Hidroelektrik Enerji Tüketiminin Çevre Üzerine Etkisinin Sürekli Dalgacık Uyumu Modeli ile Araştırılması: ABD Örneği

Yıl 2020, Sayı: 55, 263 - 284, 27.04.2020

Sevda Kuşkaya , Faik Bilgili

https://doi.org/10.18070/erciyesiibd.565196

Cited By: 1

Öz

Küresel ısınma en önemli çevre sorunlarının başında gelmektedir. Küresel ısınmanın temel nedenlerinden birisi, fosil yakıt kullanımı neticesinde oluşan CO2 emisyonudur. Hem bu soruna çözüm getirmek hem de enerji kaynaklarının kısıtlı olması, toplumları fosil yakıt kullanımına alternatif olabilecek enerji kaynaklarını kullanmaya yöneltmiştir. Bu durum ise yenilenebilir enerjilerin CO2 emisyonu üzerindeki etkilerinin belirlenmesini gündeme getirmiştir.

Bu çalışmada yenilenebilir enerji kaynaklarından, hidroelektrik enerji kullanımı ile CO2 emisyonu arasındaki ilişki, ABD için incelenmiştir. Araştırmada analiz yöntemi olarak dalgacık uyumu (wavelet coherence) yöntemlerinden birisi olan Morlet dalgacık uyumu modeli kullanılmıştır. Analiz değişkenleri; hidroelektrik enerji tüketimi, toplam biyokütle enerji tüketimi, sanayi üretim endeksi (SÜE), toplam fosil yakıt tüketimi, nükleer enerji tüketimi ve toplam CO2 emisyonu şeklinde belirlenmiştir. Analiz neticesinde hidroelektrik kullanımının (TBiyokütle, TFosil, Nükleer ve SÜE kontrol değişken iken) 2015:1-2015:12 döneminde, CO2 emisyonunu azalttığı tespit edilmiştir.

Anahtar Kelimeler

Küresel Isınma, Çevre Kirliliği, CO2 Emisyonu, Hidroelektrik Enerji, Morlet Dalgacık Uyumu

Destekleyen Kurum

Erciyes Üniversitesi BAP Doktora

Proje Numarası

SDK-2017-7332

Investigation of The Effect of Hydroelectric Energy Consumption on The Envıronment by Using A Continuous Wavelet Coherence Model: Case of Usa

Öz

Global warming is the most important environmental problems. The most important reason for global warming is the CO2 emission resulting from the use of fossil fuels. Both the solution to this problem and the limited resources of energy have led the societies to use the energies that could be an alternative to the use of fossil fuels. This situation necessitated the determination of the effects of renewable energies on CO2 emissions.

In this paper, the relationship between the carbon dioxide (CO2) emission of hydroelectric energy use, which is one of the renewable energy source, has been examined for USA. Morlet wavelet coherence model which is one of the wavelet coherence methods has been used as the method of analysis. In the analysis, hydroelectric energy consumption, total biomass energy consumption, industrial production index, total fossil fuel consumption, nuclear energy consumption and total CO2 emission were preferred as variables. As a result of the analysis, it was determined that the use of hydroelectricity (while TBiomass, TFossil, Nuclear and IP were control variable) decreased the CO2 emission in the 1 ~ 3 frequency band, 2015: 1-2015: 12 period. In this context, it is foreseen that more efficient production can be achieved from hydroelectric energy in terms of CO2 emission.

Anahtar Kelimeler

Global Warming, Environmental Pollution, CO2 Emission, Hydroelectric Energy, Morlet Wavelet Coherence

