黔中喀斯特地区农业生产碳排放实证研究

EMPIRICAL STUDY ON CARBON EMISSION OF AGRICULTURAL PRODUCTION IN KARST REGION OF GUIZHOU PROVINCE

关键词:  喀斯特  农业  碳排放  Tapio脱钩模型  灰色预测

Key words:  karst  agriculture  carbon emission  Tapio decoupling model  grey prediction

摘要:

目的 以贵阳市为例，测算其2007—2016年农业碳排放量，分析时序变化特征、脱钩关系并预测未来10年农业碳排放量，为我国西南喀斯特地区农业减源增汇以及经济发展提供参考。方法 文章运用碳排放系数法计算2007—2016年贵阳市农业碳排放量；基于Tapio脱钩模型分析区域农业碳排放量与农业GDP的脱钩关系；利用GM（1.1）模型预测贵阳市未来10年农业碳排放量。结果 2007—2016年贵阳市农业碳排放量呈下降趋势，年均递减0.75%；三大类碳源中水稻种植占比例最大，为67.37%，其次为畜禽养殖，为17.08%，最后为农地投入，占比为15.55%；细分碳源，除水稻外，化肥与牛碳排放量较高，但农膜、农用柴油、农地灌溉以及羊碳排放都呈增加趋势；脱钩分析表明，贵阳市农业碳排放与农业经济增长间的脱钩类型呈现强脱钩、弱脱钩、强负脱钩、扩张负脱钩4种状态，脱钩类型以强脱钩为主，说明近年来农业碳减排取得一定成效；根据GM（1.1）模型预测，贵阳市农业碳排放量逐年下降，由2017年的50.14万t下降至2026年的47.76万t。结论 贵阳市农业碳减排效果明显，未来还需进一步采取措施以实现农业减源增汇。

Abstract:

Having opted Guiyang city as a case study and performed carbon emission calculations for agriculture sector from 2007 to 2016, this paper analyzed the characteristics of time series change and decoupling relationship, and predicted agricultural carbon emissions in the next 10 years, so as to provide reference for reducing agricultural sources and increasing potential sinks and economic development in karst areas of Southwest China. The agricultural carbon emissions in Guiyang city from 2007 to 2016 were calculated by carbon emission coefficient method; the decoupling relationship between regional agricultural carbon emissions and agricultural GDP was analyzed based on Tapio decoupling model; and the agricultural carbon emissions in Guiyang city within the next 10 years were projected by GM (1.1) model. From 2007 to 2016, agricultural carbon emissions in Guiyang city showed a downward trend, with an average annual decline of 0.75%. Rice planting accounted for 67.37% of the three major carbon sources, followed by livestock and poultry farming, 17.08%, and finally agricultural land investment accounted for 15.55%. Segmented carbon sources, except rice, fertilizer and cattle had a higher contribution to carbon emissions, but agricultural film, agricultural-related diesel fuel consumption, agricultural land irrigation, and sheep carbon emissions were all high. The decoupling analysis distinguished four types of decoupling between agricultural carbon emissions and agricultural economic growth in Guiyang: strong decoupling, weak decoupling, strong negative decoupling, and expansion negative decoupling. The decoupling types found to be mainly strong decoupling, which indicated that agricultural carbon emission reduction had achieved certain results in recent years. According to the GM (1.1) model, the agricultural carbon emissions in Guiyang had been decreasing year by year, from 51.04 ten thousand tons in 2017 to 47.76 ten thousand tons in 2026. In summary, the effect of agricultural carbon emission reduction in Guiyang city is obvious, and further measures should be taken to reduce agricultural sources and increase carbon sinks in the future.