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There are two main ways to reduce anthropogenic GHG emissions: energy efficiency improvement and increase usage of renewable energy sources. Taking these two main ways into account, it is possible to analyze the main drivers of GHG emissions in the country and to make forecast of future GHG emissions based on historical trends. The Visegrad group (V4) countries, including Poland, Hungary, Slovakia, and Czech Republic were selected to provide comparative assessment of their GHG emission drivers and to evaluate effects of climate change mitigation policies in energy sector on GHG emission trends. The Kaya identity approach was applied allowing to perform simple multiplication. Kaya identity equation substitutes the factors with well-established and measurable quantities, which leave little space for ambiguity. The multiplying population size by GDP per capita, energy intensity, and carbon intensity of energy allows to get total GHG emissions in the country and define its energy efficiency or use of renewables are the main drivers of GHG emissions, including the effect of economic growth expressed by GDP per capita. (original abstract)
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Twórcy
autor
- Mykolas Romeris University, Vilnius, Lithuania
Bibliografia
- Allard, A., Takman, J., Sallah Uddin, G., & Ahmed, A. (2018). The N-shaped environmental Kuznets curve`: An empirical evaluation using a panel quantile regression approach. Environmental Science and Pollution Research, 5848-5861. https://doi.org/10.1007/s11356-017-0907-0
- Al-Mulali, U., & Ozturk, I. (2016). The investigation of environmental Kuznets curve hypothesis in the advanced economies: The role of energy prices. Renewable and Sustainable Energy Reviews, 1622-1631. https://doi.org/10.1016/j.rser.2015.10.131
- Apeaning, R. W. (2021). Technological constraints to energy-related carbon emissions and economic growth decoupling: A retrospective and prospective analysis. Journal of Cleaner Production, 291. https://doi.org/10.1016/j.jclepro.2020.125706.
- Ben Jebli, M., Ben Youssef, S., & Ozturk, I. (2016). Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries. Ecological Indicators, 824-831. https://doi.org/10.1016/j.ecolind.2015.08.031
- Bilgili, F., Kocak, E., & Bulut, U. (2016). The dynamic impact of renewable energy consumption on CO2 emissions: A revisited Environmental Kuznets Curve approach. Renewable and Sustainable Energy Reviews, 838-84.
- Brodny, J., & Tutak, M. (2021). The analysis of similarities between the European Union countries in terms of the level and structure of the emissions of selected gases and air pollutants into the atmosphere. Journal of Cleaner Production, 279 https://doi.org/10.1016/j.jclepro.2020.123641.
- Dolge, K., & Blumberga, D. (2021). Economic growth in contrast to GHG emission reduction measures in Green Deal context. Ecological Indicators, 130, 108153. https://doi.org/10.1016/j.ecolind.2021.108153.
- European Commission. (2022). Eurostat [Data set]. https://ec.europa.eu/info/news/eu-energydatasheets-latest-data-now-available-2020-feb-24_en
- Farhani, S., Mrizak, S., Chaibi, A., & Rault, C. (2014). The environmental Kuznets curve and sustainability: A panel data analysis. Energy Policy, 189-198. https://doi.org/10.1016/j.rser.2015.10.080
- Garrett-Peltier, H. (2018). Kuznets, Kaya, and Shapley: The Economic and Energetic Determinants of Carbon Emissions and the Implications for Development and Environmental Policy, Working Paper Number 474, available at https://doi.org/10.7275/27138529.
- González-Torres, M., Pérez-Lombard, L., Coronel, J. F., & Maestre, I. E. R. (2021). Revisiting Kaya Identity to define an emissions indicators pyramid. Journal of Cleaner Production, 317, 128328. https://doi.org/10.1016/j.jclepro.2021.128328.
- Hafner, M., & Paolo, P. (2020). Priorities and challenges of the EU energy transition: From the European Green Package to the new Green Deal. Russian Journal of Economics, 6, 374-389. https://doi.org/10.32609/j.ruje.6.55375.
- Istudor, N., Dinu, V., & Nitescu, D.C. (2021). Influence factors of green energy on EU trade. Transformations in Business & Economics, 20(53), 116-130.
