skip to main content

The contribution of green technological innovation, clean energy, and oil rents in improving the load capacity factor and achieving SDG13 in Saudi Arabia

1Department of Business Administration, College of Business and Economics, Qassim University, PO Box 6640, Buraidah 51452, Saudi Arabia

2Department of Finance and Insurance, College of Business Administration, Northern Border University, PO Box, 1321 Arar 91431, Saudi Arabia

Received: 28 Aug 2024; Revised: 4 Oct 2024; Accepted: 10 Oct 2024; Available online: 20 Oct 2024; Published: 1 Nov 2024.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2024 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

This research aims to assess the effects of green technological innovation, renewable energy sources, and oil rents on the load capacity factor in Saudi Arabia from 1988 to 2021. The primary conclusions can be outlined as follows. The combined cointegration and Saikkonen-Lütkepohl cointegration tests reveal long-run relationships between the load capacity factor and the explanatory variables at the 1% significance level. In comparison, the Phillips-Ouliaris test shows evidence of cointegration only at 10%. Moreover, the quantile regression indicates that oil rents adversely impact environmental quality; however, they remain contingent upon environmental conditions. A 1% increase in oil rents results in a decline in environmental quality by 0.025% under poor conditions, 0.036% under moderate/normal conditions, and 0.108% under good conditions. On the contrary, renewable energy consumption and green technological innovation improve environmental quality, irrespective of the prevailing environmental conditions. However, the environmental impacts of renewable energy consumption exceed those of green technological innovation. Results show that a 1% increase in renewable energy consumption leads to a 0.052-0.253% improvement in environmental quality, whereas a 1% increase in green technological innovation results only in a 0.017-0.047% improvement. Finally, population and GDP per capita exert negative and positive implications on the load capacity factor, respectively, while energy intensity has no significant environmental effects. The research findings provide significant insights and suggest policy recommendations to address climate change and meet the targets set out in SDG13.

Fulltext View|Download
Keywords: Load capacity factor; sustainable development; renewable energy; technological innovation; Saudi Arabia; Quantile regression.
Funding: The authors gratefully acknowledge Qassim University, represented by the Deanship of Graduate Studies and Scientific Research, on the financial support for this research under the number 2023-SDG-1-HSRC-36963 during the academic year 1445 AH/2023 AD.

Article Metrics:

