关键词: 农地碳排放, 影响因素, 空间差异性, STIRPAT模型, GWR 模型

Abstract: This paper, based on 31 provinces' farmland carbon emission data during 2011 to 2013, uses STIRPAT and GWR models to study the spatial variance of impact and coefficient of population, prosperity and technology on farmland carbon emission. Farmland gross carbon emission is characterized by high in agricultural province, carbon emission per capita by north-high-south-low, and carbon emission per acre by north-low-south-high. Population has a positively fixed elasticity on farmland carbon emission, but prosperity and technology display a spatial variance that the elasticity on agricultural increment per capita, non-agricultural income per capita, urbanization rate, agricultural machine gross power are stable but its values of spatial variance, and that on agriculture to the first industry ratio and agricultural farmland scale shows spatial variance, and values as well. Suggestions are presented on adjusting the inner structure of the fist industry in controlling farmland carbon emission, increasing farmland operation scale per capita in promoting farmland carbon emission reduction, especially for northeastern, northern, eastern and Inner Mongolia.

Key words: farmland carbon emission, factor, spatial variance, STIRPAT model, GWR model