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Spatiotemporal Characteristics and Influencing Factors of Renewable Energy Production Development in Ningxia Hui Autonomous Region, China (2014–2021)

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  • Xiao Ma

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
    College of Geographical Sciences and Planning, Ningxia University, Yinchuan 750021, China)

  • Yongchun Yang

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
    Key Laboratory of Western China’s Environmental Systems, Ministry of Education of the People’s Republic of China, Lanzhou University, Lanzhou 730000, China)

  • Huazhang Zhu

    (Ningxia Academy of Environmental Sciences, Yinchuan 750021, China)

Abstract

Promoting the development of low-carbon renewable energy is crucial for meeting the growing energy demand, reducing dependence on fossil fuels, and controlling carbon dioxide emissions. Clarifying the spatiotemporal characteristics of regional renewable energy production and its influencing factors will help optimize the spatial layout of renewable energy production and provide a solid theoretical basis for coordinating the development of all aspects of renewable energy production. Using panel data from 22 districts and counties in Ningxia from 2014 to 2021, this study employed the spatial Gini coefficient, Moran’s I index, standard deviational ellipse, and geographical detector to analyze the spatiotemporal evolution patterns and influencing factors of renewable energy production development in Ningxia. The results indicate that renewable energy production in Ningxia exhibits significant spatial agglomeration and autocorrelation. Temporally, renewable energy production shows a spatial expansion trend characterized by dynamic agglomeration patterns. The coupling degree between renewable energy generation and the spatial distribution of power production is relatively high, with notable regional disparities. Urbanization level, urban population, per capita GDP, and industrial SO 2 emissions have a positive impact on renewable energy production, while energy intensity and environmental regulation show insignificant effects. To further promote the development of renewable energy, Ningxia should strengthen power infrastructure construction at the county level, enhance the radiating and driving effects of high-value areas on surrounding cities and counties, optimize the spatial layout of power facilities based on the agglomeration trajectories of renewable energy production, integrate multiple types of renewable energy to improve overall generation efficiency and system stability, and encourage local enterprises to increase technological and economic investments in renewable energy, thereby advancing sustainable energy transition and achieving high-quality development in resource-based regions.

Suggested Citation

  • Xiao Ma & Yongchun Yang & Huazhang Zhu, 2025. "Spatiotemporal Characteristics and Influencing Factors of Renewable Energy Production Development in Ningxia Hui Autonomous Region, China (2014–2021)," Land, MDPI, vol. 14(4), pages 1-26, April.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:4:p:908-:d:1639086
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    References listed on IDEAS

