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Understanding the Impact of the Key Determinants of Change in Household Emissions in The European Union: Index Decomposition Analysis

Year 2024, Volume: 9 Issue: 1, 113 - 144, 29.02.2024
https://doi.org/10.25229/beta.1368760

Abstract

Sectoral and household activities are the main drivers of greenhouse gas emissions caused by human activity. Still, household emissions are often overlooked and no concentrated effort is undertaken. However, in order to achieve global climate mitigation and the net zero target, household emissions must be reduced. This study intends to investigate the change in emissions caused by household activities in 27 countries of the European Union, which is a pioneer in emission reduction. In the study, the Log Mean Divisia Index (LMDI) approach is employed to analyse changes in household emissions, which are separated into four major impacts (emission intensity, energy intensity, consumption, and population). The findings show that in most EU-27 countries, emission intensity and energy intensity factors reduce emissions, whereas consumption effect and population effect factors increase emissions and negatively affect household emission reduction performance. In such a case, where final consumption by households per capita increases emissions, interventions focused at guiding consumer behaviour would be preferable. As a result, it is concluded that programmes encouraging sustainable consumption habits, providing incentives for access to low-carbon items, and other similar policies will be appropriate policy practises for EU-27 countries.

Ethical Statement

Çalışmanın, etik kurul izni ve/veya yasal/özel izin gerektirmeyen bir çalışma olduğunu ve akademik etik kurallara uygun olarak yazıldığını beyan ederim

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Avrupa Birliği’nde Hanehalkı Emisyonlarındaki Değişimin Temel Belirleyicilerinin Etkisini Anlamak: İndeks Ayrıştırma Analizi

Year 2024, Volume: 9 Issue: 1, 113 - 144, 29.02.2024
https://doi.org/10.25229/beta.1368760

Abstract

Sektörel faaliyetler ve hanehalkı faaliyetleri, insan faaliyetlerinden kaynaklanan sera gazı emisyonlarının ana etkenleridir. Yine de hanehalkı emisyonları sıklıkla göz ardı edilmekte ve uyumlu bir çaba gösterilememektedir. Ancak küresel iklim azaltımına ve net sıfır hedefine ulaşmak için hanehalkı emisyonlarının azaltılması gerekmektedir. Bu çalışmada emisyon azaltımında öncü olan Avrupa Birliği'ndeki 27 ülkede hanehalklarının faaliyetlerinden kaynaklanan emisyonlardaki değişimin incelenmesi amaçlanmıştır. Logaritmik Ortalama Divisia Endeksi (LMDI) yöntemi, çalışmada dört ana etkiye (emisyon yoğunluğu, enerji yoğunluğu, tüketim, nüfus) ayırılan hanehalkı emisyonlarındaki değişimi analiz etmek için kullanılmaktadır. Elde edilen bulgular, AB-27 ülkelerinin çoğunda, emisyon yoğunluğu ve enerji yoğunluğu faktörlerinin emisyonları azaltıcı etkide bulunduğunu, harcama etkisi ve nüfus etkisi faktörlerinin ise emisyonları artıran ve hanehalklarının emisyon azaltım performansını olumsuz etkileyen iki temel etken olduğunu göstermektedir. Hanehalkının kişi başına nihai tüketiminin emisyonları artırdığı böyle bir durumda, tüketici davranışını yönlendirmeye odaklanan müdahaleler tercih edilebilir. Sonuç olarak sürdürülebilir tüketim alışkanlıklarını teşvik eden, düşük karbonlu ürünlere erişimi teşvik eden programların ve benzeri politikaların AB-27 ülkeleri için uygun politika uygulamaları olacağı sonucuna varılmıştır.

