326 / 2023-10-15 09:02:05

Ground-based GNSS CORS Network 3D High-precision Water Vapor Products to Monitor the Temporal and Spatial Variation of Short-term PM2.5 Concentration

GNSS Meteorology; Zenith Total Delay (ZTD); Precipitable Water Vapor (PWV); GNSS tropospheric tomography; Fine particulate matter (PM2.5)

With the improvement of the global navigation satellite system (GNSS) Continuously Operating Reference Stations (CORS), it can provide large-scale, low-cost, high temporal and spatial resolution, real-time and high-precision water vapor distribution information for disaster monitoring (rainstorm, typhoon, hail, haze, etc.), and then provides a new way to predict haze. In this study, taking the CORS network area of Jiaozuo City, Henan Province as the experimental area, the changes of water vapor on haze weather are detailed with the optimization algorithm of GNSS tropospheric tomography method.  

Firstly, the optimized algorithm is used to obtain high-precision three-dimensional (3D) tomographic water vapor products with the corresponding meteorological data and numerical weather forecast ERA5 data in the CORS network area of Jiaozuo, Henan Province from January 1 to March 31, July 1 to August 31 in 2019. Then, 3D GNSS high-precision water vapor products in conjunction with 2D products are used to monitor short-term haze weather (mainly PM_2.5). Taking the haze weather in the experimental area in January 2019 as an example, combined with the actual height of haze (mainly PM_2.5), the PM_2.5 concentration transfer process over the area is analyzed by using the changes of the water vapor density of 1-3 layers (756m), especially 1-2 layers (358m). This experimental process details the changes of PM_2.5 concentration at different locations and strengths, at the same time, the change of PM_2.5 concentration around each single GNSS station was also analyzed in this experiment. Finally, the experimental results show that the two-dimensional combined three-dimensional method can better refine the process of PM_2.5 concentration change. And this method plays an important role in predicting haze events more accurately in the future.