  1. Abbassi, A., Ben Mehrez, R., Abbassi, R., Jerbi, H., Saidi, S., & Jemli, M. (2022). Eco-feasibility study of a distributed power generation system driven by renewable green energy sources. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 3981-3999. https://doi.org/10.1080/15567036.2022.2071504
  2. Acheampong, A. O., & Opoku, E. E. O. (2023). Environmental degradation and economic growth: Investigating linkages and potential pathways. Energy Economics, 123, 106734. https://doi.org/10.1016/j.eneco.2023.106734
  3. Adebayo, T. S., Meo, M. S., & Özkan, O. (2024). Scrutinizing the impact of energy transition on GHG emissions in G7 countries via a novel green quality of energy mix index. Renewable Energy, 226, 120384. https://doi.org/10.1016/j.renene.2024.120384
  4. Ahmad, M., & Satrovic, E. (2023). How does monetary policy moderate the influence of economic complexity and technological innovation on environmental sustainability? The role of green central banking. International Journal of Finance & Economics. https://doi.org/10.1002/ijfe.2872
  5. Ahmed, Z., Ahmad, M., Rjoub, H., Kalugina, O. A., & Hussain, N. (2022). Economic growth, renewable energy consumption, and ecological footprint: Exploring the role of environmental regulations and democracy in sustainable development. Sustainable Development, 30(4), 595-605. https://doi.org/10.1002/sd.2251
  6. Ahmed, Z., Le, H. P., & Shahzad, S. J. H. (2022). Toward environmental sustainability: how do urbanization, economic growth, and industrialization affect biocapacity in Brazil? Environment, Development and Sustainability, 24(10), 11676-11696. https://doi.org/10.1007/s10668-021-01915-x
  7. Alharbey, M., & Ben-Salha, O. (2024). Do institutions contribute to environmental sustainability? A global analysis using the dynamic spatial Durbin and threshold models. Journal of Environmental Management, 357, 120681. https://doi.org/10.1016/j.jenvman.2024.120681
  8. Ali, S., Yan, Q., Razzaq, A., Khan, I., & Irfan, M. (2023). Modeling factors of biogas technology adoption: a roadmap towards environmental sustainability and green revolution. Environmental Science and Pollution Research, 30(5), 11838-11860. https://doi.org/10.1007/s11356-022-22894-0
  9. Ali, U., Guo, Q., Nurgazina, Z., Sharif, A., Kartal, M. T., Depren, S. K., & Khan, A. (2023). Heterogeneous impact of industrialization, foreign direct investments, and technological innovation on carbon emissions intensity: Evidence from Kingdom of Saudi Arabia. Applied Energy, 336, 120804. https://doi.org/10.1016/j.apenergy.2023.120804
  10. Alkhathlan, K., & Javid, M. (2015). Carbon emissions and oil consumption in Saudi Arabia. Renewable and Sustainable Energy Reviews, 48, 105-111. https://doi.org/10.1016/j.rser.2015.03.072
  11. Al-Mulali, U., Saboori, B., & Ozturk, I. (2015). Investigating the environmental Kuznets curve hypothesis in Vietnam. Energy Policy, 76, 123-131. https://doi.org/10.1016/j.enpol.2014.11.019
  12. AlNemer, H. A., Hkiri, B., & Tissaoui, K. (2023). Dynamic impact of renewable and non-renewable energy consumption on CO2 emission and economic growth in Saudi Arabia: Fresh evidence from wavelet coherence analysis. Renewable Energy, 209, 340-356. https://doi.org/10.1016/j.enpol.2014.11.019
  13. Alola, A. A., Adebayo, T. S., & Onifade, S. T. (2022). Examining the dynamics of ecological footprint in China with spectral Granger causality and quantile-on-quantile approaches. International Journal of Sustainable Development & World Ecology, 29(3), 263-276. https://doi.org/10.1080/13504509.2021.1990158
  14. Apergis, N., Degirmenci, T., & Aydin, M. (2023). Renewable and non-renewable energy consumption, energy technology investment, green technological innovation, and environmental sustainability in the United States: Testing the EKC and LCC hypotheses with novel Fourier estimation. Environmental Science and Pollution Research, 30(60), 125570-125584. https://doi.org/10.1007/s11356-023-30901-1
  15. Arslan, H. M., Khan, I., Latif, M. I., Komal, B., & Chen, S. (2022). Understanding the dynamics of natural resources rents, environmental sustainability, and sustainable economic growth: new insights from China. Environmental Science and Pollution Research, 29(39), 58746-58761. https://doi.org/10.1007/s11356-022-19952-y
  16. Avcı, P., Sarıgül, S. S., Karataşer, B., Çetin, M., & Aslan, A. (2024). Analysis of the relationship between tourism, green technological innovation and environmental quality in the top 15 most visited countries: evidence from method of moments quantile regression. Clean Technologies and Environmental Policy, 1-19. https://doi.org/10.1007/s10098-023-02708-8