- Karmellos, M., Kopidou, D., & Diakoulaki, D. (2016). A decomposition analysis of the driving factors of CO2 (Carbon dioxide) emissions from the power sector in the European Union countries. Energy, 94, 680-692. https://doi.org/10.1016/j.energy.2015.10.145
- Kulovesi, K., & Oberthür, S. (2020) Assessing the EU's 2030 Climate and energy policy framework: Incremental change toward radical transformation? Review of European, Comparative & International Environmental Law, 29(2), 151-166. https://doi.org/10.1111/reel.12358
- Lima, F., Lopes, M., Cunha, J., & Lucena, F. P. (2016). A cross-country assessment of energy-related CO 2 emissions: An extended Kaya Index decomposition approach. Energy, 115, 1361-1374. https://doi.org/10.1016/j.energy.2016.05.037.
- Liobikienė, G., Butkus, M., & Bernatonienė, J. (2016). Drivers of greenhouse gas emissions in the Baltic states: decomposition analysis related to the implementation of Europe 2020 strategy, Renewable and Sustainable Energy Reviews, 54, 309-317. https://doi.org/10.1016/j.rser.2015.10.028.
- Mahony, T. O. (2013). Decomposition of Ireland's carbon emissions from 1990 to 2010: An extended Kaya identity, Energy Policy, 59, 573-581, https://doi.org/10.1016/j.enpol.2013.04.013
- Mastini, R., Kallis, G., & Hickel, J. (2021). A Green New Deal without growth? Ecological Economics, 179, 106832. https://doi.org/https://doi.org/10.1016/j.ecolecon.2020.106832.
- Ortega-Ruiz, G., Mena-Nieto, A., & García-Ramos, J. E. (2020). Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990-2016. Science of the Total Environment, 737, 139638. https://doi.org/10.1016/j.scitotenv.2020.139638.
- Ramanathan, R. (2006). A multi-factor efficiency perspective to the relationships among world GDP, energy consumption and carbon dioxide emissions. Technological Forecasting and Social Change, 73 (5), 483-494. https://doi.org/10.1016/j.techfore.2005.06.012.
- Rus, A.V., Rovinaru, M.D., Pirvu, M., Bako, E.D., & Rovinaru, F.I. (2020), Renewable energy generation and consumption across 2030 - Analysis and forecast of required growth in generation capacity. Transformations in Business & Economics, 19(50B), 746-766.
- Streimikiene D., & Balezentis T. (2016). Kaya identity for analysis of the main drivers of GHG emissions and feasibility to implement EU "20-20-20" targets in the Baltic States. Renewable and Sustainable Energy Reviews, 58, 1108-1113. https://doi.org/10.1016/j.rser.2015.12.311.
- Su, W., Wang, Y., Streimikiene, D., Balezentis, T., & Zhang, C. (2020). Carbon dioxide emission decomposition along the gradient of economic development: The case of energy sustainability in the G7 and Brazil, Russia, India, China and South Africa. Sustainable Development, 28(4), 657-669. https://doi.org/10.1002/sd.2016
- Tavakoli, A. (2018). A journey among top ten emitter country, decomposition of "Kaya Identity". Sustainable Cities and Society Volume, 38, 254-264. https://doi.org/10.1016/j.scs.2017.12.04
- Wang Q., Zhao M., & R. Li. (2019). Decoupling sectoral economic output from carbon emissions on city level: A comparative study of Beijing and Shanghai, China. Journal of Cleaner Production, 209, 126-133. https://doi.org/10.1016/j.jclepro.2018.10.188.
- Young, H., Seok, Um, J.-S. Hwang, J. H., & Schlüter, S. (2020). Evaluating the Causal Relations between the Kaya Identity Index and ODIAC-Based Fossil Fuel CO2 Flux. Energies 13, 22, 6009. https://doi.org/10.3390/en13226009.
- Zhang, M., Mu, H., Ning, Y., & Song, Y. (2009). Decomposition of energy-related CO2 emission over 1991-2006 in China. Ecological Economics, 68(7), 2122-2128. https://doi.org/10.1016/j.ecolecon.2009.02.005
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171657812