| Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques Q Wang, S Li, R Li Energy 161, 821-831, 2018 | 199 | 2018 |
| Underestimated impact of the COVID-19 on carbon emission reduction in developing countries–a novel assessment based on scenario analysis Q Wang, S Li, R Li, F Jiang Environmental Research 204, 111990, 2022 | 155 | 2022 |
| Heterogeneous effects of energy efficiency, oil price, environmental pressure, R&D investment, and policy on renewable energy--evidence from the G20 countries Q Wang, S Li, Z Pisarenko Energy 209, 118322, 2020 | 132 | 2020 |
| Forecasting US shale gas monthly production using a hybrid ARIMA and metabolic nonlinear grey model Q Wang, S Li, R Li, M Ma Energy 160, 378-387, 2018 | 129 | 2018 |
| China's dependency on foreign oil will exceed 80% by 2030: Developing a novel NMGM-ARIMA to forecast China's foreign oil dependence from two dimensions Q Wang, S Li, R Li Energy 163, 151-167, 2018 | 98 | 2018 |
| Modeling carbon emission trajectory of China, US and India Q Wang, S Li, Z Pisarenko Journal of Cleaner Production 258, 120723, 2020 | 95 | 2020 |
| Uncovering the impact of the COVID-19 pandemic on energy consumption: New insight from difference between pandemic-free scenario and actual electricity consumption in China Q Wang, S Li, F Jiang Journal of Cleaner Production 313, 127897, 2021 | 94 | 2021 |
| Nonlinear impact of COVID-19 on pollutions–Evidence from Wuhan, New York, Milan, Madrid, bandra, London, tokyo and Mexico city Q Wang, S Li Sustainable Cities and Society 65, 102629, 2021 | 80 | 2021 |
| Comparison of forecasting energy consumption in Shandong, China Using the ARIMA model, GM model, and ARIMA-GM model S Li, R Li Sustainability 9 (7), 1181, 2017 | 70 | 2017 |
| Impact of COVID-19 pandemic on oil consumption in the United States: a new estimation approach Q Wang, S Li, M Zhang, R Li Energy 239, 122280, 2022 | 64 | 2022 |
| Comparison of forecasting India’s energy demand using an MGM, ARIMA model, MGM-ARIMA model, and BP neural network model F Jiang, X Yang, S Li Sustainability 10 (7), 2225, 2018 | 42 | 2018 |
| Carbon emission post-coronavirus: continual decline or rebound? R Li, S Li Structural Change and Economic Dynamics 57, 57-67, 2021 | 40 | 2021 |
| India's dependence on foreign oil will exceed 90% around 2025-The forecasting results based on two hybridized NMGM-ARIMA and NMGM-BP models S Li, Q Wang Journal of Cleaner Production 232, 137-153, 2019 | 37 | 2019 |
| Will Trump's coal revival plan work?-Comparison of results based on the optimal combined forecasting technique and an extended IPAT forecasting technique Q Wang, S Li, R Li Energy 169, 762-775, 2019 | 34 | 2019 |
| Forecasting China’s coal power installed capacity: A comparison of MGM, ARIMA, GM-ARIMA, and NMGM models S Li, X Yang, R Li Sustainability 10 (2), 506, 2018 | 31 | 2018 |
| The negative impact of the COVID-19 on renewable energy growth in developing countries: Underestimated S Li, Q Wang, X Jiang, R Li Journal of Cleaner Production 367, 132996, 2022 | 25 | 2022 |
| Forecasting coal consumption in India by 2030: using linear modified linear (MGM-ARIMA) and linear modified nonlinear (BP-ARIMA) combined models S Li, X Yang, R Li Sustainability 11 (3), 695, 2019 | 25 | 2019 |
| Evaluating energy sustainability using the pressure-state-response and improved matter-element extension models: case study of China S Li, R Li Sustainability 11 (1), 290, 2019 | 21 | 2019 |
| Predicting coal consumption in South Africa based on linear (metabolic grey model), nonlinear (non-linear grey model), and combined (metabolic grey model-Autoregressive … M Ma, M Su, S Li, F Jiang, R Li Sustainability 10 (7), 2552, 2018 | 15 | 2018 |
| Revisiting the existence of EKC hypothesis under different degrees of population aging: empirical analysis of panel data from 140 countries S Li, R Li International Journal of Environmental Research and Public Health 18 (23), 12753, 2021 | 7 | 2021 |