References

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  • Anser, M. K., Alharthi, M., Aziz, B., & Wasim, S. (2020). Impact of urbanization, economic growth, and population size on residential carbon emissions in the SAARC countries. Clean Technologies and Environmental Policy, 22(4), 923–936. https://doi.org/10.1007/S10098-020-01833-Y/FIGURES/3
  • Bataille, C. G. F. (2020). Physical and policy pathways to net-zero emissions industry. Wiley Interdisciplinary Reviews: Climate Change, 11(2). https://doi.org/10.1002/WCC.633
  • Berrill, P., Gillingham, K. T., & Hertwich, E. G. (2021). Drivers of change in US residential energy consumption and greenhouse gas emissions, 1990-2015. In Environmental Research Letters (Vol. 16, Issue 3). IOP Publishing Ltd. https://doi.org/10.1088/1748-9326/abe325
  • Bin, S., & Dowlatabadi, H. (2005). Consumer lifestyle approach to US energy use and the related CO2 emissions. Energy Policy, 33(2), 197–208. https://doi.org/10.1016/S0301-4215(03)00210-6
  • Cansino, J. M., Sánchez-Braza, A., & Rodríguez-Arévalo, M. L. (2015). Driving forces of Spain׳s CO2 emissions: A LMDI decomposition approach. Renewable and Sustainable Energy Reviews, 48, 749–759. https://doi.org/10.1016/J.RSER.2015.04.011
  • Cellura, M., Longo, S., & Mistretta, M. (2012). Application of the Structural Decomposition Analysis to assess the indirect energy consumption and air emission changes related to Italian households consumption. Renewable and Sustainable Energy Reviews, 16, 1135–1145. https://doi.org/10.1016/j.rser.2011.11.016
  • Chen, C., Liu, G., Meng, F., Hao, Y., Zhang, Y., & Casazza, M. (2019). Energy consumption and carbon footprint accounting of urban and rural residents in Beijing through Consumer Lifestyle Approach. Ecological Indicators, 98, 575–586. https://doi.org/10.1016/J.ECOLIND.2018.11.049
  • Chen, G. Q., Wu, X. D., Guo, J., Meng, J., & Li, C. (2019). Global overview for energy use of the world economy: Household-consumption-based accounting based on the world input-output database (WIOD). Energy Economics, 81, 835–847. https://doi.org/10.1016/J.ENECO.2019.05.019
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  • Chen, L., Xu, L., Xia, L., Wang, Y., & Yang, Z. (2022). Decomposition of residential electricity-related CO2 emissions in China, a spatial-temporal study. In Journal of Environmental Management (Vol. 320). Academic Press. https://doi.org/10.1016/j.jenvman.2022.115754
  • Christis, M., Breemersch, K., Vercalsteren, A., & Dils, E. (2019). A detailed household carbon footprint analysis using expenditure accounts – Case of Flanders (Belgium). Journal of Cleaner Production, 228, 1167–1175. https://doi.org/10.1016/J.JCLEPRO.2019.04.160
  • Diakoulaki, D., & Mandaraka, M. (2007). Decomposition analysis for assessing the progress in decoupling industrial growth from CO2 emissions in the EU manufacturing sector. Energy Economics, 29(4), 636–664. https://doi.org/10.1016/J.ENECO.2007.01.005
  • Donglan, Z., Dequn, Z., & Peng, Z. (2010). Driving forces of residential CO 2 emissions in urban and rural China: An index decomposition analysis. Energy Policy, 38, 3377–3383. https://doi.org/10.1016/j.enpol.2010.02.011
  • Duarte, R., Mainar, A., & Sánchez-Chóliz, J. (2013). The role of consumption patterns, demand and technological factors on the recent evolution of CO2 emissions in a group of advanced economies. Ecological Economics, 96, 1–13. https://doi.org/10.1016/j.ecolecon.2013.09.007
  • Duarte, R., Miranda-Buetas, S., & Sarasa, C. (2021). Household consumption patterns and income inequality in EU countries: Scenario analysis for a fair transition towards low-carbon economies. Energy Economics, 104. https://doi.org/10.1016/j.eneco.2021.105614
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  • Dünya Bankası. (2023b). Nüfus (toplam). https://databank.worldbank.org/source/world-development-indicators Eurostat. (2022). NACE Rev. 2 faaliyetine göre hava emisyon hesapları. https://ec.europa.eu/eurostat/databrowser/view/ ENV_AC_AINAH_R2__custom_7251403/default/table
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  • Gill, B., & Moeller, S. (2018). GHG Emissions and the Rural-Urban Divide. A Carbon Footprint Analysis Based on the German Official Income and Expenditure Survey. Ecological Economics, 145, 160–169. https://doi.org/10.1016/J.ECOLECON.2017.09.004
  • Golley, J., & Meng, X. (2012). Income inequality and carbon dioxide emissions: The case of Chinese urban households. Energy Economics, 34(6), 1864–1872. https://doi.org/10.1016/j.eneco.2012.07.025
  • González, P. F., Presno, M. J., & Landajo, M. (2024). Tracking the change in Spanish greenhouse gas emissions through an LMDI decomposition model: A global and sectoral approach. Journal of Environmental Sciences, 139, 114–122. https://doi.org/10.1016/J.JES.2022.08.027
  • Han, L., Xu, X., & Han, L. (2015). Applying quantile regression and Shapley decomposition to analyzing the determinants of household embedded carbon emissions: Evidence from urban China. Journal of Cleaner Production, 103, 219–230. https://doi.org/10.1016/j.jclepro.2014.08.078
  • Hoekstra, R., & van der Bergh, J. J. C. J. M. (2003). Comparing structural decomposition analysis and index. Energy Economics, 25(1), 39–64. https://doi.org/10.1016/S0140-9883(02)00059-2
  • Huo, T., Ma, Y., Yu, T., Cai, W., Liu, B., & Ren, H. (2021). Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China. Environmental Impact Assessment Review, 86. https://doi.org/10.1016/j.eiar.2020.106487
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  • Ivanova, D., Vita, G., Steen-Olsen, K., Stadler, K., Melo, P. C., Wood, R., & Hertwich, E. G. (2017). Mapping the carbon footprint of EU regions. Environmental Research Letters, 12. https://doi.org/10.1088/1748-9326/aa6da9
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Details

Primary Language Turkish
Subjects Green Economy
Journal Section Articles
Authors

Burcu Hiçyılmaz 0000-0003-3501-2012

Early Pub Date February 29, 2024
Publication Date February 29, 2024
Submission Date September 29, 2023
Acceptance Date December 13, 2023
Published in Issue Year 2024 Volume: 9 Issue: 1

Cite

APA Hiçyılmaz, B. (2024). Avrupa Birliği’nde Hanehalkı Emisyonlarındaki Değişimin Temel Belirleyicilerinin Etkisini Anlamak: İndeks Ayrıştırma Analizi. Bulletin of Economic Theory and Analysis, 9(1), 113-144. https://doi.org/10.25229/beta.1368760