Chen, Jie; Wu, Zhijun; Wu, Guangming; Gong, Xianda; Wang, Feng; Chen, Jingchuan; Shi, Guo Liang; Hu, Min; Cong, Zhiyuan (2020): Source apportionment analysis from the Tibetan Plateau [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.923855, In: Chen, J et al. (2020): Ice-Nucleating Particle Concentrations and Sources in Rainwater over the Third Pole, Tibetan Plateau [dataset bundled publication]. PANGAEA, https://doi.org/10.1594/PANGAEA.923856
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Published: 2020-10-13 • DOI registered: 2020-11-13
Abstract:
This data gives the contributions of different sources (Marine and salt-lake, dust, biomass burning and long-range transport anthropogenic pollutants) to chemical components measured in rainwater resulted from the Positive Matrix Factorization Model developed by Environmental Protection Agency (EPA-PMF).
Related to:
Chen, J; Wu, Z J; Wu, G M; Gong, X D; Wang, F; Chen, J C; Shi, G L; Hu, M; Cong, Z Y (2021): Ice-Nucleating Particle Concentrations and Sources in Rainwater Over the Third Pole, Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 126(9), e2020JD033864, https://doi.org/10.1029/2020JD033864
Coverage:
Latitude: 30.731990 * Longitude: 90.685710
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Sample ID | Sample ID | Gong, Xianda | |||
| 2 | Date/time start | Date/time start | Gong, Xianda | |||
| 3 | Date/time end | Date/time end | Gong, Xianda | |||
| 4 | Components, chemical | Comp chem | µg/l | Gong, Xianda | Positive Matrix Factorization Model | Dust |
| 5 | Components, chemical | Comp chem | µg/l | Gong, Xianda | Positive Matrix Factorization Model | Marine and salt-lake |
| 6 | Components, chemical | Comp chem | µg/l | Gong, Xianda | Positive Matrix Factorization Model | Long range transport anthropogenic emssion |
| 7 | Components, chemical | Comp chem | µg/l | Gong, Xianda | Positive Matrix Factorization Model | Biomass burning |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Size:
238 data points