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ChinaHighPM₁: Daily Seamless 1 km Ground-Level PM₁ Dataset for China (2000–Present)

Authors: Wei, Jing; Li, Zhanqing;

ChinaHighPM₁: Daily Seamless 1 km Ground-Level PM₁ Dataset for China (2000–Present)

Abstract

ChinaHighPM1 is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution. Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level PM1 dataset for China from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.83, a root-mean-square error (RMSE) of 9.50 µg m-3, and a mean absolute error (MAE) of 6.17 µg m-3 on a daily basis. If you use the ChinaHighPM1 dataset in your scientific research, please cite the following reference (Wei et al., EST, 2019): Wei, J., Li, Z., Guo, J., Sun, L., Huang, W., Xue, W., Fan, T., and Cribb, M. Satellite-derived 1-km-resolution PM1 concentrations from 2014 to 2018 across China. Environmental Science & Technology, 2019, 53(22), 13265–13274. https://doi.org/10.1021/acs.est.9b03258 More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html

Note that the data are recorded in local time (i.e., Beijing time: GMT+8). This dataset is continuously updated. If you require additional data for related scientific research, please contact us (weijing_rs@163.com or weijing.rs@gmail.com).

Related Organizations
Keywords

Big Data, Remote Sensing, Artificial intelligence, 1 km, CHAP, ChinaHighPM10, ChinaHighPM1

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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