甘肃省农业碳排放区域差异、时空特征及趋势预测  

Regional differences in the spatial and temporal characteristics and trend prediction of agricultural carbon emissions in Gansu Province

作　　者：陈睿涛 李薇 燕振刚[1] CHEN Ruitao;LI Wei;YAN Zhengang(College of Information Science and Technology,Gansu Agriculture University,Lanzhou 730070,Gansu,China;College of Finance and Economics,Gansu Agriculture University,Lanzhou 730070,Gansu,China)

机构地区：[1]甘肃农业大学信息科学技术学院,甘肃兰州730070 [2]甘肃农业大学财经学院,甘肃兰州730070

出　　处：《草业科学》2023年第1期287-302,共16页Pratacultural Science

基　　金：甘肃省重点研发项目(21YF5FA095);甘肃省高等学校创新基金(2021A-057);甘肃省财政厅项目(GSCZZ-20160909-03);国家自然基金(31660347)。

摘　　要：以甘肃省5个典型生态区域(民族、河西、陇东、陇中、陇南地区)为研究对象,利用Theil指数分析农业碳排放强度区域差异,采用R/S分析法对农业碳排放量及强度发展趋势进行研究,并在此基础之上结合灰色理论预测2020-2030年甘肃省农业碳排放总量及总强度走势及数值。结果表明:1991-2019年甘肃省5个区域农业碳排放量呈先上升后下降趋势,农业碳排放较低强度市域呈扩大态势,而较高强度市域呈缩小趋势;农业碳排放强度区域总差异整体呈下降趋势,其中区域内差异为主要影响因素,除民族区域之外其他区域内农业碳排放强度差异较小且波动不大;5个区域农业碳排放量及强度具有较强的分形特征,未来农业碳排放量及强度值将呈现出继续下降的演化趋势;甘肃省农业碳排放总量及总强度经R/S分析后进行灰色预测,模型平均精度较高,具有一定参考价值。本研究为探索甘肃省农业碳排放在不同空间尺度下区域差异和未来发展趋势以及制定相应节能减排措施提供了理论依据。In this study, the regional differences of agricultural carbon intensity in five typical ecological areas(Minzu, Hexi,Longdong, Longzhong and Longnan) in Gansu Province were examined through Theil index analysis, which uses the R/S method to analyze the developmental trend of agricultural carbon emission intensity by combining it with grey theory forecast to predict the overall strength and value of agricultural carbon emissions in Gansu Province in 2020-2030. The results showed that agricultural carbon emissions initially increased and then decreased from 1991 to 2019 in the five regions of Gansu Province. The cities with low agricultural carbon emission intensity increased, while cities with high agricultural carbon emission intensity decreased. The total regional differences of agricultural carbon emission intensity showed a downward trend, with the intra-regional difference as the main influencing factor. The differences of agricultural carbon emission intensity in other regions were small with little fluctuations, except for ethnic regions. The agricultural carbon emission intensity of the five regions have strong fractal characteristics that will continue to decline in the future. After R/S analysis, the grey prediction of total agricultural carbon emission and its total intensity was carried out in Gansu Province.The average accuracy of the model is high, with a certain reference value. This study provides a theoretical basis for exploring the regional differences and future developmental trends of agricultural carbon emissions at different spatial scales in Gansu Province for the formulation of corresponding energy conservation and emission reduction measures.

关 键 词：碳排放强度 区域贡献度 THEIL指数 时空格局 HURST指数 

分 类 号：X322[环境科学与工程—环境工程] F327[经济管理—产业经济]