| Autor: |
Shao-Wei Wu, Huei Huang, Shu-Fen Tsai, Chao-Yuan Lin |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Ecological Indicators, Vol 154, Iss , Pp 110864- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1470-160X |
| DOI: |
10.1016/j.ecolind.2023.110864 |
| Popis: |
This study introduces a risk model that utilizes the ventilation index (VI), Temperature Vegetation Dryness Index (TVDI), and coefficient of variation (CV) of soil moisture content to identify dust supply hotspots in the exposed riverbed of Taiwan's Zhuoshui River during the dry season. The research demonstrates a positive correlation between PM10 concentration and high-risk locations, achieving an 80% interpretation rate. The average bare riverbed area is approximately 3,500 ha, with the M2 area being a significant contributor to PM10 (covering around 1,186 ha). The dust source hotspot (high CV in soil moisture) spans about 141 ha, accounting for approximately 34% and 4.02% of the bare land, respectively. To effectively mitigate the impact of river dust on nearby residents' health and the environment, employing unmanned aerial vehicles (UAVs) for precise prevention and management is recommended. This study successfully integrates theory and practice, introducing a conceptual model that combines risk analysis with environmental indicators to identify potential river dust emission areas. The model's adaptability allows for its application and expansion to other regions and internationally, making significant contributions to dust risk management strategies. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Full Text from ScienceDirect