Published August 18, 2024 | Version 2 (2000-2023)
Dataset Open

ChinaHighO3: Big Data Seamless 1 km Ground-level MDA8 O3 Dataset for China (2000-Present)

  • 1. ROR icon University of Maryland, College Park

Description

ChinaHighO3 is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. 

This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level maximum 8-hour average (MDA8) O3 dataset in China from 2000 to the present. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.89, a root-mean-square error (RMSE) of 15.77 µg m-3, and a mean absolute error (MAE) of 10.48 µg m-3 on a daily basis.

If you use the ChinaHighO3 dataset for related scientific research, please cite the corresponding references (Wei et al., RSE, 2022; Yang et al., RSE, 2025):

More CHAP datasets of different air pollutants can be found at: https://weijing-rs.github.io/product.html

Notes

Note that the data are recorded in local time (i.e., Beijing time: GMT+8), and measured at the standard condition (i.e., 273 K and 1013 hPa). The concentrations can be converted to the room condition (i.e., 298 K and 1013 hPa) by dividing by a factor of 1.09375 (MEE, 2018).

This dataset is continuously updated, and if you want to apply for more data or have any questions, please contact me (Email: weijing_rs@163.com; weijing@umd.edu).

Files

Wei_et_al-RSE-2022.pdf

Files (81.6 GB)

