Planned intervention: On Wednesday April 3rd 05:30 UTC Zenodo will be unavailable for up to 2-10 minutes to perform a storage cluster upgrade.
Published September 3, 2021 | Version v1
Dataset Open

Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005-2017 based on multi-variable random forest model

  • 1. China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention

Description

The aim of our study was to construct random forest models with high-performance, and estimate daily average PM2.5 concentration and O3 daily maximum 8h average concentration (O3-8hmax) of China in 2005-2017 at a spatial resolution of 1km×1km. The model variables included meteorological variables, satellite data, chemical transport model output, geographic variables and socioeconomic variables. Random forest model based on ten-fold cross validation was established, and spatial and temporal validations were performed to evaluate the model performance. According to our sample-based division method, the daily, monthly and yearly simulations of PM2.5 gave average model fitting R2 values of 0.85, 0.88 and 0.90, respectively; these R2 values were 0.77, 0.77, and 0.69 for O3-8hmax, respectively. The meteorological variables and their lagged values can significantly affect both PM2.5 and O3-8hmax simulations. During 2005-2017, PM2.5 exhibited an overall downward trend, while ambient O3 experienced an upward trend. Whilst the spatial patterns of PM2.5 and O3-8hmax barely changed between 2005 and 2017, the temporal trend had spatial characteristic.

Each dataset is the annual mean concentration of PM2.5 or O3-8hmax based on the standard grid (Grid.csv) for that year. The coordinate system of the grid is WGS-84.

Files

Files (1.1 GB)

Name Size Download all
md5:77fc469d348bd03e7f466e783550b7ab
35.5 MB Download
md5:674f12be312ba14aa2bdc0e78ff2fbfe
35.5 MB Download
md5:7b868358bf3a59f2c1a54424d24426f0
35.6 MB Download
md5:9f21dccd95b32b5a93b098eb9241ae6a
35.7 MB Download
md5:a9677638f87344c6ab8884730ef2e8ca
35.5 MB Download
md5:076250e5fe6a0f170679967e5a6c6421
35.5 MB Download
md5:533f1d42e05f163f1cb8b5bebd9eb5a0
35.6 MB Download
md5:e0b807456b3611cd8a3b8943de3b3a75
35.6 MB Download
md5:004472106e809e93e0e0c15807d258fe
35.7 MB Download
md5:bd00be5d95cb7ec6a54144da61104073
35.4 MB Download
md5:2e60f9819748cad32df24ad539a373cb
34.9 MB Download
md5:0d960f3b80a3442dd674907db8a3abe1
35.0 MB Download
md5:7685ed5c49494008d0359fd09e5a945f
35.2 MB Download
md5:2c264d8e9ac113a70305aae0661bfa97
152.5 MB Download
md5:43883c2a548032a5fe54cbc4a9611183
33.7 MB Download
md5:372dffe06aecea3d7147933ca9596df3
33.8 MB Download
md5:2d3f33755b3e76a31acd273b767a4b73
33.9 MB Download
md5:7e67cb7ab5ae3d9df99010d826562e83
33.8 MB Download
md5:6deacaa5a341d95415b4f7b86c52eafa
34.0 MB Download
md5:cfdf8b5cdc9ed857a8995a1488ee95d6
33.8 MB Download
md5:da7b4f8e02436c2869df8e1b1169c724
33.7 MB Download
md5:48dff8ded20d04fefcceb8ca27c5179a
33.7 MB Download
md5:9c245816b1407271dc352129dc5c1969
33.9 MB Download
md5:2dc3ad0abc80e3a6ac0f49ae77840717
33.8 MB Download
md5:0237adcd4d6cea34519bc52916150cf8
33.5 MB Download
md5:be604091ef82abb001942054e1db7923
34.2 MB Download
md5:2fcd6e7e5f515d9e91e2ef1970799ea6
34.1 MB Download