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Dergiler / Black Sea Journal of Engineering and Science / 2026 / Cilt: 9 Sayı: 3

Determinants of CO₂ Emissions in the Balkans, Black Sea, and Caucasus Region: Evidence from Panel ARDL–PMG and DCCE Models

Tuğba Özyıldız(GAZİANTEP ÜNİVERSİTESİ)0000-0002-2101-2954
Sayfa
1329–1337
Yayın Tarihi
2026-05-15
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Overall, the results indicate a need for greater emphasis on renewable energy, sustainable urban planning, better water management, and more environmentally friendly aquaculture practices.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:This study examines the determinants of carbon dioxide (CO₂) emissions in 12 countries from the Balkans, Black Sea, and Caucasus region over the period 1990–2024.
📊
Temel Bulgular & Veri:The results show that population density, electricity consumption, and freshwater withdrawal increase CO₂ emissions in the long run.
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Sonuç & Katkı:Overall, the results indicate a need for greater emphasis on renewable energy, sustainable urban planning, better water management, and more environmentally friendly aquaculture practices.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2024 Verileri
⚙️Değişkenler:Carbon emissions · Electricity consumption · Freshwater withdrawal

Özet

This study examines the determinants of carbon dioxide (CO₂) emissions in 12 countries from the Balkans, Black Sea, and Caucasus region over the period 1990–2024. It extends the literature by including freshwater withdrawal and aquaculture production as explanatory variables. The study also controls for GDP, population density, and electricity consumption as additional covariates. In doing so, the study proposes resource related determinants of on environmental pressure. The analysis uses annual panel data from the World Development Indicators database of the World Bank. To account for cross-sectional dependence and mixed orders of integration, the study applies a panel ARDL–PMG model. The Dynamic Common Correlated Effects(DCCE) estimator is also used as a robustness check. The results show that population density, electricity consumption, and freshwater withdrawal increase CO₂ emissions in the long run. In the short run, GDP and electricity consumption have positive and statistically significant effects on emissions. The DCCE estimates also show the positive effect of electricity consumption and a weaker positive effect of population density. They indicate a positive association between aquaculture production and emissions. In both estimation, the Environmental Kuznets Curve hypothesis is not supported. Overall, the findings suggest that environmental pressure is linked to energy use, population density, and resource usage in the sampled countries. Overall, the results indicate a need for greater emphasis on renewable energy, sustainable urban planning, better water management, and more environmentally friendly aquaculture practices.

Abstract

This study examines the determinants of carbon dioxide (CO₂) emissions in 12 countries from the Balkans, Black Sea, and Caucasus region over the period 1990–2024. It extends the literature by including freshwater withdrawal and aquaculture production as explanatory variables. The study also controls for GDP, population density, and electricity consumption as additional covariates. In doing so, the study proposes resource related determinants of on environmental pressure. The analysis uses annual panel data from the World Development Indicators database of the World Bank. To account for cross-sectional dependence and mixed orders of integration, the study applies a panel ARDL–PMG model. The Dynamic Common Correlated Effects(DCCE) estimator is also used as a robustness check. The results show that population density, electricity consumption, and freshwater withdrawal increase CO₂ emissions in the long run. In the short run, GDP and electricity consumption have positive and statistically significant effects on emissions. The DCCE estimates also show the positive effect of electricity consumption and a weaker positive effect of population density. They indicate a positive association between aquaculture production and emissions. In both estimation, the Environmental Kuznets Curve hypothesis is not supported. Overall, the findings suggest that environmental pressure is linked to energy use, population density, and resource usage in the sampled countries. Overall, the results indicate a need for greater emphasis on renewable energy, sustainable urban planning, better water management, and more environmentally friendly aquaculture practices.