Name Size Download all
md5:0196e36468b406aa9ae0735b6646825c
3.3 GB Preview Download
md5:f6c3e5a4d2a002e7d54508635fae4404
3.3 GB Preview Download
md5:cd8d34d6ab3e346e3b94f03cb92fbde5
3.3 GB Preview Download
md5:d9e09122c9fd4651983cb385f17b3ece
3.4 GB Preview Download
md5:50a4ab1d93473b777e54df671a70c1be
3.4 GB Preview Download
md5:0d4cc1d2c0c29d4e5c52470922767dc9
3.4 GB Preview Download
md5:d1eda17d7ec421136c9426082ae47b3a
3.4 GB Preview Download
md5:112692060e24bf0e5eea9719ee462b28
3.4 GB Preview Download
md5:37c9cc20888c7246837b69fb5c707cd5
3.4 GB Preview Download
md5:eb6abb94ca41038520d1c4f4b3d0af28
3.4 GB Preview Download
md5:aa565a6c3f4ce31a6d2de01e1c1bad8c
3.4 GB Preview Download
md5:79df06a53784e444a2235d9eec07a33b
3.4 GB Preview Download
md5:31beadaedf70d702a85837af2c67a970
3.4 GB Preview Download
md5:09fcdac5ad58578b169b116b5dc55b74
3.4 GB Preview Download
md5:0ea0a11d36e8fba3c70401619e46e4c3
3.4 GB Preview Download
md5:efc433b563f57963b48dea0f4a312053
3.4 GB Preview Download
md5:7aa59b84c1ecc8e2dd704d3652d2b210
3.3 GB Preview Download
md5:6ae743e26120b0ef17ecef4583c303cf
3.2 GB Preview Download
md5:1c844ca554ea159a6ea3a6eec719ee2c
3.2 GB Preview Download
md5:4a982cccd7953166a5dc0dfebf6c0ecd
3.2 GB Preview Download
md5:2e5690ed0e847c88c5ca208e94fc32be
3.1 GB Preview Download
md5:a182d1307a4c304b5a45586e7f071f26
3.1 GB Preview Download
md5:e862fd7e00df648e142d3b03796cede3
3.1 GB Preview Download
md5:5fe16607a614b9a6cdcccb7cc6d47838
3.0 GB Preview Download
md5:eccf7c3d5e7969ea670475988b8e6837
92.7 MB Preview Download
md5:9c0c3b21a5a0a705cee1c46552d70c54
93.3 MB Preview Download
md5:03091738253556f6d419e95ee2f7a8b1
93.2 MB Preview Download
md5:258438e666dea2de6c29b459f42ba3a8
94.2 MB Preview Download
md5:c703def5a0960d953e9d5c62182f3bd5
94.5 MB Preview Download
md5:ee507083a2e104f043d94449281848f2
94.6 MB Preview Download
md5:78bddc531aa51f89ae5d89622bf4e495
95.1 MB Preview Download
md5:400f920e7085d7e5dd845a4f81a823cc
95.2 MB Preview Download
md5:238694309ec3ee804a6fc06b8870fd49
94.7 MB Preview Download
md5:2dd350b1cbe79668dff876b33c73f613
95.0 MB Preview Download
md5:ce6860a2db471acda4f14ae8859e9161
94.5 MB Preview Download
md5:d641f32bdec84e0a8e4e90c99c6fcf75
95.3 MB Preview Download
md5:536aa70ac1b1519b00487e6d0228e1a4
95.2 MB Preview Download
md5:4767c3e96f3afa3823e19c4124d67c34
95.7 MB Preview Download
md5:3cceb9224523d939e8e5dd0d3d651613
96.2 MB Preview Download
md5:3ea1ed3cfa17dbe64fa70088d5308917
96.9 MB Preview Download
md5:c93d921815d786042b928808af265650
94.0 MB Preview Download
md5:e86c156bb7ce21310f6f07734346ee7d
88.0 MB Preview Download
md5:55cdcea0aad62cb253c57ab2740e9604
85.9 MB Preview Download
md5:ce6111ef6b59e8cf58b53f1a6396344e
87.4 MB Preview Download
md5:0baed35c975e87ad92dea8ca5e5e372c
83.6 MB Preview Download
md5:a0024cd2a999614ab583305c87d7c115
81.1 MB Preview Download
md5:c4136543765aacceefef8c69b9f6af7b
81.7 MB Preview Download
md5:24cb301c03ebd305bd5fc0312fec9af2
75.3 MB Preview Download
md5:c1a09ee15bb041d62a8d98d44498aeb1
7.3 MB Download
md5:330c1a4f8dfb3efe1b27ddf30d2910f3
7.3 MB Download
md5:333f02bded150e29d9413f7d69db1535
7.3 MB Download
md5:123b58d781f8c583d8771eaf24afece6
7.5 MB Download
md5:2e227510be89cb13ee07a871925c1fba
7.5 MB Download
md5:08ee504e2b4fb6dceebda85f988c7889
7.5 MB Download
md5:70f991baaf46be75b3adf510d74685c9
7.5 MB Download
md5:06e6fc4b53c658cf95e8138aa28afb47
7.5 MB Download
md5:b47f2db8a90f75c50a95f40aec760bd4
7.5 MB Download
md5:92dee97fc2e9f9953442f0ebd740edd0
7.5 MB Download
md5:38d93a68c365e49a5a60c8c3fd5e23c1
7.5 MB Download
md5:31b7f062270bc838e31e235f0bf0d2ca
7.5 MB Download
md5:0cab69c8432c631088a19fc9ca8c0d4d
7.6 MB Download
md5:b6e271dc5ee7bd4ff484e6548b0e387e
7.6 MB Download
md5:d885a2f2f7166f61142183f532603dd9
7.7 MB Download
md5:40e4eb07813ecfacee42e7ed7d64be14
7.7 MB Download
md5:9142e86a8179d2c8a5b30bc888d0a033
7.4 MB Download
md5:c285bcdc58e1767948bccc4eb41a6a49
6.7 MB Download
md5:ba43cb30e578a312a4715ce9eb1e7232
6.4 MB Download
md5:56390c9c1259dd85cb18e54da6ab66d2
6.6 MB Download
md5:5b7a617082f1c89df18581ac366b60d7
6.3 MB Download
md5:f22893c73f7108e478b0d1dc4245bc5a
5.9 MB Download
md5:3773b22187a50fad07a202e1458a7e17
6.0 MB Download
md5:6f4ecb8b0b9b11635c017cbc94dd14c7
5.5 MB Download
md5:271efe8fc46832ac203b4e175fd512bd
3.3 kB Preview Download
md5:f578cdfaffa5f2549125c0ccc738012d
13.1 MB Preview Download

Additional details

Related works

Is referenced by
Dataset: 10.1016/j.rse.2021.112775 (DOI)

Dates

Available
2020-12-30

References

  • Wei, J., Li, Z., Li, K., Dickerson, R., Pinker, R., Wang, J., Liu, X., Sun, L., Xue, W., and Cribb, M. Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China. Remote Sensing of Environment, 2022, 270, 112775. https://doi.org/10.1016/j.rse.2021.112775
  • Yang, Z., Li, Z., Cheng, F., Lv, Q., Li, K., Zhang, T., Zhou, Y., Zhao, B., Xue, W., and Wei, J. Two-decade surface ozone (O3) pollution in China: enhanced fine-scale estimations and environmental health implications. Remote Sensing of Environment, 2025, 317, 114459. https://doi.org/10.1016/j.rse.2024.114459