GlobalHighPM₂.₅ (2018)
Authors/Creators
-
1.
Peking University
-
2.
University of Maryland, College Park
Description
Here is the first big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) global ground-level PM2.5 dataset over land for the year 2018. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.91 and a root-mean-square error (RMSE) of 9.20 µg m-3 on a daily basis.
If you use the GlobalHighPM2.5 dataset in your scientific research, please cite the following reference (Wei et al., NC, 2023):
-
Wei, J., Li, Z., Lyapustin, A., Wang, J., Dubovik, O., Schwartz, J., Sun, L., Li, C., Liu, S., and Zhu, T. First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact. Nature Communications, 2023, 14, 8349. https://doi.org/10.1038/s41467-023-43862-3
Notes
Note that the data are recorded in UTC time (i.e., GMT+0).
This dataset is continuously updated. If you require additional data for related scientific research, please contact us (jingwei@pku.edu.cn or weijing.rs@gmail.com).
Files
GHAP_Dataset_Cover.png
Files
(36.9 GB)
| Name | Size | |
|---|---|---|
|
md5:20bb86606d198ea8668ab76c9e651c56
|
1.5 MB | Preview Download |
|
md5:5f4f47d8960c0fc933785caefc192675
|
3.0 GB | Preview Download |
|
md5:ead035fe480305173f36d3e69662037b
|
2.8 GB | Preview Download |
|
md5:e851458d17ca6e0ae8707ab65e24db7b
|
3.0 GB | Preview Download |
|
md5:4ef6804fc920938f882374c4d697e88b
|
3.0 GB | Preview Download |
|
md5:257cf5fde60a055e0e2640d93e8cc1df
|
3.1 GB | Preview Download |
|
md5:95a2baf3ef1a4ca4276abd3eb196a091
|
3.0 GB | Preview Download |
|
md5:678c7f7e21caa604e44ac51895037db8
|
3.2 GB | Preview Download |
|
md5:7d0e02dd4f40e43206d8cc32db266b09
|
3.1 GB | Preview Download |
|
md5:b065c216561841a7919afb3c0b10af8f
|
2.9 GB | Preview Download |
|
md5:85485a7b5a3f5976809b647977b115de
|
2.9 GB | Preview Download |
|
md5:aad44ba50c29a9d5e5c61dffa5a80456
|
2.8 GB | Preview Download |
|
md5:a963b4398be76febfe31445d0949f3cc
|
3.0 GB | Preview Download |
|
md5:4bf5dae77515c5fb7ba495aad01b02bb
|
81.9 MB | Download |
|
md5:7e1246bf8cce63e660f25bfe339a3ba1
|
81.0 MB | Download |
|
md5:71ed0ebe01ebdd7015103e6c1ee78d47
|
80.7 MB | Download |
|
md5:43b31b835574355e9ce99c8ca720974c
|
80.3 MB | Download |
|
md5:f74c134a54310e301e74d63b6ab03579
|
85.2 MB | Download |
|
md5:9f8c15159c96038d62caf7bd097241b4
|
81.9 MB | Download |
|
md5:e2202cacdc9ef147092d50101d687532
|
83.8 MB | Download |
|
md5:75e39972c09937aa3f9125063b39f897
|
81.5 MB | Download |
|
md5:92511ef0b4932372e1cb9763fdc9f92a
|
77.1 MB | Download |
|
md5:35a8eec242bb0544da19d66807372665
|
76.3 MB | Download |
|
md5:6f0420ea7630a7120529a960ec8c8acf
|
77.6 MB | Download |
|
md5:e24ef03eb63ed7873bb04f1f486abe98
|
79.1 MB | Download |
|
md5:c9375ac683305453a2b2fb1da327b940
|
68.6 MB | Download |
|
md5:b197fd78fb3a48f40360931f200d43df
|
3.3 kB | Preview Download |
|
md5:df77274e5ad9e67889165b663ea9f621
|
33.9 MB | Preview Download |
Additional details
References
- Wei, J., Li, Z., Lyapustin, A., Wang, J., Dubovik, O., Schwartz, J., Sun, L., Li, C., Liu, S., and Zhu, T. First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact. Nature Communications, 2023, 14, 8349. https://doi.org/10.1038/s41467-023-43862-3