Han, Tian, Hu, Xiaomin, Zhang, Jing, Xue, Wenhao, Che, Yunfei, Deng, Xiaoqing, Zhou, Lihua (2023) Rebuilding high-quality near-surface ozone data based on the combination of WRF-Chem model with a machine learning method to better estimate its impact on crop yields in the Beijing-Tianjin-Hebei region from 2014 to 2019. Environmental Pollution, 336. 122334 doi:10.1016/j.envpol.2023.122334
| Reference Type | Journal (article/letter/editorial) | ||
|---|---|---|---|
| Title | Rebuilding high-quality near-surface ozone data based on the combination of WRF-Chem model with a machine learning method to better estimate its impact on crop yields in the Beijing-Tianjin-Hebei region from 2014 to 2019 | ||
| Journal | Environmental Pollution | ||
| Authors | Han, Tian | Author | |
| Hu, Xiaomin | Author | ||
| Zhang, Jing | Author | ||
| Xue, Wenhao | Author | ||
| Che, Yunfei | Author | ||
| Deng, Xiaoqing | Author | ||
| Zhou, Lihua | Author | ||
| Year | 2023 (November) | Volume | 336 |
| Publisher | Elsevier BV | ||
| DOI | doi:10.1016/j.envpol.2023.122334Search in ResearchGate | ||
| Generate Citation Formats | |||
| Mindat Ref. ID | 16656104 | Long-form Identifier | mindat:1:5:16656104:3 |
| GUID | 0 | ||
| Full Reference | Han, Tian, Hu, Xiaomin, Zhang, Jing, Xue, Wenhao, Che, Yunfei, Deng, Xiaoqing, Zhou, Lihua (2023) Rebuilding high-quality near-surface ozone data based on the combination of WRF-Chem model with a machine learning method to better estimate its impact on crop yields in the Beijing-Tianjin-Hebei region from 2014 to 2019. Environmental Pollution, 336. 122334 doi:10.1016/j.envpol.2023.122334 | ||
| Plain Text | Han, Tian, Hu, Xiaomin, Zhang, Jing, Xue, Wenhao, Che, Yunfei, Deng, Xiaoqing, Zhou, Lihua (2023) Rebuilding high-quality near-surface ozone data based on the combination of WRF-Chem model with a machine learning method to better estimate its impact on crop yields in the Beijing-Tianjin-Hebei region from 2014 to 2019. Environmental Pollution, 336. 122334 doi:10.1016/j.envpol.2023.122334 | ||
| In | (2023) Environmental Pollution Vol. 336. Elsevier BV | ||
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