  17. Aydin, M., & Degirmenci, T. (2023). The role of greenfield investment and investment freedom on environmental quality: testing the EKC hypothesis for EU countries. International Journal of Sustainable Development & World Ecology, 1-11. https://doi.org/10.1080/13504509.2024.2326567
  18. Ayhan, F., Kartal, M. T., Kılıç Depren, S., & Depren, Ö. (2023). Asymmetric effect of economic policy uncertainty, political stability, energy consumption, and economic growth on CO2 emissions: evidence from G-7 countries. Environmental Science and Pollution Research, 30(16), 47422-47437. https://doi.org/10.1007/s11356-023-25665-7
  19. Ben-Ahmed, K., & Ben-Salha, O. (2024). Assessing the spillover effects of various forms of energy on CO2 emissions—An empirical study based on dynamic spatial Durbin model. Heliyon, 10(10). https://www.cell.com/heliyon/fulltext/S2405-8440(24)07114-7
  20. Benhamed, A., Osman, Y., Ben-Salha, O., & Jaidi, Z. (2023). Unveiling the spatial effects of climate change on economic growth: International evidence. Sustainability, 15(10), 8197. https://doi.org/10.3390/su15108197
  21. Ben-Salha, O., & Zmami, M. (2023). Analyzing the symmetric and asymmetric effects of disaggregate natural resources on the ecological footprint in Saudi Arabia: insights from the dynamic ARDL approach. Environmental Science and Pollution Research, 30(21), 59424-59442. https://doi.org/10.1007/s11356-023-26683-1 ·
  22. Ben-Salha, O., Abid, A., & El Montasser, G. (2023). Linear and nonlinear causal linkages between exports and growth in next eleven economies. Journal of the Knowledge Economy, 14(2), 1194-1226. https://doi.org/10.1007/s13132-022-00958-3
  23. Ben-Salha, O., Hakimi, A., Zaghdoudi, T., Soltani, H., & Nsaibi, M. (2022). Assessing the impact of fossil fuel prices on renewable energy in China using the novel dynamic ARDL simulations approach. Sustainability, 14(16), 10439. https://doi.org/10.3390/su141610439
  24. Bulut, U., Atay-Polat, M., & Bulut, A. S. (2024). Environmental deterioration, renewable energy, natural resource rents, and schooling in Türkiye: Does the degree of energy transition matter for environmental quality? Journal of Environmental Management, 365, 121639. https://doi.org/10.1016/j.jenvman.2024.121639
  25. Chen, J., Huang, S., & Kamran, H. W. (2023). Empowering sustainability practices through energy transition for sustainable development goal 7: the role of energy patents and natural resources among European Union economies through advanced panel. Energy Policy, 176, 113499. https://doi.org/10.1016/j.enpol.2023.113499
  26. Damrah, S., Satrovic, E., & Shawtari, F. A. (2022). How does financial inclusion affect environmental degradation in the six oil exporting countries? The moderating role of information and communication technology. Frontiers in Environmental Science, 10, 1013326. https://doi.org/10.3389/fenvs.2022.1013326
  27. Dietz, T., & Rosa, E. A. (1994). Rethinking the environmental impacts of population, affluence and technology. Human Ecology Review, 1(2), 277-300. http://www.jstor.org/stable/24706840
  28. Djedaiet, A., Ayad, H., & Ben-Salha, O. (2024). Oil prices and the load capacity factor in African oil-producing OPEC members: Modeling the symmetric and asymmetric effects. Resources Policy, 89, 104598. https://doi.org/10.1016/j.resourpol.2023.104598
  29. Dong, K., Sun, R., & Dong, X. (2018). CO2 emissions, natural gas and renewables, economic growth: assessing the evidence from China. Science of the Total Environment, 640, 293-302. https://doi.org/10.1016/j.scitotenv.2018.05.322
  30. Dorta, M., & Sanchez, G. (2021). Bootstrap unit-root test for random walk with drift: The bsrwalkdrift command. The Stata Journal, 21(1), 39-50. https://doi.org/10.1177/1536867X211000003
  31. Ehrlich, P. R., & Holdren, J. P. (1971). Impact of population growth. Science, 171(3977), 1212-1217. https://www.science.org/doi/abs/10.1126/science.171.3977.1212
  32. Fang, Z., Wang, T., & Yang, C. (2024). Nexus among natural resources, environmental sustainability, and political risk: Testing the load capacity factor curve hypothesis. Resources Policy, 90, 104791. https://doi.org/10.1016/j.resourpol.2024.104791
  33. Hossain, M. E., Islam, M. S., Bandyopadhyay, A., Awan, A., Hossain, M. R., & Rej, S. (2022). Mexico at the crossroads of natural resource dependence and COP26 pledge: Does technological innovation help?. Resources Policy, 77, 102710. https://doi.org/10.1016/j.resourpol.2022.102710
  34. Islam, M. S. (2024). Linking green innovation to environmental quality in Saudi Arabia: an application of the NARDL approach. Environment, Development and Sustainability, 1-22. https://doi.org/10.1007/s10668-024-04751-x
