基于扩展的STIRPAT模型的广东农业碳排放影响因素分析

Analysis of Influencing Factors of Agricultural Carbon Emission in Guangdong Province with the Extended STIRPAT Model

摘要:

广东农业是典型的高碳型农业。基于1991—2013年时间序列数据，在变形的Kaya恒等式基础上，利用扩展的STIRPAT模型分析广东农业碳排放强度的影响因素。结果显示：城镇化水平、农业人口规模与广东碳排放强度显著正相关，表明广东城镇化水平提高加剧了农业碳排放，农业人口规模的减少有碳减排效应；农业生产效率的提高有利于实现广东农业碳减排；农业经济发展水平与广东碳排放强度呈正U型曲线关系，且已越过阶段较低点处于上升态势；种植业在农业中的比重、农业自然灾害程度与广东农业碳排放强度显著正相关。

Abstract:

The agriculture is a typical high-carbon one in Guangdong. Based on the Kaya identity of deformation as well as time-series data from 1991 to 2013, and using the extended STIRPAT model, the influencing factors on agricultural carbon emission intensity in Guangdong are analyzed. The results show that the agriculture carbon intensity is highly positively correlated to both the level of urbanization and agricultural population size, indicating that the high urbanization level intensified Guangdong agricultural carbon emissions, at the same time, the reducing of agricultural population size in Guangdong caused carbon emissions reduction. It’s helpful to reduce agricultural carbon emissions with the improving of the efficiency of agricultural production. The variation of agricultural carbon intensity corresponding to the level of economic development is characterized with a U-shaped line, and is currently located in the rising edge. Moreover, the agriculture carbon intensity is also highly positively correlated to the proportion of planting industry in agriculture as well as the damage degree of natural disasters in agriculture.