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Is the Ratoon Rice System More Sustainable? An Environmental Efficiency Evaluation Considering Carbon Emissions and Non-Point Source Pollution

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Listed:
  • Hui Qiao

    (Rural Development Institute, Chinese Academy of Social Sciences, Beijing 100732, China)

  • Mingzhe Pu

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Ruonan Wang

    (Research Institute for Eco-Civilization, Sichuan Academy of Social Sciences, Chengdu 610072, China)

  • Fengtian Zheng

    (School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China)

Abstract

The sustainability of rice-cropping systems hinges on balancing resources, output, and environmental impacts. China is revitalizing the ancient ratoon rice (RR) system for input savings and environmental benefits. Prior research has explored the RR system’s performance using various individual indicators, but few studies have focused on its overall balance of these factors. Environmental efficiency (EE) analysis addresses this gap. Using field survey data from Hunan Province in China and the slacks-based data envelopment analysis method, we quantified the EE of the RR, double-season rice (DR), and single-season rice (SR) systems. Key findings include: (1) the RR system outperforms in carbon emissions and non-point source pollution; (2) the RR system’s EE is 0.67, significantly higher than the DR (0.58) and SR (0.57) systems, indicating superior performance; and (3) despite its relatively high EE, the RR system can still improve, mainly due to input redundancy and production value shortfall. These findings provide strategies for optimizing RR systems to enhance agricultural sustainability.

Suggested Citation

  • Hui Qiao & Mingzhe Pu & Ruonan Wang & Fengtian Zheng, 2024. "Is the Ratoon Rice System More Sustainable? An Environmental Efficiency Evaluation Considering Carbon Emissions and Non-Point Source Pollution," Sustainability, MDPI, vol. 16(22), pages 1-17, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9920-:d:1520694
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    References listed on IDEAS

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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Ghisellini, Patrizia & Zucaro, Amalia & Viglia, Silvio & Ulgiati, Sergio, 2014. "Monitoring and evaluating the sustainability of Italian agricultural system. An emergy decomposition analysis," Ecological Modelling, Elsevier, vol. 271(C), pages 132-148.
    3. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    4. Kashyap, Durba & Agarwal, Tripti, 2021. "Carbon footprint and water footprint of rice and wheat production in Punjab, India," Agricultural Systems, Elsevier, vol. 186(C).
    5. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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