食物消费结构升级对农业碳排放的动态影响机制研究

STUDY ON THE DYNAMIC INFLUENCING MECHANISM OF FOOD CONSUMPTION STRUCTURE UPGRADE ON THE AGRICULTURAL CARBON EMISSION

关键词:  食物消费结构农业碳排放动态影响影响机制VAR模型

Key words:  food consumption structure  agricultural GHG emissions  dynamic influence  influencing mechanism  VAR model

摘要:

［目的］探寻主要食物消费结构与农业碳排放之间的动态关联机制。［方法］基于1990—2015年面板数据，通过VAR模型进行研究。［结果］结果显示食物消费结构升级与农业碳排放确实有着一定的关联性，且存在一定的滞后性，但其影响程度和方向因食物种类而异。［结论］（1）从影响方向看，农业碳排放对肉禽类、奶类等动物性食物消费和粮食、蔬菜、食用植物油等植物性食物消费变动的冲击响应方向基本相反，这主要是由动物性食物和植物性食物的替代性导致； 农业碳排放对食物消费变化冲击的响应方向呈正负交替变化，且随着时间的推移而趋于平缓，主要是由于农产品供求的收敛型“蛛网”变动特点引起。（2）从响应时间看，农业碳排放变动对植物性食物消费冲击响应更为迅速，主要是由于动物类食物调整生产周期明显长于植物类食物产品； 以植物性食物消费代替动物性食物消费的方式在短期内（3~4年以内）确实可以一定程度上降低碳排放，但是长期看来效果并不明显； 所有食物消费变动对农业碳排放的冲击效应在8~9期以后均逐渐消失，说明食物消费结构的变动对农业碳排放的影响持久，农业碳减排任务不可能在短期内一蹴而就，而需要长期而持续的努力。（3）从影响程度看，方差分解结果表明，对农业碳排放变动的影响贡献最大的是其自身，说明农业碳排放基数庞大，减排工作任务艰巨，尽管肉禽类食物消费导致的碳排放量比重较大，但研究期间农业碳排放变动的并不是主要由这类食物消费的变化导致，而是由植物性食物消费变化导致。研究结果为在满足居民食物消费需求的前提下降低农业碳排放、发展低碳农业提供一定的依据。

Abstract:

Based on the panel data for 31 provinces from 1990 to 2015, this research aims to explore the dynamic correlation mechanism between the main food consumption species and agricultural greenhouse gas(GHG) emissions by constructing the VAR model. The empirical results showed that the change of food structure had certain correlations with agricultural GHG, with some lagging effects, whereas the degree and direction of the impacts varied with types of the food. Main conclusions are as follows. Firstly, from the direction of the impacts, the response of agricultural GHG to the animal sourced foods such as meat, poultry, and milk and the consumption of plant based foods such as grain, vegetables, and edible vegetable oil are basically in opposite directions, mainly due to the substitution of animal sourced foods for plant based foods. The direction of agricultural GHG′ response to changes in food consumption is alternating positive and negative, tending to be flat over time, mainly due to the characteristics of the convergence of the supply and demand of agricultural products based on "Cobweb Theorem". Secondly, from the perspective of response time, changes in agricultural GHG respond more quickly to the impact of plant based foods, mainly due to the fact that the production cycle of animal sourced food is significantly longer than that of plant based food products. The replacement of animal sourced food with plant based food do reduce GHG emissions to some extent, in the short term (within three or four years), whereas the long term effect is not obvious. The impacts of food changes on agricultural GHG emissions will gradually disappear after the eight or nine years. It shows that the changes in food consumption structure have a lasting impact on agricultural GHG emissions. The task of reducing agricultural GHG cannot be achieved overnight, but requires long term and continuous efforts. Finally, in relation to the degree of impacts, it shows that the biggest contribution to the impact of agricultural GHG is itself, indicating that the agricultural GHG base is so huge that the task of reducing GHG emissions is arduous. Despite the large proportion of GHG emissions caused by meat and poultry food consumption, the changes in agricultural GHG emissions during the study period are not mainly caused by changes in food consumption of meat and poultry, but caused by changes in plant based food consumption. The research results provide a certain basis for reducing agricultural GHG emissions and developing low carbon agriculture under the premise of meeting the food consumption needs of residents.