    as
    1. François, B. & Borga, M. & Creutin, J.D. & Hingray, B. & Raynaud, D. & Sauterleute, J.F., 2016. "Complementarity between solar and hydro power: Sensitivity study to climate characteristics in Northern-Italy," Renewable Energy, Elsevier, vol. 86(C), pages 543-553.
    2. Cai, Jinyang & Zheng, Huanyu & Vardanyan, Michael & Shen, Zhiyang, 2023. "Achieving carbon neutrality through green technological progress: evidence from China," Energy Policy, Elsevier, vol. 173(C).
    3. Pechan, A., 2017. "Where do all the windmills go? Influence of the institutional setting on the spatial distribution of renewable energy installation," Energy Economics, Elsevier, vol. 65(C), pages 75-86.
    4. Wei, Xinyang & Tong, Qing & Magill, Iain & Vithayasrichareon, Peerapat & Betz, Regina, 2020. "Evaluation of potential co-benefits of air pollution control and climate mitigation policies for China's electricity sector," Energy Economics, Elsevier, vol. 92(C).
    5. Dylan Harrison-Atlas & Andrew Glaws & Ryan N. King & Eric Lantz, 2024. "Artificial intelligence-aided wind plant optimization for nationwide evaluation of land use and economic benefits of wake steering," Nature Energy, Nature, vol. 9(6), pages 735-749, June.
    6. L. Kruitwagen & K. T. Story & J. Friedrich & L. Byers & S. Skillman & C. Hepburn, 2021. "A global inventory of photovoltaic solar energy generating units," Nature, Nature, vol. 598(7882), pages 604-610, October.
    7. Yu, Bolin & Fang, Debin & Meng, Jingxuan, 2021. "Analysis of the generation efficiency of disaggregated renewable energy and its spatial heterogeneity influencing factors: A case study of China," Energy, Elsevier, vol. 234(C).
    8. Chen, Chaoyi & Pinar, Mehmet & Stengos, Thanasis, 2020. "Renewable energy consumption and economic growth nexus: Evidence from a threshold model," Energy Policy, Elsevier, vol. 139(C).
    9. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    10. Flores, Francisco & Feijoo, Felipe & DeStephano, Paelina & Herc, Luka & Pfeifer, Antun & Duić, Neven, 2024. "Assessment of the impacts of renewable energy variability in long-term decarbonization strategies," Applied Energy, Elsevier, vol. 368(C).
    11. Goetzke, Frank & Rave, Tilmann, 2016. "Exploring heterogeneous growth of wind energy across Germany," Utilities Policy, Elsevier, vol. 41(C), pages 193-205.
    12. 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).
    13. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
    14. Yang, Di & Luan, Weixin & Qiao, Lu & Pratama, Mahardhika, 2020. "Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery," Applied Energy, Elsevier, vol. 268(C).
    15. Luc Anselin, 2001. "Spatial Effects in Econometric Practice in Environmental and Resource Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 705-710.
    16. Elberg, Christina & Hagspiel, Simeon, 2015. "Spatial dependencies of wind power and interrelations with spot price dynamics," European Journal of Operational Research, Elsevier, vol. 241(1), pages 260-272.
    17. Abbas, Khizar & Han, Mengyao & Xu, Deyi & Butt, Khalid Manzoor & Baz, Khan & Cheng, Jinhua & Zhu, Yongguang & Hussain, Sanwal, 2024. "Exploring synergistic and individual causal effects of rare earth elements and renewable energy on multidimensional economic complexity for sustainable economic development," Applied Energy, Elsevier, vol. 364(C).
    18. Philipp C. Verpoort & Lukas Gast & Anke Hofmann & Falko Ueckerdt, 2024. "Impact of global heterogeneity of renewable energy supply on heavy industrial production and green value chains," Nature Energy, Nature, vol. 9(4), pages 491-503, April.
    19. Shi, Xiaohui & Chu, Junhui & Zhao, Changyi, 2021. "Exploring the spatiotemporal evolution of energy intensity in China by visual technology of the GIS," Energy, Elsevier, vol. 228(C).
    20. Xu, Jie & Lv, Tao & Hou, Xiaoran & Deng, Xu & Li, Na & Liu, Feng, 2022. "Spatiotemporal characteristics and influencing factors of renewable energy production in China: A spatial econometric analysis," Energy Economics, Elsevier, vol. 116(C).
    21. Aamir Javed & Agnese Rapposelli & Feroz Khan & Asif Javed & Nabila Abid, 2024. "Do Green Technology Innovation, Environmental Policy, and the Transition to Renewable Energy Matter in Times of Ecological Crises? A Step towards Ecological Sustainability," Post-Print hal-04889069, HAL.
    22. Javed, Aamir & Rapposelli, Agnese & Khan, Feroz & Javed, Asif & Abid, Nabila, 2024. "Do green technology innovation, environmental policy, and the transition to renewable energy matter in times of ecological crises? A step towards ecological sustainability," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    23. Lohr, C. & Schlemminger, M. & Peterssen, F. & Bensmann, A. & Niepelt, R. & Brendel, R. & Hanke-Rauschenbach, R., 2022. "Spatial concentration of renewables in energy system optimization models," Renewable Energy, Elsevier, vol. 198(C), pages 144-154.
    24. Lan Khanh Chu, 2023. "Environmentally related technologies and environmental regulations in promoting renewable energy: evidence from OECD countries," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 13(1), pages 177-197, March.
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