Spatiotemporal variations of cultivated land use efficiency in the Yangtze River Economic Belt based on carbon emission constraints

被引:70
作者
Luo Xiang [1 ]
Ao Xinhe [1 ]
Zhang Zuo [1 ]
Wan Qing [2 ]
Liu Xingjian [3 ]
机构
[1] Cent China Normal Univ, Coll Publ Adm, Wuhan 430079, Peoples R China
[2] Wuhan Inst Technol, Sch Management, Wuhan 430205, Peoples R China
[3] Univ Hong Kong, Dept Urban Planning & Design, Hong Kong 999077, Peoples R China
基金
中国国家自然科学基金;
关键词
Yangtze River Economic Belt; carbon emissions; cultivated land use efficiency; Tobit model; ENERGY EFFICIENCY; CROP PRODUCTION; CHINA; AGRICULTURE; TILLAGE; SEQUESTRATION; URBANIZATION; PRODUCTIVITY; VARIABILITY; PROTECTION;
D O I
10.1007/s11442-020-1741-8
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
In this study, the carbon emissions (CEs) from cultivated land (CL) were included as an undesirable output in the utilization efficiency of such land. A slack-based model was used to calculate the CL use efficiency (CLUE) for 11 provinces and cities in the Yangtze River Economic Belt (YREB) from 2007 to 2016, and then a kernel density estimation map was drawn to analyze the spatiotemporal variations of CLUE. The Tobit model was also employed to analyze the factors affecting the CLUE. The results show the following. 1) In the YREB, the CEs from CL showed a rising and then a slowly decreasing trend. In this paper, we calculate CEs by carbon emission factors and major carbon sources, and the CEs from CL in the YREB totaled 25.2354 million tons in 2007. By 2014, the value had increased gradually to 28.4400 million tons, and by 2016 it had declined to 27.8922 million tons, suggesting that the carbon-emission reduction measures of the government had an impact. 2) The CLUE of various provinces and cities in the YREB showed an upward trend in the time dimension, while for the spatial dimension, the kernel density was high in the east and low in the west, and the areas with high kernel density were mainly located in the Yangtze River Delta. 3) The per capita gross domestic product, the primary industrial output, and the number of agricultural technicians per 10,000 people had positive effects on the CLUE. The CL area per capita and the electrical power per hectare for agricultural machinery had significant negative impacts on CLUE. In addition, every 1% increase in the number of agricultural technicians increased the CLUE by 0.057%.
引用
收藏
页码:535 / 552
页数:18
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