  35. Javed, A., Subhani, B. H., Javed, A., & Rapposelli, A. (2024). Accessing the efficacy of green growth, energy efficiency, and green innovation for environmental performance in top manufacturing nations in the framework of sustainable development. Quality & Quantity, 1-35. https://doi.org/10.1007/s11135-024-01918-6
  36. Kahia, M., Jarraya, B., Kahouli, B., & Omri, A. (2023). Do environmental innovation and green energy matter for environmental sustainability? Evidence from Saudi Arabia (1990–2018). Energies, 16(3), 1376. https://doi.org/10.3390/en16031376
  37. Kahia, M., Moulahi, T., Mahfoudhi, S., Boubaker, S., & Omri, A. (2021). A machine learning process for examining the linkage among disaggregated energy consumption, economic growth, and environmental degradation. Resources Policy, 79, 103104. https://doi.org/10.1016/j.resourpol.2022.103104
  38. Khoshnevis Yazdi, S., & Shakouri, B. (2018). The effect of renewable energy and urbanization on CO2 emissions: A panel data. Energy Sources, Part B: Economics, Planning, and Policy, 13(2), 121-127. https://doi.org/10.1080/15567249.2017.1400607
  39. Koenker, R., & Bassett, G. J. (1978). Regression quantiles. Econometrica, 46, 33-50. https://doi.org/10.2307/1913643
  40. Mahmood, H., & Saqib, N. (2022). Oil rents, economic growth, and CO2 emissions in 13 OPEC member economies: asymmetry analyses. Frontiers in Environmental Science, 10, 1025756. https://doi.org/10.3389/fenvs.2022.1025756
  41. Ngoc, B. H., & Awan, A. (2022). Does financial development reinforce ecological footprint in Singapore? Evidence from ARDL and Bayesian analysis. Environmental Science and Pollution Research, 29(16), 24219-24233. https://doi.org/10.1007/s11356-021-17565-5
  42. Ni, Z., Yang, J., & Razzaq, A. (2022). How do natural resources, digitalization, and institutional governance contribute to ecological sustainability through load capacity factors in highly resource-consuming economies? Resources Policy, 79, 103068. https://doi.org/10.1016/j.resourpol.2022.103068
  43. Niu, J., Qin, W., Wang, L., Zhang, M., Wu, J., & Zhang, Y. (2023). Climate change impact on photovoltaic power potential in China based on CMIP6 models. Science of the Total Environment, 858, 159776. https://doi.org/10.1016/j.scitotenv.2022.159776
  44. Nuţă, F. M., Sharafat, A., Abban, O. J., Khan, I., Irfan, M., Nuţă, A. C., ... & Asghar, M. (2024). The relationship among urbanization, economic growth, renewable energy consumption, and environmental degradation: A comparative view of European and Asian emerging economies. Gondwana Research, 128, 325-339. https://doi.org/10.1016/j.gr.2023.10.023
  45. Pata, U. K., & Karlilar Pata, S. (2024). Assessing the power of biofuels and green technology innovation on the environment: The LCC perspective. Energy & Environment. https://doi.org/10.1177/0958305X241279905
  46. Pata, U. K., Wang, Q., Kartal, M. T., & Sharif, A. (2024). The role of disaggregated renewable energy consumption on income and load capacity factor: a novel inclusive sustainable growth approach. Geoscience Frontiers, 15(1), 101693. https://doi.org/10.1016/j.gsf.2023.101693
  47. Raggad, B., Ben-Salha, O., Zrelly, H., & Jbir, R. (2024). Modelling the impact of uncertainty on sectoral GHG emissions in Saudi Arabia using the causality-in-quantiles and quantile-on-quantile approaches. Energy Strategy Reviews, 51, 101308. https://doi.org/10.1016/j.esr.2024.101308
  48. Ragmoun, W. (2022). A spatio-temporal analysis of human capital, economic and institutional quality as determinants of international formal entrepreneurship. European Journal of International Management, Forthcoming, https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ejim
  49. Ragmoun, W. (2023a). Ecological footprint, natural resource rent, and industrial production in MENA region: Empirical evidence using the SDM model. Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e20060
  50. Ragmoun, W. (2023b). Institutional quality, unemployment, economic growth and entrepreneurial activity in developed countries: a dynamic and sustainable approach. Review of International Business and Strategy, 33 (3), 345-370. https://doi.org/10.1108/RIBS-10-2021-0136
  51. Ragmoun, W. (2024a). The Analysis of Trigger Factors of the Environmental Entrepreneurship Process in Saudi Arabia: An Innovative Approach. Economies, 12(9), 254. https://doi.org/10.3390/economies12090254
  52. Ragmoun, W. (2024b), The impact of environmental entrepreneurship and anti-corruption on environmental degradation. Journal of Global Entrepreneurship Research, 14 (17), 1-17, . https://doi.org/10.1007/s40497-024-00389-1
  53. Rehman, A., Alam, M. M., Ozturk, I., Alvarado, R., Murshed, M., Işık, C., & Ma, H. (2023). Globalization and renewable energy use: how are they contributing to upsurge the CO2 emissions? A global perspective. Environmental Science and Pollution Research, 30(4), 9699-9712. https://doi.org/10.1007/s11356-022-22775-6
