The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China
Open accessAbstract
Ozone (O 3 ) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O 3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O 3 from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products , atmospheric reanalysis, and an emission inventory . A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O 3 dataset covering China (called ChinaHighO 3 ) from 2013 to 2020 was generated. Our MDA8 O 3 estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m 3 in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O 3 pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O 3 concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O 3 concentration showed an average growth rate of 2.49 μg/m 3 /yr ( p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O 3 standard (i.e., MDA8 O 3 = 160 μg/m 3 ). Summertime O 3 concentrations and the probability of occurrence of daily O 3 pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China.
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., et al. (2020) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.3803 · Cited by 31,882
Coronavirus Disease 2019 (COVID-19): A Perspective from China
Zu, Z. Y., Jiang, M. D., Xu, P. P., Chen, W., Ni, Q. Q., Lu, G. M., & Zhang, L. J. (2020) · Radiology · doi:10.1148/radiol.2020200490 · Cited by 2,070
Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., et al. (2020) · Science · doi:10.1126/science.abb6105 · Cited by 2,010
Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation
Rodriguez, J. D., Perez, A., & Lozano, J. A. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.187 · Cited by 1,890
Anthropogenic drivers of 2013–2017 trends in summer surface ozone in China
Li, K., Jacob, D. J., Liao, H., Shen, L., Zhang, Q., & Bates, K. H. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1812168116 · Cited by 1,804
Self-citationIndirect radiative forcing of climate change through ozone effects on the land-carbon sink
Sitch, S., Cox, P. M., Collins, W. J., & Huntingford, C. (2007) · Nature · doi:10.1038/nature06059 · Cited by 1,019
Long-term ozone exposure and mortality in a large prospective study
Turner, M. C., Jerrett, M., Pope, C. A., Krewski, D., Gapstur, S. M., Diver, W. R., Beckerman, B. S., Marshall, J. D., Su, J., Crouse, D. L., et al. (2016) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201508-1633oc · Cited by 938
Wong, C.-M., Vichit-Vadakan, N., Kan, H., & Qian, Z. (2008) · Environmental Health Perspectives · doi:10.1289/ehp.11257 · Cited by 476
Long-Term Exposure to Ozone and Cause-Specific Mortality Risk in the United States
Lim, C. C., Hayes, R. B., Ahn, J., Shao, Y., Silverman, D. T., Jones, R. R., Garcia, C., Bell, M. L., & Thurston, G. D. (2019) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201806-1161oc · Cited by 237
Metadata
- Authors
- Wei, J., Li, Z., Li, K., Dickerson, R. R., Pinker, R. T., Wang, J., Liu, X., Sun, L., Xue, W., & Cribb, M.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2022-03
- Volume
- 270
- Pages
- 112775
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W3190822217
- Cited by
- 683
- References
- 10
- FWCI
- 27.54
- Type
- journal article
- Language
- en
- Open access
- gold
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- The paper
- Wei, J., Li, Z., Li, K., Dickerson, R. R., Pinker, R. T., Wang, J., Liu, X., Sun, L., Xue, W., & Cribb, M. (2022). Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2021.112775
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