Exploring the spatiotemporal evolution of energy intensity in China by visual technology of the GIS
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DOI: 10.1016/j.energy.2021.120650
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Cited by:
- Limei Ma & Qianying Wang & Dan Shi & Qinglong Shao, 2023. "Spatiotemporal patterns and determinants of renewable energy innovation: Evidence from a province-level analysis in China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
- Chong, Cheng Tung & Fan, Yee Van & Lee, Chew Tin & Klemeš, Jiří Jaromír, 2022. "Post COVID-19 ENERGY sustainability and carbon emissions neutrality," Energy, Elsevier, vol. 241(C).
- Wang, Kai-Hua & Zhao, Yan-Xin & Su, Yun Hsuan & Lobonţ, Oana-Ramona, 2023. "Energy security and CO2 emissions: New evidence from time-varying and quantile-varying aspects," Energy, Elsevier, vol. 273(C).
- Zhang, Hongyan & Chen, Suisui & Wang, Shuhong, 2022. "Impact of economic growth and labor productivity dispersion on energy intensity in China," Energy, Elsevier, vol. 242(C).
- Wang, Na & Fu, Xiaodong & Wang, Shaobin, 2022. "Spatial-temporal variation and coupling analysis of residential energy consumption and economic growth in China," Applied Energy, Elsevier, vol. 309(C).
- Yan, Junna & Li, Yingzhu & Su, Bin & Ng, Tsan Sheng, 2022. "Contributors and drivers of Chinese energy use and intensity from regional and demand perspectives, 2012-2015-2017," Energy Economics, Elsevier, vol. 115(C).
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Keywords
Energy intensity; Spatiotemporal evolution; Standard deviational ellipse; Spatial heterogeneity;All these keywords.
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