农业机械化是否会制约中国农业碳达峰?一个非线性关系的考察

Will agricultural mechanization restrict carbon peaking in China’s agriculture?An examination of nonlinear relationships

  • 摘要: 农业机械化带来农业能源消耗增加, 成为学术界广泛讨论的制约农业碳达峰的因素。同时, 农业机械化也会导致农业化学品等要素的重新配置和种植结构调整, 进而给中国农业碳排放的变化带来不确定性。本文通过厘清上述路径, 深度剖析农业机械化发展对中国农业碳达峰的影响。本文基于全国(不包括中国香港、澳门、台湾和西藏)县级层面数据, 利用固定效应模型实证分析农业机械化水平对中国农业碳排放的影响, 并进一步采用联立方程模型, 从化学品投入和水稻种植两个角度实证检验其中的作用路径。研究结果表明: 1)随着农业机械使用强度的增加, 农业碳排放强度呈先增后减的“倒U形”变化, 拐点出现在机械使用强度达87.50 kW∙hm−2时, 远高于当前全国平均水平。2)随着农业机械使用强度的提高, 化肥和农药等农业化学品投入强度呈先增加后减少的“倒U形”变化趋势, 成为农业碳排放强度呈“倒U形”变化趋势的主导因素。3)随着农业机械使用强度的增加, 水稻播种面积占比呈先减少后增加的“U形”变化, 但不足以扭转农业碳排放强度的“倒U形”变化趋势。因此, 农业机械化发展在初期会增加农业碳排放强度, 成为制约农业碳达峰的因素。但是, 当农业机械化水平发展到一定程度后, 将有助于农业碳减排, 这种“倒U形”变化趋势主要是由农业化学品投入强度的类似变化所致。基于以上结论, 应加快推进农业机械化进程以促进农业碳减排, 但在农业机械化初期应加强农业化学品的环境管控, 并优化农业生产结构以推动农业碳减排。

     

    Abstract: Agricultural mechanization has led to increased energy consumption in agriculture, which has become a widely discussed factor restricting China’s agricultural carbon peak. However, what is often overlooked is that agricultural mechanization also results in the reallocation of agricultural inputs, such as chemicals, and adjustments in crop planting structures, which in turn introduce uncertainties into changes in China’s agricultural carbon emissions. This study provides a detailed analysis of the impact of agricultural mechanization on China’s agricultural carbon peak by clarifying these pathways. Based on county-level data across the country (not including Hong Kong, Macao, Taiwan and Xizang of China), this study empirically analyzed the impact of agricultural mechanization on agricultural carbon emissions in China using a fixed effects model. Furthermore, a simultaneous equations model was employed to empirically test the pathways of this effect from the perspectives of chemical inputs and rice planting. The research findings indicated that 1) with the increase in the intensity of agricultural machinery utilization intensity, agricultural carbon emission intensity first increased and then decreased in an inverted U-shape, with the turning point occurring when the machinery utilization intensity reached 87.50 kW∙hm−2, much higher than the current national average level; 2) as the machinery utilization intensity increased, the intensity of agricultural chemical inputs, such as fertilizers and pesticides, followed a similar inverted U-shape pattern, becoming the dominant factor driving the inverted U-shape trend in agricultural carbon emission intensity; 3) as the machinery utilization intensity increased, the proportion of rice planting area initially decreased and then increased in a U-shape; however, this was not sufficient to reverse the inverted U-shape trend of agricultural carbon emission intensity. Therefore, in the early stages of agricultural mechanization, the intensity of agricultural carbon emissions increased, thereby restricting the agricultural carbon peak. However, when machinery utilization intensity reached a certain level, it contributed to a reduction in agricultural carbon emissions. This inverted U-shaped trend was mainly due to similar changes in the agricultural chemical input intensity. Based on these findings, accelerating the process of agricultural mechanization to promote agricultural carbon reduction while enhancing the environmental management of agricultural chemicals and optimizing agricultural production structures in the early stages of mechanization to drive further carbon reduction in agriculture is crucial.

     

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