  54. Saidi, K., & Mbarek, M. B. (2016). Nuclear energy, renewable energy, CO2 emissions, and economic growth for nine developed countries: Evidence from panel Granger causality tests. Progress in Nuclear Energy, 88, 364-374. https://doi.org/10.1016/j.pnucene.2016.01.018
  55. Shittu, W., Adedoyin, F. F., Shah, M. I., & Musibau, H. O. (2021). An investigation of the nexus between natural resources, environmental performance, energy security and environmental degradation: evidence from Asia. Resources Policy, 73, 102227. https://doi.org/10.1016/j.resourpol.2021.102227
  56. Siche, R., Pereira, L., Agostinho, F., & Ortega, E. (2010). Convergence of ecological footprint and emergy analysis as a sustainability indicator of countries: Peru as case study. Communications in Nonlinear Science and Numerical Simulation, 15(10), 3182-3192. https://doi.org/10.1016/j.cnsns.2009.10.027
  57. Sweidan, O. D., & Elbargathi, K. (2022). The effect of oil rent on economic development in Saudi Arabia: Comparing the role of globalization and the international geopolitical risk. Resources Policy, 75, 102469. https://doi.org/10.1016/j.resourpol.2021.102469
  58. Tiba, S. (2021). The oil abundance and oil dependence scenarios: The bad and the ugly? Environmental Modeling & Assessment, 26, 283-294. https://doi.org/10.1007/s10666-020-09737-3
  59. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. https://doi.org/10.1016/0304-4076(94)01616-8
  60. Touati, K., & Ben-Salha, O. (2024). Are Natural Resources Harmful to the Ecology? Fresh Insights from Middle East and North African Resource-Abundant Countries. Sustainability, 16(11), 4435. https://doi.org/10.3390/su16114435
  61. Toumi, S., & Toumi, H. (2019). Asymmetric causality among renewable energy consumption, CO 2 emissions, and economic growth in KSA: evidence from a non-linear ARDL model. Environmental Science and Pollution Research, 26, 16145-16156. https://doi.org/10.1007/s11356-019-04955-z
  62. Ulucak, R., & Baloch, M. A. (2023). An empirical approach to the nexus between natural resources and environmental pollution: do economic policy and environmental-related technologies make any difference? Resources Policy, 81, 103361. https://doi.org/10.1016/j.resourpol.2023.103361
  63. Uralovich, K. S., Toshmamatovich, T. U., Kubayevich, K. F., Sapaev, I. B., Saylaubaevna, S. S., Beknazarova, Z. F., & Khurramov, A. (2023). A primary factor in sustainable development and environmental sustainability is environmental education. Caspian Journal of Environmental Sciences, 21(4), 965-975. https://cjes.guilan.ac.ir/article_7155.html
  64. Waheed, R., Chang, D., Sarwar, S., & Chen, W. (2018). Forest, agriculture, renewable energy, and CO2 emission. Journal of Cleaner Production, 172, 4231-4238. https://doi.org/10.1016/j.jclepro.2017.10.287
  65. Wang, K., Yan, M., Wang, Y., & Chang, C. P. (2023). The impact of environmental policy stringency on air quality. Atmospheric Environment, 231, 117522. https://doi.org/10.1016/j.atmosenv.2020.117522
  66. World Bank (2024). Urban population (% of total population). Available at: https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS.
  67. Xin, L., Sun, H., Xia, X., Wang, H., Xiao, H., & Yan, X. (2022). How does renewable energy technology innovation affect manufacturing carbon intensity in China? Environmental Science and Pollution Research, 29(39), 59784-59801. https://doi.org/10.1007/s11356-022-20012-8
  68. Yadav, M., Singh, N. K., Sahu, S. P., & Padhiyar, H. (2022). Investigations on air quality of a critically polluted industrial city using multivariate statistical methods: Way forward for future sustainability. Chemosphere, 291, 133024. https://doi.org/10.1016/j.chemosphere.2021.133024
  69. Yang, S., Jahanger, A., & Hossain, M. R. (2023). How effective has the low-carbon city pilot policy been as an environmental intervention in curbing pollution? Evidence from Chinese industrial enterprises. Energy Economics, 118, 106523. https://doi.org/10.1016/j.eneco.2023.106523
  70. Zambrano-Monserrate, M. A., & Ormeño-Candelario, V. (2023). Disaggregated impact of natural resources rents on the ecological footprint: new evidence from more polluting countries. Mineral Economics, 1-12. https://doi.org/10.1007/s13563-023-00407-w
  71. Zhang, Y., She, J., Long, X., & Zhang, M. (2022). Spatio-temporal evolution and driving factors of eco-environmental quality based on RSEI in Chang-Zhu-Tan metropolitan circle, central China. Ecological Indicators, 144, 109436. https://doi.org/10.1016/j.ecolind.2022.109436

Last update:

No citation recorded.

Last update: 2024-12-11 15:46:22

No citation recorded.