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2 results for “ChinaHighO3”
ChinaHighO3: Big Data Seamless 10 km Ground-level MDA8 O3 Dataset for China
<p>ChinaHighO<sub>3</sub> 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. </p> <p>This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 10 km (i.e., D10K, M10K, and Y10K) ground-level maximum 8-hour average (MDA8) O<sub>3</sub> dataset in China from 1979 to 2020. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R<sup>2</sup>) of 0.87, a root-mean-square error (RMSE) of 17.10 µg m<sup>-3</sup>, and a mean absolute error (MAE) of 11.29 µg m<sup>-3</sup> on a daily basis.</p> <p>If you use the ChinaHighO<sub>3</sub> dataset for related scientific research, please cite the corresponding reference (Wei et al., RSE, 2022; He et al., 2022):</p> <ul> <li> <p>Wei, J., Li, Z., Li, K., Dickerson, R., Pinker, R., Wang, J., Liu, X., Sun, L., Xue, W., and Cribb, M. <a href="https://weijing-rs.github.io/publications/Wei_et_al-RSE-2022.pdf">Full-coverage mapping and spatiotemporal variations of ground-level ozone (O<sub>3</sub>) pollution from 2013 to 2020 across China</a>. <em>Remote Sensing of Environment</em>, 2022, 270, 112775. https://doi.org/10.1016/j.rse.2021.112775</p> </li> <li> <p>He, L., Wei, J., Wang, Y., Shang, Q., Liu, J., Yin, Y., Frankerberg, C., Jiang, J., Li, Z., and Yung, Y. <a href="https://weijing-rs.github.io/publications/He_et_al-EF-2022.pdf">Marked impacts of pollution mitigation on crop yields in China</a>. <em>Earth's Future</em>, 2022, 10, e2022EF002936. https://doi.org/10.1029/2022EF002936</p> </li> </ul> <p><strong>Note that access to this dataset is now restricted, as a longer-term (2000 to present), high-resolution (1 km), and higher quality ChinaHighO<sub>3</sub> dataset is now available: <a href="http://doi.org/10.5281/zenodo.10477125">http://doi.org/10.5281/zenodo.10477125</a></strong></p> <p><strong>More CHAP datasets of different air pollutants can be found at: <a href="https://weijing-rs.github.io/product.html">https://weijing-rs.github.io/product.html</a></strong></p>
ChinaHighO3: OMI/Aura 25 km Ground-level O3 Dataset for China (Closed)
<p>ChinaHighO<sub>3</sub> 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. </p> <p>This is the OMI/Aura-derived yearly 25 km ground-level O<sub>3</sub> products in China from 2005 to 2019, and this dataset yields a high quality with a cross-validation coefficient of determination (CV-R<sup>2</sup>) of 0.84 and a root-mean-square error (RMSE) of 20.11 µg m<sup>-3</sup> on a daily basis.</p> <p><strong>Note that this dataset is closed access since a longer-term, seamless, high-resolution (10 km), and higher quality ChinaHighO<sub>3</sub> dataset is available at: <a href="https://doi.org/10.5281/zenodo.4400042">https://doi.org/10.5281/zenodo.4400042</a></strong></p> <p><strong>More CHAP datasets of different air pollutants can be found at: <a href="https://weijing-rs.github.io/product.html">https://weijing-rs.github.io/product.html</a></strong></p>
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