EGU22-7031, updated on 28 Mar 2022
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Aeolian River Dust in Central and Southern Taiwan Rivers: Spatial-Temporal Characterization and Public Health Implication

Chun-Kuang Chen1 and Christina W. Tsai2
Chun-Kuang Chen and Christina W. Tsai
  • 1National Taiwan University, Civil Engineering, Taiwan (
  • 2National Taiwan University, Civil Engineering, Taiwan (

Aeolian river dust has been one of the significant local air quality concerns in central and southern Taiwan for a long time. Aeolian river dust is not only affecting local visibility and air quality but also causing adverse health effects. It has been demonstrated that long-term exposure to PM10, even the low-level concentrations, may induce adverse health effects such as pulmonary, respiratory diseases and even death. Moreover, Taiwan Environmental Protection Administration (EPA) indicated nine river-dust events occurring in western Taiwan between 1994 and 2017. However, due to global climate change, the frequency and intensity of extreme events, such as droughts, are increasing significantly, which may contribute to the occurrence of river dust events. Furthermore, in Taiwan, most studies have only focused on the Asian dust storms transported from China, while the spatial-temporal characterization and health implication of river dust events is still not widely understood. Therefore, in this study, to explore the causes and effects of river dust in Taiwan, we mainly analyze the PM10 concentration, relevant hydro-meteorological factors (temperature, precipitation, relative humidity, wind speed, and river water level), drought events, and medical data of respiratory diseases by using time-frequency analysis. Time-frequency analysis is a tool that allows us to investigate the characteristic time scale and energy distribution of the signals since the signals are most likely to be both nonlinear and nonstationary, which cannot be adaptively analyzed by traditional data-analysis methods such as Fourier transform. Thus, the method of improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is introduced in this study to adaptively decompose hydro-meteorological time series and medical data into their intrinsic mode functions (IMFs) and a trend. Moreover, the time-dependent intrinsic correlation method (TDIC) is introduced to calculate the running correlation coefficient between two IMFs with the sliding window in different time scales. After the ICEEMDAN and TDIC work, the correlation between river dust and relevant hydro-meteorological factors can be identified. The impact of frequency and intensity of droughts on river dust events in Taiwan can be explored, and then the association between respiratory diseases and river dust can be determined. It is hoped that the results of this study can assist in promoting the related air pollution policies in protecting residents and reducing the risk of disaster to people, particularly during droughts when most of the river dust events prevail.

How to cite: Chen, C.-K. and Tsai, C. W.: Aeolian River Dust in Central and Southern Taiwan Rivers: Spatial-Temporal Characterization and Public Health Implication, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7031,, 2022.