Abstract
Environmental problems have been attracting the interest of all relevant parties because of the increasing negative effects on humanity. At this point, further clean, especially nuclear, energy consumption (EC) is seen as a strategic option to combat environmental deterioration (ED). Because clean energy, nuclear energy-related R&D investments (NRD), energy security risk (ESR), as well as increasing economic policy uncertainty (EPU) and trade policy uncertainty (TPU) in recent times have the potential to affect clean EC, this research uncovers the contribution of nuclear EC (NEC) in combating ED by considering also gross domestic product (GDP) and renewable EC (REC) along with the interaction terms of NEC with NRD, ESR, EPU, and TPU. In this vein, the study focuses on the USA case as the biggest economy and leading country in NEC, applies the kernel regularized least squares (KRLS) approach on data from 1974 through 2022, and uses carbon dioxide (CO2) emissions in the main analysis and ecological footprint (EFP) in checking robustness as an ED indicator. The empirical results show that (i) NEC (REC & EPU) is completely ineffective (beneficial) to reduce CO2 emissions; (ii) GDP, ESR, and TPU is almost completely unhelpful to decline CO2 emissions; (iii) the interaction of NRD and EPU with NEC provide a decrease in CO2 emissions; (iv) KRLS approach successfully estimates variations in CO2 emissions around 95%; (v) some variables (e.g., GDP & TPU) have a varying effect across percentiles, whereas others don’t. Thus, the study reveals the efficiency of certain factors (e.g., REC, EPU, interaction of NEC with NRD & EPU) on CO2 emissions, whereas GDP, NEC, ESR, & TPU can’t be helpful to protect the environment. Accordingly, the study argues policy implications (e.g., allocating free/low cost land, ensuring low cost financing support, removing customs-related barriers to import relevant components to install new clean EC capacity in short term, trying to nationally produce clean EC components in long term, ensuring long-term security of rare earth minerals, as well as preventing the displacement between REC and NEC through simultaneously supporting both REC and NEC to appropriately allocating incentives) for USA policymakers.
Data availability
Data will be made available on request.
References
Ali, M. I., Islam, M. M., & Ceh, B. Growth-environment nexus in Canada: Revisiting EKC via demand and supply dynamics. Energy Environ. 0958305X241263833 (2024).
Mehboob, M. Y., Ma, B., Sadiq, M. & Zhang, Y. Does nuclear energy reduce consumption-based carbon emissions: The role of environmental taxes and trade globalization in highest carbon emitting countries. Nucl. Eng. Technol. 56(1), 180–188 (2024).
Lau, L., Choong, C., Ng, C., Liew, F. & Ching, S. Is nuclear energy clean? Revisit of environmental Kuznets curve hypothesis in OECD countries. Econ. Model. 77, 12–20 (2018).
Pan, B., Adebayo, T. S., Ibrahim, R. L. & Al-Faryan, M. A. S. Does nuclear energy consumption mitigate carbon emissions in leading countries by nuclear power consumption? Evidence from quantile causality approach. Energy Environ. 34(7), 2521–2543 (2022).
Murphy, C., Cole, W., Bistline, J., Bragg-Sitton, S., Dixon, B., Eschmann, E., Ho, J., Kwon, A., Martin, L., Namovicz, C., & Sowder, A. Nuclear power’s future role in a decarbonized U.S. electricity system. https://doi.org/10.2172/1988235 (2023).
EIA. U.S. nuclear industry. https://www.eia.gov/energyexplained/nuclear/us-nuclear-industry.php, Accessed on 20 June 2025 (2023).
EIA. U.S. nuclear generating statistics. https://www.eia.gov/todayinenergy/detail.php?id=65104#:~:text=In%202024%2C%20U.S.%20utilities%20operated,generation%20fleet%20in%20the%20world, Accessed on 20 June 2025 (2024).
Kim, S. H., Taiwo, T. A. & Dixon, B. W. The carbon value of nuclear power plant lifetime extensions in the United States. Nucl. Technol. 207(6), 775–790 (2021).
