ChinaHighNO2: Big Data Seamless 1 km Ground-level NO2 Dataset for China

  • Jing Wei (Creator)
  • Song Liu (Creator)
  • Zhanqing Li (Creator)
  • Cheng Liu (Creator)
  • Kai Qin (Creator)
  • Xiong Liu (Creator)
  • Rachel T. Pinker (Creator)
  • Russell R. Dickerson (Creator)
  • Jintai Lin (Creator)
  • Folkert Boersma (Creator)
  • Xiao Lin Sun (Creator)
  • Runze Li (Creator)
  • Wenhao Xue (Creator)
  • Yuanzheng Cui (Creator)
  • Chengxin Zhang (Creator)
  • Jun Wang (Creator)



ChinaHighNO2 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 the 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 NO2 dataset in China from 2019 to 2020. This dataset yields a high quality with cross-validation coefficient of determination (CV-R2) values of 0.93, 0.95, and 0.96, and root-mean-square error (RMSE) values of 4.89, 3.11, and 2.35 µg m-3 on the daily, monthly, and yearly basises, respectively.
Date made available1 Mar 2021
Temporal coverage2019 - 2020
Geographical coverageChina


  • CHAP
  • ChinaHighNO2
  • big data
  • artificial itelligence

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