| Autor: |
Zhitong Liu, Jinshan Huang, Junyu Huang, Renbo Luo, Zhuowen Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Applied Sciences, Vol 14, Iss 23, p 10908 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app142310908 |
| Popis: |
This study innovatively employs drones equipped with air quality sensors to collect three-dimensional air quality data in a campus microenvironment. Data are accurately corrected using a BP neural network, and a cubic model is constructed using three-dimensional interpolation. Combining photogrammetry technology, this study analyzes air quality patterns, finding significant differences from macro trends. Construction activities and large electronic experimental equipment significantly increase PM2.5 levels in the air. In rainy weather, the respiration of vegetation is enhanced, leading to higher CO2 concentrations, while water bodies exhibit higher temperatures in rainy weather due to their high specific heat capacity. This research not only provides a new perspective for microenvironment air quality monitoring but also offers a scientific basis for future air quality monitoring and management. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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