四川省农业碳排放时空演变特征及其影响因素研究

SPATIAL-TEMPORAL EVOLUTION AND INFLUENCING FACTORS OF AGRICULTURAL CARBON EMISSIONS IN SICHUAN PROVINCE

关键词:  农业碳排放  时空演变  面板Tobit模型  相对重要性分析  四川省

Key words:  agricultural carbon emissions  spatial-temporal evolution  panel Tobit model  relative importance analysis  Sichuan province

摘要:

目的 推动农业碳减排既是农业高质量发展的关键所在，也是实现“双碳”目标的重要一环。方法 文章基于三大类碳源测算2005—2020年四川省农业碳排放量，进一步分析其时空特征与动态演变趋势，理清地区差异；构建面板Tobit模型从经济和社会两个层面探讨其影响因素并通过相对重要性分析诠释不同因素的贡献程度。结果 （1）四川省农业碳排放量呈现波动下降趋势，其时间演变轨迹可大致归为“波动下降、持续上升、快速下降、回升”等4个阶段，农业碳排放强度逐年递减；（2）各市州农业碳排放量呈现出明显的“四周高、中间低”的空间分布特征；（3）全省、川西地区、成都平原地区、川东地区农业碳排放强度均呈现递减态势，空间差异缩小，但各自存在一定区别；（4）农业发展水平与农业碳排放呈“倒U型”关系，农业产业结构、产业集聚水平、城镇化水平、农地规模经营对农业碳排放均具有正向影响，机械化水平、农业财政支持则表现出负向影响；（5）相较于经济层面，社会层面因素对农业碳排放的贡献程度更大，其中机械化水平、农业财政支持、农业产业结构和城镇化水平的贡献程度依次居于前四，其解释力合计达到了80.016%。结论 研究四川省农业碳排放时空演变特征并探究影响各市州农业碳排放变化的关键因素，相关结论能为四川省乃至全国农业碳减排规划和精准施策提供参考。

Abstract:

Promoting agricultural carbon emission reduction is not only the key to agricultural high-quality development, but also an important part of achieving the "dual carbon" goal. Based on three major types of carbon sources, this paper estimated agricultural carbon emissions in Sichuan province from 2005 to 2020, analyzed their spatial-temporal characteristics and dynamic evolution trends, and clarified regional differences. Then it constructed a panel Tobit model to explore the influencing factors from two levels of economy and society. Furthermore, it interpreted the respective contribution of different factors through the relative importance analysis. The results were listed as follows. (1) Agricultural carbon emissions in Sichuan province presented a fluctuation downward trend, which could be categorized into 4 different stages, such as "fluctuating decline, continuous rise, rapid decline and rebound", while agricultural carbon emission intensity was decreasing annually. (2) Carbon emissions in each city (state) showed the distribution pattern of "high in the surroundings, while low in the middle". (3) Agricultural carbon emission intensity in Sichuan, western Sichuan, Chengdu plain and eastern Sichuan all presented a decreasing trend, and the spatial differences narrowed, but each had certain differences. (4) The level of agricultural development had an inverted U-shaped relationship with agricultural carbon emissions, and agricultural industrial structure, industrial agglomeration level, urbanization level and farmland scale management all had driving effects on agricultural carbon emissions, but mechanization level and agricultural financial support showed inhibiting effects. (5) Compared with the economic level, the social level factors contributed more to agricultural carbon emissions, with the contribution of mechanization level, agricultural financial support, agricultural industry structure and urbanization level ranked as the top fourth, and their combined explanatory power reached 80.016%. In summary, this research studies the spatiotemporal evolution characteristics of agricultural carbon emissions in Sichuan province and explores the key factors affecting the changes in agricultural carbon emissions in various cities and states, and the results will contribute to provide references for agricultural carbon emission reduction planning and precise implementation for Sichuan province and even the whole country.