中国农地利用碳排放时空演变特征及驱动因素研究——基于IPCC法与LMDI指数分解模型
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摘要
基于灌溉、翻耕、农药、农用化肥、农膜、农用柴油等6大主要碳排放源,利用IPCC法、标准差和变异系数法对2004—2016年我国农地利用碳排放总量及碳排放强度的时序与空间演化进程进行测量,并运用LMDI指数分解模型对其影响因素进行探究。结果表明:我国农地利用碳排放量总体呈现出"低速上升—低速下降"的趋势,碳排放强度变化具有"双峰"特点;农地利用高碳排放区基本覆盖我国主要的粮食作物产区,而碳排放高强度区则大致与我国农地资源匮乏、经济发展程度高且人口众多的地区重叠。13年来,我国31个省(市、区)的农地利用碳排放量的相对差异表现出先扩大后缩小的趋势,绝对差异逐步减少,碳排放强度的相对差异与绝对差异均在2008年后保持先缩小后扩大的趋势;农业效率、农业结构与农业劳动力对农地利用碳排放起抑制作用,农业经济是促使农地利用碳排放增长的主要因素。
Based on 6 major carbon emissions sources,this paper used the method of IPCC and standard deviation and coefficient of variation to investigate the time series and spatial evolution process of China' s agricultural land carbon emission and carbon intensity from 2004 to 2016. Then,the LMDI index decomposition model was applied to analyze influencing factors. The results showed that: Firstly,agricultural land carbon emission in China was a trend of"low speed rise following with low speed drop",and the change in carbon intensity had a"double peak"characteristic. Secondly,the high carbon emission area of agricultural land basically coverd China's main food crop production areas,while the high intensity of carbon emission was roughly overlapped with the regions lacking in agricultural land resources as well as economically developed with large population regions in China. Thirdly,in the past 13 years,the relative differences of agricultural land carbon emission in 31 provinces(including cities and districts) in China were a trend of first increasing and then shrinking,the absolute difference was gradually decreasing,and the relative and absolute differences of agricultural land carbon emission intensity were both first decreasing then shrinking after 2008. Finally,agricultural efficiency,agricultural structure and agricultural labor force had a restraining effect on agricultural land carbon emission,and the agricultural economy was the main factor to promote the growth of carbon emissions of agricultural land.
Based on 6 major carbon emissions sources,this paper used the method of IPCC and standard deviation and coefficient of variation to investigate the time series and spatial evolution process of China' s agricultural land carbon emission and carbon intensity from 2004 to 2016. Then,the LMDI index decomposition model was applied to analyze influencing factors. The results showed that: Firstly,agricultural land carbon emission in China was a trend of"low speed rise following with low speed drop",and the change in carbon intensity had a"double peak"characteristic. Secondly,the high carbon emission area of agricultural land basically coverd China's main food crop production areas,while the high intensity of carbon emission was roughly overlapped with the regions lacking in agricultural land resources as well as economically developed with large population regions in China. Thirdly,in the past 13 years,the relative differences of agricultural land carbon emission in 31 provinces(including cities and districts) in China were a trend of first increasing and then shrinking,the absolute difference was gradually decreasing,and the relative and absolute differences of agricultural land carbon emission intensity were both first decreasing then shrinking after 2008. Finally,agricultural efficiency,agricultural structure and agricultural labor force had a restraining effect on agricultural land carbon emission,and the agricultural economy was the main factor to promote the growth of carbon emissions of agricultural land.
引文
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[19]李波,刘雪琪,王昆.中国农地利用结构变化的碳效应及时空演进趋势研究[J].中国土地科学,2018,32(3)∶43-51.
[20]何艳秋,陈柔,吴昊王月,等.中国农业碳排放空间格局及影响因素动态研究[J].中国生态农业学报,2018,26(9)∶1269-1282.
[2]张志高,袁征,李贝歌,等.基于投入视角的河南省农业碳排放时空演化特征与影响因素分解[J].中国农业资源与区划,2017,38(10)∶152-161.
[3]吴贤荣,张俊飚,田云,等.中国省域农业碳排放:测算、效率变动及影响因素研究———基于DEA-Malmquist指数分解方法与Tobit模型运用[J].资源科学,2014,36(1)∶129-138.
[4]刘航,温宗国.全球气候治理新趋势、新问题及国家低碳战略新部署[J].环境保护,2018,46(2)∶50-54.
[5]戴小文,何艳秋,钟秋波.中国农业能源消耗碳排放变化驱动因素及其贡献研究———基于Kaya恒等扩展与LMDI指数分解方法[J].中国生态农业学报,2015,23(11)∶1445-1454.
[6]吴贤荣,张俊飚,田云,等.基于公平与效率双重视角的中国农业碳减排潜力分析[J].自然资源学报,2015,30(7)∶1172-1182.
[7]李立,周灿,李二,等.基于投入视角的黄淮海平原农业碳排放与经济发展脱钩研究[J].生态与农村环境学报,2013,29(5)∶551-558.
[8]李国志,李宗植.中国农业能源消费碳排放因素分解实证分析———基于LMDI模型[J].农业技术经济,2010,(10)∶66-72.
[9]刘丽辉,徐军.基于扩展的STIRPAT模型的广东农业碳排放影响因素分析[J].科技管理研究,2016,36(6)∶250-255.
[10]戴小文,何艳秋,钟秋波.基于扩展的Kaya恒等式的中国农业碳排放驱动因素分析[J].中国科学院大学学报,2015,32(6)∶751-759.
[11]李玉波,许清涛,高标,等.吉林省农业碳排放与经济增长脱钩关系实证分析[J].中国农机化学报,2017,38(2)∶130-134.
[12]张玉梅,乔娟.都市农业发展与碳排放脱钩关系分析———基于脱钩理论的Tapio弹性分析法[J].经济问题,2014,(10)∶81-86.
[13]洪业应.农业碳排放与经济增长关系的实证研究———基于环境库兹涅茨曲线的检验[J].浙江农业学报,2015,27(9)∶1664-1669.
[14]高标,房骄,许清涛,等.吉林省农业碳排放动态变化及驱动因素分析[J].农业现代化研究,2013,34(5)∶617-621.
[15]李波,张俊飚,李海鹏.中国农业碳排放时空特征及影响因素分解[J].中国人口·资源与环境,2011,21(8)∶80-86.
[16]田云,李波,张俊飙.基于投入角度的农业碳排放时空特征及因素分解研究———以湖北省为例[J].农业现代化研究,2011,32(6)∶752-755.
[17]张利平.绿色发展理念下我国农业低碳化路径创新[J].学习论坛,2016,32(5)∶38-41.
[18]韩骥,周翔,象伟宁.土地利用碳排放效应及其低碳管理研究进展[J].生态学报,2016,36(4)∶1152-1161.
[19]李波,刘雪琪,王昆.中国农地利用结构变化的碳效应及时空演进趋势研究[J].中国土地科学,2018,32(3)∶43-51.
[20]何艳秋,陈柔,吴昊王月,等.中国农业碳排放空间格局及影响因素动态研究[J].中国生态农业学报,2018,26(9)∶1269-1282.