近20年来中国农业碳排放强度区域差异、时空格局及动态演化

研究农业碳排放强度的区域差异、时空格局与动态演化规律,对制定合理的农业碳减排政策具有重要的理论及实践意义。采用Theil指数及空间分析相关方法分析1997～2016年中国农业碳排放强度的区域差异、时空格局特征,并利用R/S分析法预测其演化趋势。结果表明:(1)1997～2016年中国及三大粮食功能区的农业碳排放强度均呈下降趋势,不同类型农业碳排放强度省域的空间分布变化均较大,碳排放高强度省域保持稳定,而低强度省域呈扩大态势;(2)农业碳排放强度的区域差异总体呈扩大趋势,其中区域间差异变化较小,区域内差异趋于扩大,粮食平衡区区域内差异趋于上升,主产区区域内差异先升后降,主销区区域内差异趋于收敛;(3)中国农业碳排放强度的空间集聚程度趋于缩小,热点区保持不变,而冷点区呈收缩态势,青-藏保持稳定性热点区,京-津-冀-陕-晋-豫-鲁为稳定性冷点区域;(4)中国、三大功能区及各省域农业碳排放强度具有明显的分形特征,未来碳排放强度值将呈现出继续下降的演化态势,尤其以粮食主销区的下降趋势具有更强的持久性。

Regional Inequality,Spatial-Temporal Pattern and Dynamic Evolution of Carbon Emission Intensity from Agriculture in China in the Period of 1997-2016

Abstract：Exploring regional inequality, spatial-temporal pattern and dynamic evolution of carbon emission intensity from agriculture has important theoretical and practical significance for formulating a reasonable agricultural carbon emission reduction policy.In this paper, 31 provinces (municipalities and autonomous regions) in China were taken as the research unit to measure carbon emission intensity from agriculture during 1997-2016, through an integration of Theil index and exploratory spatial data analysis (ESDA) and R/S, we examine the regional inequality, spatio-temporal pattern and dynamic evolution characteristics of carbon emission intensity from agriculture.The results are shown as follows: (1） The carbon emission intensity from agriculture in China and the three major grain functional zones showed a downward trend, and the spatial distribution of different types carbon emission intensity from agriculture in province was larger, the high-intensity provinces of carbon emissions remained stable, while the low-intensity provinces are expanding; （2) The regional inequality of carbon emission intensity from agriculture presented an extending trend in 1997-2016, Among this, the agricultural carbon intensity inequality between regions is not obvious, but that within a region presented an expanding trend, and the growing rate of inequalities in the grain balance area tends to rise, the main production area rises first and then falls, and the main sales area tends to converge; （3) By observing the change of Moran’s I in 1997-2016, we found that the spatial agglomeration range of carbon emission intensity presented a narrowing trend, hot spots remain unchanged, but cold spots presented a shrinking tendency, Qinghai and Xizang formed a stable cold spot, and Beijing, Tianjin, Hebei, Shannxi, Shanxi, Henan and Shandong formed a stable hot spot; (4） The performance of carbon emission intensity from agriculture in China, the three major functional areas and the provinces had an obvious fractal characteristic, and carbon emission intensity value will show an evolutionary trend that continues to decline in future, especially with the downward trend of the grain sales area.