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Bu Makaleye Atıf Yap

Özyıldız, T. (2026). Determinants of CO₂ Emissions in the Balkans, Black Sea, and Caucasus Region: Evidence from Panel ARDL–PMG and DCCE Models. Black Sea Journal of Engineering and Science, Cilt: 9 Sayı: 3, 1329–1337. https://doi.org/10.34248/bsengineering.1907493

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Kaynakça (37)

  1. Ahmed, N., Thompson, S., & Glaser, M. (2019). Global aquaculture productivity, environmental sustainability, and climate change adaptability. Environmental Management, 63(2), 159–172.
  2. Apergis, N., & Payne, J. E. (2014). Renewable energy, output, CO2 emissions, and fossil fuel prices in Central America: Evidence from a nonlinear panel smooth transition vector error correction model. Energy Economics, 42, 226–232.
  3. Balsalobre-Lorente, D., Shahbaz, M., Roubaud, D., & Farhani, S. (2018). How economic growth, renewable electricity and natural resources contribute to CO2 emissions?. Energy Policy, 113, 356–367.
  4. Copeland, C., & Carter, N. T. (2014, January). Energy-water nexus: The water sector's energy use. Library of Congress, Congressional Research Service.
  5. Dinda, S. (2004). Environmental Kuznets curve hypothesis: A survey. Ecological Economics, 49(4), 431–455. https://doi.org/10.1016/j.ecolecon.2004.02.011
  6. Dogan, E., & Inglesi-Lotz, R. (2020). The impact of economic structure to the environmental Kuznets curve (EKC) hypothesis: evidence from European countries. Environmental Science and Pollution Research, 27(11), 12717–12724.
  7. Fang, D., & Chen, B. (2017). Linkage analysis for the water–energy nexus of city. Applied Energy, 189, 770–779. https://doi.org/10.1016/j.apenergy.2016.12.020
  8. Flint, S. S., Lauerwald, R., Raymond, P. A., & Regnier, P. (2025). Anthropogenic water withdrawals modify freshwater inorganic carbon fluxes across the United States. Nature Communications, 16(1), Article 316. https://doi.org/10.1038/s41467-024-55447-0
  9. Grossman, G. M., & Krueger, A. B. (1995). Economic growth and the environment. The Quarterly Journal of Economics, 110(2), 353–377.
  10. Gujarati, D. N., & Porter, D. C. (2009). Basic econometrics (5. bs.). McGraw-Hill.
  11. Guliyev, H., & Seyfullayev, I. (2025). Is the environmental Kuznets curve hypothesis valid for all countries? Fresh insights from bias-corrected dynamic panel data models. Journal of Environmental Management, 393, Article 126960.
  12. Guo, X., & Shahbaz, M. (2024). The existence of environmental Kuznets curve: Critical look and future implications for environmental management. Journal of Environmental Management, 351, Article 119648.
  13. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the Econometric Society, 46(6), 1251–1271.
  14. Hong, S., Hui, E. C. M., & Lin, Y. (2022). Relationships between carbon emissions and urban population size and density, based on geo-urban scaling analysis: a multi carbon source empirical study. Urban Climate, 46, Article 101337.
  15. Kakar, S. K., Ali, J., Wang, J., Wu, X., Arshed, N., Le Hien, T. T., & Yadav, R. S. (2024). Exploring the impact of industrialization and electricity use on carbon emissions: The role of green FinTech in Asian countries using an asymmetric panel quantile ARDL approach. Journal of Environmental Management, 370, Article 122970.
  16. Liddle, B. (2014). Impact of population, age structure, and urbanization on carbon emissions/energy consumption: evidence from macro-level, cross-country analyses. Population and Environment, 35(3), 286–304.
  17. MacLeod, M. J., Hasan, M. R., Robb, D. H., & Mamun-Ur-Rashid, M. (2020). Quantifying greenhouse gas emissions from global aquaculture. Scientific Reports, 10(1), Article 11679.
