Spatial–temporal differentiation and influencing factors of marine fishery carbon emission efficiency in China

Yuan Gao (), Zhongwei Fu (), Jun Yang (), Miao Yu () and Wenhui Wang ()
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Yuan Gao: Liaoning Normal University
Zhongwei Fu: Liaoning Normal University
Jun Yang: Liaoning Normal University
Miao Yu: Liaoning Normal University
Wenhui Wang: Liaoning Normal University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 1, No 17, 453-478

Abstract: Abstract Carbon reduction in marine fisheries plays a role in realizing the “dual carbon” goal. In this study, we measured the marine fishery carbon emission efficiency in the eastern coastal provinces of China from 2008 to 2020. We analyzed the spatial–temporal variation characteristics of marine fishery carbon emission efficiency based on a violin plot and standard deviation ellipse. Additionally, we used ridge regression and fuzzy-set qualitative comparative analysis to study the influencing factors and improvement paths of marine fishery carbon emission efficiency. The results demonstrate that the overall marine fishery carbon emission efficiency in coastal provinces increased from 2008 to 2020. The violin plot evolves from a "double peak" to a "single peak" and the carbon emission efficiency transitions from a low-value range to a high-value range. There is room to improve the carbon emission efficiency of provinces to different degrees. Additionally, the area of standard deviation ellipse of marine fishery carbon emission efficiency fluctuated from 1.46 million km2 in 2008 to 1.45 million km2 in 2020, and the spatial distribution range showed a concentrated trend. The spatial distribution center of carbon emission efficiency mainly moved northward before 2014 and southward after 2014. Regarding the influencing factors, the industrial structure did not pass the significance level, and the employment structure exhibited a negative correlation with the marine fishery carbon emission efficiency with a ridge regression coefficient of − 0.217. The level of economic development, carbon sink capacity, and educational level of technical extension personnel exhibited a positive correlation with the carbon emission efficiency, with ridge regression coefficients 0.034, 0.049, and 0.028, respectively. Furthermore, there were different paths for the low-carbon and green development of marine fisheries in coastal provinces. The individual and combined effects of influencing factors varied according to coastal provinces. Based on the influencing factors, three paths were determined. This study provides relevant recommendations to improve carbon emission efficiency and sustainably develop marine fisheries in China.

Keywords: Marine fishery; Carbon emission efficiency; Spatial–temporal differentiation; Influencing factors; Fuzzy-set qualitative comparative analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-022-02716-6

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