Hassan, S. T., Khan, D., Zhu, B. & Batool, B. Is public service transportation increase environmental contamination in China? The role of nuclear energy consumption and technological change. Energy 238, 121890 (2022).
Majeed, M. T., Öztürk, İ, Samreen, I. & Luni, T. Evaluating the asymmetric effects of nuclear energy on carbon emissions in Pakistan. Nucl. Eng. Technol. 54(5), 1664–1673 (2022).
Bozkaya, Ş, Onifade, S. T. & Duran, M. S. Nuclear energy utilization and the expectations of emission-reduction gains: Empirical evidence from economic trajectory of selected utilizing states. Prog. Nucl. Energy 178, 105526 (2025).
Özcan, B., Kılıç Depren, S. & Kartal, M. T. Impact of nuclear energy and hydro electricity consumption in achieving environmental quality: Evidence from load capacity factor by quantile based non-linear approaches. Gondwana Res. 129, 412–424 (2024).
Jiang, Y., Zhou, Z. & Liu, C. Does economic policy uncertainty matter for carbon emission? Evidence from US sector level data. Environ. Sci. Pollut. Res. 26(24), 24380–24394 (2019).
Song, K., Dai, W. & Bian, Y. Trade policy uncertainty and environmental performance of Chinese enterprises. Struct. Chang. Econ. Dyn. 64, 73–85 (2023).
Chiou, W. J. P., Fu, S. H., Lin, J. B. & Tsai, W. Exploring the impacts of economic policies, policy uncertainty, and politics on carbon emissions. Environ. Resour. Econ. 88(4), 895–919 (2025).
Mandacı, P. E., Çağlı, E. C., Taşkın, D. & Kocakaya, B. T. Quantile-on-quantile connectedness of uncertainty with fossil and green energy markets. Renew. Energy 249, 123235 (2025).
Jaforullah, M. & King, A. Does the use of renewable energy sources mitigate CO2 emissions? A reassessment of the US evidence. Energy Economics 49, 711–717 (2015).
Bhowmik, R., Syed, Q. R., Apergis, N., Alola, A. A. & Gai, Z. Applying a dynamic ARDL approach to the environmental phillips curve (EPC) hypothesis amid monetary, fiscal, and trade policy uncertainty in the USA. Environ. Sci. Pollut. Res. 29(10), 14914–14928 (2022).
Işık, C. et al. Renewable energy, climate policy uncertainty, industrial production, domestic exports/re-exports, and CO2 emissions in the USA: a SVAR approach. Gondwana Res. 127, 156–164 (2024).
Joof, F., Samour, A., Ali, M., Rehman, M. A. & Tursoy, T. Economic complexity, renewable energy and ecological footprint: The role of the housing market in the USA. Energy Build. 311, 114131 (2024).
Kraft, J. & Kraft, A. On the relationship between energy and GNP. J Energy Dev. 3(2), 401–403 (1978).
Grossman, G. M., & Krueger, A. B. Environmental impacts of a North American free trade agreement. NBER Working Paper. No. 3914 (1991).
Payne, J. E. Survey of the international evidence on the causal relationship between energy consumption and growth. J. Econ. Stud. 37(1), 53–95 (2010).
Ali, M. I., Rahaman, M. A., Ali, M. J. & Rahman, M. F. The growth-environment nexus amid geopolitical risks: Cointegration and machine learning algorithm approaches. Discov. Sustain. 6(1), 78 (2025).
Magazzino, C. Ecological footprint, electricity consumption, and economic growth in China: geopolitical risk and natural resources governance. Empirical Econ. 66(1), 1–25 (2024).
Baek, J. & Pride, D. On the income-nuclear energy-CO2 emissions nexus revisited. Energy Econ. 43, 6–10 (2014).
Baek, J. & Kim, H. S. Is economic growth good or bad for the environment? Empirical evidence from Korea. Energy Econ. 36, 744–749 (2013).
Danish, K., Ulucak, R. & Erdogan, S. The effect of nuclear energy on the environment in the context of globalization: Consumption vs production-based CO2 emissions. Nucl. Eng. Technol. 54(4), 1312–1320 (2022).
