Regional differences of agricultural total factor carbon efficiency in China

Xiuquan Huang, Tao Zhang (), Xi Wang, Jiansong Zheng, Guoli Xu and Xiaoshan Wu
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Xiuquan Huang: Nanjing University of Chinese Medicine
Tao Zhang: Macao Polytechnic University
Xi Wang: Macao Polytechnic University
Jiansong Zheng: Macao Polytechnic University
Guoli Xu: Macao Polytechnic University
Xiaoshan Wu: Macao Polytechnic University

Palgrave Communications, 2024, vol. 11, issue 1, 1-12

Abstract: Abstract China’s agriculture has struggled over the past century to produce more food to feed the country’s expanding population while also contending with high-intensity pollution. In order to support China’s transition to low-carbon agriculture more efficiently, it is important to improve the efficiency of agricultural carbon emissions. This study employs the biennial weight modified Russell model to investigate China’s agricultural total factor carbon efficiency (ATFCE) during 1999–2018 and its differences between the three agricultural functional zones (AFZs), including the grain-producing zone (GPZ), the grain balance zone (GBZ), and the main grain-selling zone (GSZ). The study found that the ATFCE in China was 0.761, a high value. GSZ (0.9865) had the highest ATFCE, followed by GBZ (0.7201) and GPZ (0.6666). ATFCE in China fell by approximately 25%, from 0.825 in 1999 to 0.6983 in 2018. Further, the provinces with the highest ATFCE included Tibet (0.9997), Hainan (0.9981), Shanghai (0.997), Beijing (0.9937), and Jiangsu (0.9924). Provinces with the lowest ATFCEs included Hubei (0.4743), Yunnan (0.4645), Hunan (0.441), Anhui (0.4295), Heilongjiang (0.4130), and Jiangxi (0.3354). In addition, the difference in ATFCE within the whole of China, GPZ, and GBZ generally widened during 1999–2018. There was a rise in all three inequalities between the three AFZs. The difference between GPZ and GBZ was the greatest among the three interregional differences. Finally, the difference between subregions was the largest source of the total difference (43.66%), followed by the difference within subregions (30.04%) and the intensity of transvariation (25.94%).

Date: 2024
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DOI: 10.1057/s41599-024-03296-8

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