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Articles | Volume XLVIII-4/W9-2024
https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-61-2024
https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-61-2024
08 Mar 2024
 | 08 Mar 2024

BIBLIOMETRIC ANALYSIS OF THE GREATEST NUCLEAR DISASTERS: WHAT IS KNOWN SO FAR AND WHAT ARE THE PROSPECTS?

M. Batur and R. M. Alkan

Keywords: Bibliometric analysis, Chernobyl, Fukushima, Nuclear Disaster Management, Spatial Analysis

Abstract. The high potential of nuclear power to combat climate change and support sustainable development plays a critical role in achieving the goal of the Paris Agreement. Moreover, with the ever-increasing demand for electricity, it is essential to consider nuclear power as a reliable source of energy. However, it should be noted that although the risk of a radiological accident is small, it always exists, and therefore it is crucial to have a complete understanding of the management of nuclear power. Herein, we present a statistical review of nuclear accident research at Chernobyl and Fukushima Nuclear Power Plants using bibliometric analysis to identify key patterns in scientific results and current issues in accident research. More than 10,000 articles have been collected from the SCOPUS database covering the periods 1986–2022 and 2011–2022 on Chernobyl and Fukushima, respectively. The results were obtained from two perspectives: first, we identified stages through which pre- and post-accident researches have evolved, and then we analysed the spatial correlation between energy-economic performance and scientific literature for the leading productive countries. From the analysis of research trends, it was found that the number of articles increased sharply immediately after the accident and slightly decreased over time. Among the most attractive subject categories in terms of the largest number of publications and received citations were environmental sciences, medicine and energy policy. The productive country ranking was mostly topped by the country in which the accident occurred. Spatial statistical analysis revealed a strong correlation between the scientific productivity and energy-economic performance of the leading countries.