Al-Mulali, U. Investigating the impact of nuclear energy consumption on GDP growth and CO2 emission: A panel data analysis. Prog. Nucl. Energy 73, 172–178 (2014).
Mahmood, N., Danish, N., Wang, Z. & Zhang, B. The role of nuclear energy in the correction of environmental pollution: Evidence from Pakistan. Nucl. Eng. Technol. 52(6), 1327–1333 (2020).
Ali, M. I., Islam, M. M. & Ceh, B. Interaction between decomposed energy utilization and environmental health in Canada: A cointegration and counterfactual analysis approach. Int. J. Energy Res. 2025(1), 1173970 (2025).
Hicks, J. R. The theory of wages (Macmillan, 1932).
Binswanger, H. P. & Ruttan, V. W. Induced innovation: Technology, institutions, and development. J. Dev. Stud. 14(3), 1–25 (1978).
Griliches, Z. Issues in assessing the contribution of research and development to productivity growth. Bell J. Econ. 92–116 (1979).
Lin, B. & Bai, R. Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective. Res. Int. Bus. Financ. 56, 101357 (2021).
He, Z., Dong, T., Qian, W. & Xu, W. Dynamic interactions among trade policy uncertainty, climate policy uncertainty, and crude oil prices. Int. Rev. Econ. Financ. 95, 103479 (2024).
Grossman, G. M. & Krueger, A. B. Economic growth and the environment. Q. J. Econ. 110(2), 353–377 (1995).
Sadorsky, P. Renewable energy consumption and income in emerging economies. Energy Policy 37(10), 4021–4028 (2009).
Ali, M. I., Islam, M. M. & Ceh, B. Assessing the impact of three emission (3E) parameters on environmental quality in Canada: A provincial data analysis using the quantiles via moments approach. Int. J. Green Energy 22(3), 551–569 (2025).
WB. Data of GDP. https://data.worldbank.org/indicator, Accessed on 21 May 2025 (2025).
IEA. Energy Technology R&D Budgets. https://www.iea.org/data-and-statistics/data-product/energy-technology-rd-and-d-budget-database-2, Accessed on 21 May 2025 (2025).
Islam, M. M., Ali, M. I., & Moniruzzaman, M. Synergy between energy technologies and CO2 emitting goods trade in leading energy-intensive economies: proactive or counterproductive governance? Sustain. Futures, 100950 (2025).
EI. Data of Energy (Including Nuclear and Renewable Energy) Consumption and CO2 Emissions. https://www.energyinst.org/statistical-review/resources-and-data-downloads, Accessed on 21 May 2025 (2025).
GFN. Data of EFP. https://data.footprintnetwork.org, Accessed on 21 May 2025 (2025).
USC. Data of Energy Security Risk. https://www.globalenergyinstitute.org/energy-security-risk-index, Accessed on 21 May 2025 (2025).
www.policyuncertainty.com. Data of Economic Policy Uncertainty and Trade Policy Uncertainty. https://www.globalenergyinstitute.org/energy-security-risk-index, Accessed on 21 May 2025 (2025).
Magazzino, C., Monarca, U., Cassetta, E., Costantiello, A. & Gattone, T. Uncovering CO2 drivers with machine learning in high-and upper-middle-income countries. Energies 18(21), 5552 (2025).
Mehboob, M. Y., Ma, B., Mehboob, M. B. & Zhang, Y. Does green finance reduce environmental degradation? The role of green innovation, environmental tax, and geopolitical risk in China. J. Clean. Prod. 435, 140353 (2024).
Islam, M. M. et al. Renewable and non-renewable energy consumption driven sustainable development in ASEAN countries: Do financial development and institutional quality matter?. Environ. Sci. Pollut. Res. 29(23), 34231–34247 (2022).
Kartal, M. T. Time, frequency, and quantile-based role of R&D investments in energy on sectoral degradation in the United States. Energy Environ. 0958305X241228508 (2024).
