四川农业大学学报 ›› 2020, Vol. 38 ›› Issue (02): 241-250.doi: 10.16036/j.issn.1000-2650.2020.02.017

• • 上一篇    

2007—2016年中国省域种植业碳排放测算、驱动效应与时空特征

戴小文1,2, 杨雨欣2   

  1. 1.四川省农村发展研究中心;
    2.四川农业大学管理学院,成都 611130
  • 收稿日期:2019-04-03 出版日期:2020-04-28 发布日期:2021-02-02
  • 作者简介:戴小文,副教授,主要从事农业绿色发展,农业经济管理研究,E-mail:daixiaowen@yeah.net。
  • 基金资助:
    国家社科基金项目“中国区域间农业隐含碳排放补偿机制与减排路径研究”(16CJL035)

Calculation, Driving Effect and Temporal and Spatial Characteristics of Carbon Emissions in China's Provincial Planting Industry from 2007 to 2016

DAI Xiaowen1,2, YANG Yuxin2   

  1. 1. Sichuan Center for Rural Development Research;
    2. Management School, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
  • Received:2019-04-03 Online:2020-04-28 Published:2021-02-02

摘要: 【目的】研究中国省域种植业碳排放的驱动因素及时空特征对于制定针对性的种植业发展政策具有参考意义。【方法】通过构建了种植业碳排放测算体系,在科学核算2007—2016年中国种植业碳排放量的基础上采用对数平均指数分解方法(LMDI)对不同区域种植业碳排放驱动因素变动情况进行了分析。【结果】研究发现种植业碳排放总量在2007—2016这10年间经历了“快速上升-缓慢上升-略微下降”的3个阶段,其中种植业生产效率和农业劳动力规模呈现增长的负效应,农业生产结构、农业发展水平和城镇化率呈现增长或波动性增长的正效应。基于驱动效应的强弱,可将我国31个省(市、地区)划分为“种植业生产效率驱动减排型”,“农业生产水平驱动排放型”和“均衡驱动型”3类区域。其中北京、上海、广东等7个省域在10年间种植业碳排放的驱动因素和效应强度产生了变动。【结论】在绿色发展目标框架下,积极转变种植业生产方式、加大种植业科技投入以及分阶段、分地区采用针对性农业发展政策,将是未来种植业绿色发展和低碳发展的主要思路。

关键词: 种植业, 碳排放, 驱动效应, 影响因素, 绿色发展

Abstract: 【Objective】 Studying the driving factors of China's provincial planting industry carbon emissions and temporal and spatial characteristics can provide reference for making targeting policies of planting industry. 【Method】 By constructing a carbon emission calculating system for planting industry, this paper uses the Log-Mean Divisia Index method (LMDI) to analyze the change of carbon emission driving factors of planting industry in different regions in China during 2007—2016 based on scientific calculation. 【Result】 The study found that during 2007—2016, the total carbon emissions of planting industry experienced three stages: rapid rise, slow rise and slight decline, in which the production efficiency of planting industry and the scale of agricultural labor showed a negative effect, while the agricultural production structure, the level of agricultural development and urbanization rate showed positive effects of growth or fluctuating growth. Based on the strength of the driving effect, the 31 provinces (cities, regions) in China can be divided into three categories: planting production efficiency driving emission reduction type,agricultural production level driving emission type and equilibrium-driving type. Among them, the driving factors and effect intensity of carbon emissions in seven provinces including Beijing, Shanghai, Guangdong etc. have changed in the past decade. 【Conclusion】 Therefore, under the framework of the green development goals, changing the production mode of planting industry, increasing the science and technology investment, and adopting targeted agricultural development policies regionally and gradually will be the main idea for the future development of green development and low-carbon development in planting industry.

Key words: planting industry, carbon emission, driving effect, influence factor, green development

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