  18. Maziotis, A., Sala-Garrido, R., Mocholi-Arce, M., & Molinos-Senante, M. (2024). Understanding water-energy-carbon nexus in English and Welsh water industry by assessing eco-productivity of water companies. npj Clean Water, 7(1), Article 121.
  19. Munir, K. (2023). Energy use and environmental degradation in Europe: evidence from panel nonlinear ARDL. Quality & Quantity, 57(3), 2529–2543.
  20. Panayotou, T. (1993). Empirical tests and policy analysis of environmental degradation at different stages of economic development (Working Paper No. WP238; Technology and Employment Programme, Cilt 4). International Labour Office.
  21. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of Applied Econometrics, 22(2), 265–312.
  22. Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79–113.
  23. Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621–634.
  24. Pickson, R. B., Gui, P., Jian, L., & Boateng, E. (2024). Do population-related factors matter for carbon emissions? Lessons from different income groups of countries. Urban Climate, 55, Article 101934.
  25. Qin, J., Duan, W., Zou, S., Chen, Y., Huang, W., & Rosa, L. (2024). Global energy use and carbon emissions from irrigated agriculture. Nature Communications, 15(1), Article 3084.
  26. Ray, N. E., Bonaglia, S., Cavan, E. L., Sampaio, F. G., Gephart, J. A., Hillman, J. R.,. & Yuan, J. (2025). Biogeochemical consequences of marine fisheries and aquaculture. Nature Reviews Earth & Environment, 6(3), 163–177.
  27. Sadorsky, P. (2014). The effect of urbanization on CO2 emissions in emerging economies. Energy Economics, 41, 147–153.
  28. Sarkodie, S. A., & Strezov, V. (2019). A review on environmental Kuznets curve hypothesis using bibliometric and meta-analysis. Science of the Total Environment, 649, 128–145.
  29. Seto, K. C., Dhakal, S., Bigio, A., Blanco, H., Carlo Delgado, G., Dewar, D.,. & Zwickel, T. (2014). Human settlements, infrastructure, and spatial planning. In IPCC Fifth Assessment Report. Intergovernmental Panel on Climate Change.
  30. Shahbaz, M., Balsalobre-Lorente, D., & Sinha, A. (2019). Foreign direct Investment–CO2 emissions nexus in Middle East and North African countries: Importance of biomass energy consumption. Journal of Cleaner Production, 217, 603–614.
  31. Shen, L., Wu, L., Wei, W., Yang, Y., MacLeod, M. J., Lin, J.,. & Zhuang, M. (2024). Marine aquaculture can deliver 40% lower carbon footprints than freshwater aquaculture based on feed, energy and biogeochemical cycles. Nature Food, 5(7), 615–624.
  32. Stern, D. I. (2004). The rise and fall of the environmental Kuznets curve. World Development, 32(8), 1419–1439. https://doi.org/10.1016/j.worlddev.2004.03.004
  33. Yateh, M., Li, F., Tang, Y., Li, C., & Xu, B. (2024). Energy consumption and carbon emissions management in drinking water treatment plants: A systematic review. Journal of Cleaner Production, 437, Article 140688.
  34. Zhou, Z., Cao, L., Zhao, K., Li, D., & Ding, C. (2021). Spatio-temporal effects of multi-dimensional urbanization on carbon emission efficiency: analysis based on panel data of 283 cities in China. International Journal of Environmental Research and Public Health, 18(23), Article 12712.
  35. Ray, N. E., Bonaglia, S., Cavan, E. L., Sampaio, F. G., Gephart, J. A., Hillman, J. R.,. & Yuan, J. (2025). Biogeochemical consequences of marine fisheries and aquaculture. Nature Reviews Earth & Environment, 6(3), 163–177.
  36. Seto, K. C., Dhakal, S., Bigio, A., Blanco, H., Carlo Delgado, G., Dewar, D.,. & Zwickel, T. (2014). Human settlements, infrastructure, and spatial planning. In IPCC Fifth Assessment Report. Intergovernmental Panel on Climate Change.
  37. Shen, L., Wu, L., Wei, W., Yang, Y., MacLeod, M. J., Lin, J.,. & Zhuang, M. (2024). Marine aquaculture can deliver 40% lower carbon footprints than freshwater aquaculture based on feed, energy and biogeochemical cycles. Nature Food, 5(7), 615–624.