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Ecosystem Degradation in Romania: Exploring the Core Drivers

Author

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  • Alexandra-Nicoleta Ciucu-Durnoi

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Camelia Delcea

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

Abstract

The concept of sustainable development appeared as a response to the attempt to improve the quality of human life, simultaneously with the preservation of the environment. For this reason, two of the 17 Sustainable Development Goals are dedicated to life below water (SDG14) and on land (SDG15). In the course of this research, comprehensive information on the extent of degradation in Romania’s primary ecosystems was furnished, along with an exploration of the key factors precipitating this phenomenon. This investigation delves into the perspectives of 42 counties, scrutinizing the level of degradation in forest ecosystems, grasslands, lakes and rivers. The analysis commences with a presentation of descriptive statistics pertaining to each scrutinized system, followed by an elucidation of the primary causes contributing to its degradation. Subsequently, a cluster analysis is conducted on the counties of the country. One of these causes is the presence of intense industrial activity in certain areas, so it is even more important to accelerate the transition to a green economy in order to help the environment regenerate.

Suggested Citation

  • Alexandra-Nicoleta Ciucu-Durnoi & Camelia Delcea, 2024. "Ecosystem Degradation in Romania: Exploring the Core Drivers," Stats, MDPI, vol. 7(1), pages 1-16, January.
    • Handle: RePEc:gam:jstats:v:7:y:2024:i:1:p:6-94:d:1321809
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    References listed on IDEAS

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    3. De Rosa, Michele, 2018. "Land Use and Land-use Changes in Life Cycle Assessment: Green Modelling or Black Boxing?," Ecological Economics, Elsevier, vol. 144(C), pages 73-81.
    4. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
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