农村用电碳排放变化驱动因素研究

卢晓晴; 方媛; 梁泽奇

doi:10.12052/gdutxb.200145

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农村用电碳排放变化驱动因素研究

更新时间：2026-05-27

- 农村用电碳排放变化驱动因素研究
- A Driving Factors Analysis of the Carbon Emission Change of Rural Electricity Consumption
- 广东工业大学学报 2021年38卷第5期页码：90-96
- 作者机构：
  
  1. 广东工业大学土木与交通工程学院,广东,广州,510006
  2. 肇庆市供电局,广东,肇庆,526300
- 作者简介：
  
  卢晓晴(1997–)，女，硕士研究生，主要研究方向为可持续建设
  方媛(1978–)，女，讲师，博士，硕士生导师，主要研究方向为可持续建设，E-mail：carolynfang@gdut.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(51608132)
- DOI：10.12052/gdutxb.200145
  中图分类号： F282
- 网络首发：2021-09-10，
  
  纸质出版：2021
- 稿件说明：
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卢晓晴, 方媛, 梁泽奇. 农村用电碳排放变化驱动因素研究[J]. 广东工业大学学报, 2021, 38(5): 90-96.

Lu Xiao-qing, Fang Yuan, Liang Ze-qi. A Driving Factors Analysis of the Carbon Emission Change of Rural Electricity Consumption[J]. 2021, 38(5): 90-96.
卢晓晴, 方媛, 梁泽奇. 农村用电碳排放变化驱动因素研究[J]. 广东工业大学学报, 2021, 38(5): 90-96. DOI： 10.12052/gdutxb.200145.

Lu Xiao-qing, Fang Yuan, Liang Ze-qi. A Driving Factors Analysis of the Carbon Emission Change of Rural Electricity Consumption[J]. 2021, 38(5): 90-96. DOI： 10.12052/gdutxb.200145.

摘要

随着农村经济的不断发展

农村能源消费正逐步由生物质能源向电力转变。因此

从农村视角识别影响农村用电碳排放的潜在驱动因素

是我国推进农村低碳发展、实现碳减排目标的重要前提。本文采用基于人口、富裕度和技术的随机影响回归模型(Stochastic Impacts by Regression on Population

Affluence and Technology

STIRPAT)

结合岭回归

分析2005~2018年广东省农村用电碳排放的影响因素。结果表明

城市化水平、农业经济发展水平、有效灌溉面积、农业机械化水平、农业固定资产投资、收入水平以及住房条件等因素都与广东省农村用电产生的碳排放呈正相关。其中

农村居民人均可支配收入是影响广东省农村用电碳排放的最关键因素。此外

农业经济发展与广东省农村用电碳排放也呈弱脱钩关系。最后

针对如何减少广东省农村用电碳排放提出政策建议。

Abstract

With the continuous development of rural economy

rural energy consumption is gradually changing from biomass energy to electricity. Therefore

identifying the potential driving factors of rural electricity carbon emissions from the perspective of rural areas is an important prerequisite for promoting rural low-carbon development and achieving carbon emission reduction goals. In this study

Stochastic Impacts by Regression on Population

Affluence

and Technology (STIRPAT) model and ridge regression are used to analyze the influencing factors of carbon emissions from rural electricity consumption in Guangdong Province from 2005 to 2018. The results show that urbanization level

agricultural economic development level

effective irrigation area

agricultural mechanization level

agricultural fixed assets investment

income level and housing conditions are positively correlated with carbon emissions from rural power consumption. Among them

the per capita disposable income of rural residents is the most important factor affecting the carbon emission of rural electricity. In addition

there is a weak decoupling relationship between agricultural economic development and rural electricity carbon emissions. Finally

policy suggestions are put forward on how to reduce rural electricity carbon emissions in Guangdong Province.

关键词

Keywords

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