| 摘要: |
| ［目的］我国区域农业发展模式由于气候、环境的不同存在较大的差异，而目前针对农业隐含碳的时空动态研究较为缺乏，导致对于区域减排目标的设定缺乏全面的考虑，无法实现农业碳减排的效率性和公平性。因此，有必要分析农业隐含碳排放在不同省域的特征并分析其驱动因素，为制定体现地区间公平性且有效率的碳减排政策提供依据。［方法］文章利用2002年、2007年和2012年 3年的投入产出表估算我国各省（市、区）农业隐含碳排放量，根据Kaya恒等关系将其分解为经济规模、经济结构、一般农业技术进步和低碳农业技术进步4类影响因素，并利用LMDI分解分析法对这4类影响因素的驱动力进行了分析。［结果］2002—2012年我国大部分地区农业隐含碳排放量呈上升趋势，空间上呈现从西到东、从南到北逐渐增加的分布规律，经济规模效应在各省份均呈正向驱动，且在经济发展较为迅速、经济增长后劲较强的地区驱动效应逐渐增强； 经济结构效应在大部分省份呈负向驱动，且在重型工业的聚集区域负向效应逐渐增强； 一般农业技术因素正向驱动区域逐渐扩散，且在农业大省正向驱动效应逐渐增强； 低碳农业技术进步因素在东部发达地区负向的驱动效应较强，在西部驱动效应较弱。［结论］在未来的农业减排政策制定过程中，需要充分考虑不同地区的经济发展、产业结构、农业生产等特点。 |
| 关键词: 农业隐含碳碳排放LMDI分解驱动因素时空动态 |
| DOI： |
| 分类号:S-9 |
| 基金项目:国家社会科学基金青年项目“中国区域间农业隐含碳排放补偿机制与减排路径研究”(16CJL35) |
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| SPATIAL DYNAMICS OF AGRICULTURAL EMBODIED CARBON EMISSIONS IN PROVINCES OF CHINA AND THE RELATED DRIVING FACTORS |
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Shi Junhui1, Dai Xiaowen2
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1.College of Management, Sichuan Agricultural University, Chengdu 611130, Sichuan, China;2.Sichuan Rural Development Research Center, College of Management, Sichuan Agricultural University , Chengdu 611130, Sichuan, China
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| Abstract: |
| Due to the great differences in climate and environment, there is a lack of space time dynamic research on agricultural implied carbon in China′s regional agricultural development model, which leads to the lack of comprehensive consideration of setting regional emission reduction targets and the failure to achieve the efficiency and fairness of agricultural carbon emission reduction. Therefore, it is necessary to analyze the regional agricultural embodied carbon emissions and their driving factors in different agricultural development modes, so as to provide the basis for formulating carbon emission reduction policies that reflect regional equity and efficiency. In this paper, the input output model was used to estimate the implied carbon emissions from agriculture in China′s provinces and cities, and the LMDI decomposition analysis method was used to decompose the influencing factors into economic scale effect, economic structure effect, general agricultural technology progress effect and low carbon agricultural technology progress effect. The results showed that the implicit carbon emissions of agriculture in most regions of China were on the rise from 2002 to 2012, and the spatial distribution pattern was gradually increasing from west to east, from south to north. The economic scale effect was positively driven in all provinces, and the regional driving effect was more rapid in economic development and stronger in economic growth. And the economic structure effect was negatively driven in most provinces, and the negative effect was gradually enhanced in the agglomeration area of heavy industry; the positive driving effect of general agricultural technology factors was gradually diffused in the large agricultural provinces, and gradually strengthened in the large agricultural provinces; the negative driving effect of low carbon agricultural technology progress factors in the developed Eastern regions. The dynamic effect was stronger, and the driving effect was weaker in the West. Therefore, in the future agricultural emission reduction policy formulation process, we need to fully consider the characteristics of economic development, industrial structure and agricultural production in different regions. |
| Key words: agricultural embodied carbon emissions carbon emissions LMDI decomposition driving factors spatial dynamics |
