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农学学报

农学学报 ›› 2022, Vol. 12 ›› Issue (4): 80-88.doi: 10.11923/j.issn.2095-4050.cjas2020-0250

所属专题： 现代农业发展与乡村振兴

• 三农问题研究/农村产业结构 • 上一篇    下一篇

新疆农村居民生活消费碳排放及影响因素研究——基于SITRPAT模型

王志强(), 唐琪()   

  1. 新疆农业大学公共管理学院,乌鲁木齐 830052
  • 收稿日期:2020-11-13 修回日期:2021-02-18 出版日期:2022-04-20 发布日期:2022-05-19
  • 通讯作者: 唐琪 E-mail:158105219@qq.com;1547046980@qq.com
  • 作者简介:王志强,男,1982年出生,山东日照人,副教授,博士,研究方向：低碳经济、资源与环境政策。通信地址：830052 新疆乌鲁木齐市农大东路311号 新疆农业大学公共管理学院,E-mail： 158105219@qq.com。
  • 基金资助:
    国家自然科学基金项目“基于人口-产业-土地视角下的城镇化碳排放及其治理机制研究——以新疆天山北坡城市群为例”(71663052)

Carbon Emission of Xinjiang Rural Residents’ Living Consumption and Influencing Factors: Based on the SITRPAT Model

WANG Zhiqiang(), TANG Qi()   

  1. School of Public Administration, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
  • Received:2020-11-13 Revised:2021-02-18 Online:2022-04-20 Published:2022-05-19
  • Contact: TANG Qi E-mail:158105219@qq.com;1547046980@qq.com

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摘要：

构建新疆农村居民碳排放影响因素分析模型,探求各影响因素的实际贡献,为实现新疆人口、消费、环境协调发展目标提出具有针对性的对策建议。文章运用IPCC碳排放系数法和CLA法对2002—2017年新疆农村居民生活消费的碳排放进行核算,并从环境、人口、技术3个方面选取新疆人均年可支配收入、能源强度、生活消费碳排放强度、农村人口比重4个影响指标,基于扩展的STIRPAT模型结合岭回归分析对各影响因素进行实证研究。结果表明：（1）新疆农村居民生活消费碳排放的发展整体呈现递增趋势,其中居民直接碳排放增幅较大,增速较快,在碳排放总量中占比较大,间接碳排放量占比逐年增加,但增速和增幅相对缓慢;（2）各自变量的弹性系数分别为0.09、-0.19、0.89、-0.2,新疆人均年可支配收入、生活消费碳排放强度为碳排放量带来正效应,新疆农村人口比重、能源强度为碳排放量带来负效应。（3）从影响程度来看,生活消费碳排放强度对新疆农村居民生活消费碳排放的拉动作用最大;能源强度对新疆农村居民生活消费碳排放的抑制作用最大。提出建议：（1）优化农村能源系统：调整农村能源结构,推进农村生物质转化,提高农村居民资源利用率;（2）提倡科技兴农：引进低碳技术,提高农村市场供给力,改变农村地区粗放式经济的发展,实现节能产业和循环经济双向发展;（3）推进新型生态农业建设：加大农村“绿色宣传”力度,改革“绿色供给”,加强“绿色治理”,强化“绿色监管”。

关键词: STIRPAT模型, 岭回归, 影响因素, 农村居民生活消费, 碳排放

Abstract:

The study aims to construct an analysis model of factors affecting carbon emission of rural residents in Xinjiang, explore the actual contribution of each influencing factor, and put forward targeted countermeasures for realizing the coordinated development of population, consumption and environment. We used the IPCC carbon emission coefficient method and the CLA method to calculate the carbon emission of rural residents’ living consumption in Xinjiang from 2002 to 2017, and selected 4 influencing factors of per capita annual disposable income, energy intensity, carbon emission intensity of living consumption, and the proportion of rural population from three aspects: environment, population and technology. Based on the extended STIRPAT model combined with ridge regression analysis, the empirical research on each influencing factor was carried out. The results showed that: (1) the overall development of carbon emission from the living consumption of rural residents in Xinjiang had an increasing trend, among them, the direct carbon emission of residents increased significantly, and the growth rate was relatively fast, accounting for a relatively large proportion of the total carbon emission, and the proportion of indirect carbon emission increased year by year, but the growth rate and growth range were relatively slow; (2) the elastic coefficients of the 4 variables were 0.09, -0.19, 0.89 and -0.2, respectively, Xinjiang’s per capita annual disposable income and carbon emission intensity of living consumption had positive effects on carbon emission, the proportion of rural population and energy intensity in Xinjiang had a negative effect on carbon emission; (3) from the perspective of the degree of impact, the carbon emission intensity of living consumption had the greatest pulling effect on the carbon emission of rural residents’ living consumption in Xinjiang, while the energy intensity had the greatest restraint effect. Suggestions were put forward as: (1) optimizing the rural energy system by adjusting the rural energy structure, promoting the conversion of rural biomass and increasing the resource utilization rate of rural residents; (2) advocating agriculture development through science and technology by introducing low-carbon technologies, increasing rural market supply, changing regional extensive economic development in rural areas, and realizing the two-way development of energy-saving industries and circular economy; (3) promoting the construction of new ecological agriculture by intensifying rural ‘green propaganda’, reforming ‘green supply’, strengthening ‘green governance’, and enhancing ‘green supervision’.

Key words: STIRPAT Model, ridge regression, influencing factors, rural residents’ living consumption, carbon emission

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