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Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China

机译:基于江苏省延长搅拌模型的农业碳排放促进因素分析

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摘要

STIRPAT (stochastic impact by regression on population, affluence, and technology) model is used to identify the influencing factors of agricultural carbon emissions in Jiangsu province. By referring to Kaya identity and combining with the actual situation of agricultural carbon emissions, four basic influencing factors were obtained: agricultural production efficiency, agricultural structure, agricultural economic development level, and agricultural population size. In addition, urbanization, mechanization, and natural disaster level were listed as influencing factors. The results demonstrated: (a) Urbanization was the first promoting factor of agricultural carbon emissions, indicating a 0.2510% increase in agricultural carbon emissions due to a 1% increase in urbanization. The other three positive factors were, respectively, agricultural mechanization, agricultural structure, and agricultural economic development and their influence indexes were 0.1481, 0.1163, and 0.0845, respectively. (b) Agricultural production efficiency was the most important factor to restrain agricultural carbon emissions. For every 1% increase in agricultural production efficiency, corresponding agricultural carbon emissions would be reduced by 0.3288%. Agricultural population size was also an important factor to reduce agricultural carbon emissions and its influence index was -0.045. Finally, we propose policy recommendations including implementation of orderly urbanization, dependence and development of low carbon technology, establishment of agricultural carbon compensation mechanism, etc.
机译:烤棒(随机影响人口,富裕和技术)模型用于识别江苏省农业碳排放的影响因素。通过提及Kaya身份并结合农业碳排放的实际情况,获得了四种基本影响因素:农业生产效率,农业结构,农业经济发展水平和农业人口规模。此外,城市化,机械化和自然灾害水平被列为影响因素。结果表明:(a)城市化是农业碳排放的第一个促进因素,由于城市化增加1%,农业碳排放量增加0.2510%。另外三个阳性因素分别为农业机械化,农业结构和农业经济发展,其影响指标分别为0.1481,0.1163和0.0845。 (b)农业生产效率是抑制农业碳排放的最重要因素。每次1%的农业生产效率提高,相应的农业碳排放将减少0.3288%。农业人口规模也是减少农业碳排放的重要因素,其影响指数为-0.045。最后,我们提出了政策建议,包括执行有序城市化,低碳技术的依赖和发展,建立农业碳补偿机制等。

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  • 来源
    《Growth and Change》 |2020年第3期|共16页
  • 作者单位

    Chinese Acad Sci Nanjing Inst Geog &

    Limnol Key Lab Watershed Geog Sci Nanjing 210008 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog &

    Limnol Key Lab Watershed Geog Sci Nanjing 210008 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog &

    Limnol Key Lab Watershed Geog Sci Nanjing 210008 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 经济;
  • 关键词

  • 入库时间 2022-08-20 03:17:39

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