Dam, M. M., Naimoğlu, M., & Shahbaz, M. Minimizing Fossil Fuel Energy Losses: The Role of R&D and Nuclear Energy in the United States. J. Clean. Prod. 144819 (2025).
Kartal, M. T., Taşkın, D., Shahbaz, M., Kirikkaleli, D. & Kılıç Depren, S. Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models. J. Environ. Manag. 359, 120971 (2024).
Dickey, D. A. & Fuller, W. A. Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74(366a), 427–431 (1979).
Phillips, P. C. & Perron, P. Testing for a unit root in time series regression. Biometrika 75(2), 335–346 (1988).
Broock, W. A., Scheinkman, J. A., Dechert, W. D. & LeBaron, B. A test for independence based on the correlation dimension. Economet. Rev. 15(3), 197–235 (1996).
Sinha, A., Ghosh, V., Hussain, N., Nguyen, D. K. & Das, N. Green financing of renewable energy generation: Capturing the role of exogenous moderation for ensuring sustainable development. Energy Econ. 126, 107021 (2023).
Hainmueller, J. & Hazlett, C. Kernel regularized least squares: Reducing misspecification bias with a flexible and interpretable machine learning approach. Polit. Anal. 22(2), 143–168 (2014).
Kartal, M. T., Magazzino, C., Taşkın, D., Depren, Ö. & Ayhan, F. Efficiency of green bond, clean energy, oil price, and geopolitical risk on sectoral decarbonization: Evidence from the globe by daily data and marginal effect analysis. Appl. Energy 392, 125963 (2025).
Kartal, M. T., Mukhtarov, S., Depren, Ö., Ayhan, A. & Ulussever, T. How can SDG-13 be achieved by energy, environment, and economy-related policies? Evidence from five leading emerging countries. Sustain. Dev. 33(4), 5110–5133 (2025).
Kartal, M. T., Sharif, A., Magazzino, C., Mukhtarov, S. & Kirikkaleli, D. The Effects of energy transition and environmental policy stringency subtypes on ecological footprint: Evidence from BRICS countries via a KRLS approach. Engineering https://doi.org/10.1016/j.eng.2025.02.007 (2025).
Qianqian, D., Zhen, W., Mehboob, M. Y. & Shehzadi, A. Does green innovation mitigate consumption-based carbon emissions? The role of nuclear energy consumption and energy productivity in G-7 nations. Nucl. Eng. Technol. 57(5), 103384 (2025).
Yi, S., Abbasi, K. R., Hussain, K., Albaker, A. & Alvarado, R. Environmental concerns in the United States: Can renewable energy, fossil fuel energy, and natural resources depletion help?. Gondwana Res. 117, 41–55 (2023).
Usman, O., Ozkan, O., Alola, A. A. & Ghardallou, W. Energy security-related risks and the quest to attain USA’s net-zero emissions targets by 2050: A dynamic ARDL simulations modeling approach. Environ. Sci. Pollut. Res. 31(12), 18797–18812 (2024).
Kartal, M. T., Depren, Ö. & Ayhan, F. Uncovering displacement between nuclear and renewable electricity generation for G7 countries by novel wavelet-based methods. Int. J. Sust. Dev. World 32(2), 186–203 (2025).
Pata, U. K., Kartal, M. T., Mukhtarov, S. & Magazzino, C. Do energy and geopolitical risks influence environmental quality? A quantile-based load capacity factor assessment for fragile countries. Energ. Strat. Rev. 53, 101430 (2024).
Acknowledgements
Not applicable.
Funding
This research has been financed by Servizi Fondo Bombole Metano S.p.A. (Rome, Italy).
Author information
Authors and Affiliations
Contributions
M.T.K. and D.T. wrote Sections 3–4. M.M. and C.M. wrote Sections 1, 2, and 5. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Consent for publication
The authors are willing to permit the Journal to publish the article.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Kartal, M.T., Taşkın, D., Mele, M. et al. Marginal effect of clean energy, nuclear energy-related R&D investment, energy security risk, and policy uncertainty on the environment in the USA. Sci Rep (2026). https://doi.org/10.1038/s41598-026-36312-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-36312-9