| Use of multi-rotor unmanned aerial vehicles for fine-grained roadside air pollution monitoring B Li, R Cao, Z Wang, RF Song, ZR Peng, G Xiu, Q Fu Transportation research record 2673 (7), 169-180, 2019 | 36 | 2019 |
| Prediction of air pollutants on roadside of the elevated roads with combination of pollutants periodicity and deep learning method C Wu, R Song, Z Peng Building and Environment 207, 108436, 2022 | 27 | 2022 |
| Development and utilization of hexacopter unmanned aerial vehicle platform to characterize vertical distribution of boundary layer ozone in wintertime Q Chen, XB Li, R Song, HW Wang, B Li, HD He, ZR Peng Atmospheric Pollution Research 11 (7), 1073-1083, 2020 | 23 | 2020 |
| Vertical characteristics of winter ozone distribution within the boundary layer in shanghai based on hexacopter unmanned aerial vehicle platform Q Chen, D Wang, X Li, B Li, R Song, H He, Z Peng Sustainability 11 (24), 7026, 2019 | 20 | 2019 |
| A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network C Wu, R Song, X Zhu, Z Peng, Q Fu, J Pan Environmental Pollution 320, 121075, 2023 | 17 | 2023 |
| Characterizing vertical distribution patterns of PM2. 5 in low troposphere of Shanghai city, China: Implications from the perspective of unmanned aerial vehicle observations R Song, D Wang, X Li, B Li, Z Peng Atmospheric Environment 265, 118724, 2021 | 14 | 2021 |
| Observation based study on atmospheric oxidation capacity in Shanghai during late-autumn: Contribution from nitryl chloride S Lou, Z Tan, G Gan, J Chen, H Wang, Y Gao, D Huang, C Huang, X Li, ... Atmospheric Environment 271, 118902, 2022 | 8 | 2022 |
Xiaobing LiPost-doctoral research, Jinan UniversityVerified email at jnu.edu.cn