Proje Numarası

SDK-2017-7332

Kaynakça

• Acaroğlu, M. (2007), Alternatif enerji kaynakları, 2. Baskı, Nobel Yayıncılık, Ankara.
• Addison, P. S. (2002), The illustrated wavelet transform handbook introductory theory and application in science. Engineering. Medicine and Finance, (1st Edition). Taylor&Francis Group, CRS Press.
• Aguiar-Conraria, L., Magalhães P.C. ve Soares, M.J. (2013), The nationalization of electoral cycles in the United States: a wavelet analysis. Public Choice, 156 (3-4), 387–408.
• Akhmat, G., K. Zaman, T. Shukui, D. İrfan ve M. M. Khan, (2014), Does energy consumption contribute to environmental pollutants? evidence from SAARC countries. Environmental Science and Pollution Research, 21 (9), 5940-5951.
• Ang, J. B. (2007). CO2 emissions energy consumption and output in France. Energy Policy, 35, 4772-4778.
• Apergis, N., E. J. Payne, K. Menyah ve Rufael, W. Y. (2010). On the cousal dynamics between emissions, nuclear energy, renewable energy and economic growth. Ecological Economics, 69, 2255-2260.
• Arı, N., Özen, Ş. ve Özen, Ö.H. (2008), Dalgacık Teorisi (Wavelet). Ankara: Palme.
• Arouri, M. E., A. B. Youssef, M’henni H., ve Rault, C. (2012). Energy consumption, economic growth and co2 emissions in Middle East and North African Countries. Energy Policy, 45, 342-345.
• Bayraç, H. N. (2011). Enerji Kullanımının Küresel Isınmaya Etkisi ve Önleyici Politikalar. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 2(11), 229-260. http://dergipark.gov.tr/download/article-file/113309.
• Bhattacharjee, A. (2012). Everything You Need to Know About The Types of Renewable Energy, Brainmass Inc.
• Bilgili, F. (2012). The impact of biomass consumption on co2 emissions: cointegration analyses with regime shifts. Renewable and Sustainable Energy Reviews, 16, 5349-5354.
• Bilgili, F., İ. Öztürk, E. Koçak, Ü. Bulut, Y. Pamuk, E. Muğaloğlu ve Bağlıtaş, H.H. (2016). The influence of biomass energy consumption on CO2 emissions: a wavelet coherence approach. Environmental Science and Pollution Research, 23 (19), 19043-19061.
• Burrus, C.S., Gopinath, R.A. ve Guo, H. (1998). Introduction to wavelets and wavelet transforms a primer. New Jersey: Prentice Hall.
• EIA 2017, U.S. Energy Information Administration, Independent Statistics and Analysis, International https://www.eia.gov/totalenergy/data/ monthly/index.php (Erişim Tarihi: 11.12.2017).
• EPA, U.S. Environmental Protection Agency (2015), Inventory of US. Greenhouse Gas Emissions and Sinks:1990-2013, USA.
• Europa 2018, Fossil CO2 & GHG emissions of all world countries, 2017. http ://edgar.jrc.ec.europa.eu/overview.php?v=CO2andGHG1970-2016&sort= des9.
• Farge, M. (1992). Wavelet transforms and their applications to turbulence. Annual Reviews, 24, 395-457.
• Gençay R., Selçuk, F. ve Whitcher, B. (2002). An ıntroduction to wavelets and other filtering methods in finance and economics, San Diego: Academic.
• Graps, A. (1995). An ıntroduction to wavelets. IEEE Computational Science and Engineering, 2, 50-51.
• Gul, S., X. Zou, C. H. Hassan, M. Azam ve Zaman, K. (2015). Casual nexus between energy consumption and carbon dioxide emission for Malaysia using maximum entropy bootstrap approach. Environmental Science Pollution Research, 22 (24), 19773-19785.
• Halıcıoğlu, F. (2009). An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey. Energy Policy, 37, 1156-1164.
• Hossain, M. S. (2011). Panel estimation for CO2 emissions, energy consumption, economic growth, trade, openness and urbanization of newly industrialized countries. Energy Policy, 39, 6991-6999.
• Hudgins L., Friehe CA. ve Mayer ME. (1993). Wavelet transform and atmospheric turbulence. Physical Review Letters, 71 (20), 3279-3282.
• IPCC. Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel On Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)], Cambridge University Press, Camridge, United Kingdom and New York, NY, USA, 2013.
• Karl, TR., Melillo, JM ve Peterson, TC. (2009). Global climate change impacts in the United States: a state of knowledge report. Cambridge University Press, Cambridge.
• Kuşkaya, S.ve Gençoğlu, P. (2017). OECD ülkelerinin 1995-2015 yılları itibariyle sera gazı emisyonları açısından karşılaştırılması: istatistiksel bir analiz. International Journal of Disciplines Economics & Administrative Sciences Studies, 3 (3), 177-188.
• Lee, S. and Chang, W. O. (2016). Causal relationship of energy consumption, price and CO2 emissions in the us-building sector. Resources, Conservation and Recycling, 107, 220-226.
• Liaskas, K., Mavrotas, G., Mandaroke, M. ve Diakoulaki, D. (2000). Decomposition of industrial CO2 emissions: the case of European Union. Energy Economics, 22, 383-394.
• Mitchell, J. F.B. (1989). The Greenhouse Effect and Climate Change. Reviews of Geophysics, 27 (1), 115-139. doi: https://doi.org/10.1029/RG027i001p00115.
• NewScientist, (2018), Hydroelectric power's dirty secret revealed, https://www.newscientist.com/article/mg18524884-100-hydroelectric-powers-dirty-secret-revealed/
• Sorensen, T.C. (2016). Global Warming and Impacts on Climate of India, https://www.researchgate.net/profile/S_Sarvade/post/What_is_the_impact_of_global_warming_on_the_environment/attachment/59d64bf079197b80779a5db0/AS%3A482366322941955%401492016501665/download/3113.pdf.pdf .
• Tuna, M. (2000). Çevresel Sorunların Küreselleşmesi. Muğla Üniversitesi SBE Dergisi, 1(2), 1-16. http://dergipark.gov.tr/download/article-file/217462.
• Utlu, Z. (2007). Evaluation of biodiesel fuel obtained from waste cooking oil. Energy Sources, Part A, 29, 1295-1304.
• Vacha, L. ve Barunik, J. (2012). Co-movement of energy commodities revisited: evidence from wavelet coherence analysis. Energy Economics, 34 (1), 241-247.
• Zhao, G., Jiang, D., Diao, J. ve Qian, L. (2004). Application of wavelet time-frequency analysis on fault diagnosis for steam turbine, In:5th International Conference of Acoustical and Vibratory Surveillance Methods and Diagnostic Techniques, France, CETIM.