东北三省农业碳排放效率时空演化特征及驱动因素分析

Analysis on the Spatio-Temporal Evolution Characteristics and Driving Factors of Agricultural Carbon Emission Efficiency in Three Northeastern Provinces of China

中文关键词:  农业碳排放效率  农业净碳汇  空间聚类  驱动因素  空间分异

英文关键词:agricultural carbon emission efficiency  agricultural net carbon sink  spatial clustering  driving factors  spatial differentiation

中文摘要:

      在经济社会低碳转型变革中，农业作为三大支柱产业之一，其碳排放效率是判断农业可持续发展的重要指标。本研究采用考虑非期望产出的全局SBM模型测算东北三省36个城市在2010—2019年的农业碳排放效率，并运用空间聚类分析和地理探测器探究其空间分异特征及驱动因素，旨在为推动东北地区实现农业高质量发展提供启示。研究结果显示：① 2010—2019年东北三省农业净碳汇总量和农业碳排放效率整体呈上升趋势，从城市尺度出发计算得到效率平均值由0.540提高至0.743；其中吉林省净碳汇增量及效率在研究期内均居于首位，黑龙江省和辽宁省分别具有“高排高汇”和“低排低汇”特征，研究期内各省效率值均有提高。②空间上东北三省农业碳排放效率呈现出“区块状”分布特征，空间聚集程度逐渐增强。③从整体尺度看，将东北地区整体农业碳排放效率作为样本，农业机械率成为研究期内决定力均值最高的驱动因子，但其作用强度逐渐削弱；通过观察不同时期关键交互因子发现，社会因素作用强度逐渐增强。从区域尺度看，农业机械率是影响黑龙江省、辽宁省农业碳排放效率空间分异格局的主导驱动因子，吉林省农业碳排放效率空间分异格局的主导驱动因子是农产品规模和城镇化率；而农业机械率与农业产业结构经过空间叠加后形成的交互因子，对三个省份农业碳排放效率空间分异格局都起到决定性作用。

英文摘要:

      In the economic and social transformation of low-carbon, as one of the three pillar industries, the carbon emission efficiency of agriculture is an important indicator to determine its sustainable development. The global SBM model considering undesired output was used to measure the agricultural carbon emission efficiency of 36 cities in the three provinces of Northeast China from 2010 to 2019, and spatial clustering analysis and geographical detector were used to explore its spatial differentiation characteristics and driving factors, aiming to provide inspiration for promoting the high-quality development of agriculture in Northeast China. The results showed that : ①From 2010 to 2019, the total agricultural net carbon sink and agricultural carbon emission efficiency of the three provinces in Northeast China had an overall upward trend, and the average efficiency increased from 0.540 to 0.743 from the urban scale. Among them, the net carbon sink increment and efficiency of Jilin Province ranked first during the study period. Heilongjiang Province and Liaoning Province had the characteristics of ‘ high emission and high sink’ and ‘low emission and low sink’, respectively. During the study period, the efficiency value of each province had improved as a whole. ② Spatially, the agricultural carbon emission efficiency of the three provinces in Northeast China showed a ‘block’ distribution, and the degree of spatial aggregation gradually increased. ③ From the overall scale, taking the overall agricultural carbon emission efficiency in Northeast China as a sample, the agricultural machinery rate became the driving factor with the highest mean value of the decisive force during the study period, but its intensity gradually weakened.By observing the key interaction factors in different periods, it was found that the intensity of social factors was gradually increasing. From the perspective of regional scale, agricultural machinery rate was the dominant driving factor affecting the spatial differentiation pattern of agricultural carbon emission efficiency in Heilongjiang Province and Liaoning Province. The dominant driving factors of the spatial differentiation pattern of agricultural carbon emission efficiency in Jilin Province were the scale of agricultural products and urbanization rate. The interaction factor formed by the spatial superposition of agricultural machinery rate and agricultural industrial structure played a decisive role in the spatial differentiation pattern of agricultural carbon emission efficiency in the three provinces.