in PM2.5 mass concentration, a key component of haze pollution. The study found that by selecting periods with stable weather conditions and applying wavelet decomposition to filter high-frequency noise, the correlation between GNSS PWV and PM2.5 improved significantly, reaching up to 0.73. This method successfully established a multiple-regression model using independent variables such as NO2, relative humidity, wind speed, and other pollutants, demonstrating its potential for accurate haze weather forecasting. Conducted at the Temple of Heaven station in Beijing, this research highlights the utility of GNSS-derived data in environmental monitoring and pollution prediction.

Guo, M., Xia, P., Li, P., & Zhang, H. (2021). Global navigation satellite system precipitable water vapour combined with other atmospheric factors to predict the short-term change of PM2.5 mass concentration. Meteorologische Zeitschrift, 30(5), 429–444. https://doi.org/10.1127/metz/2021/1061