Coal-to-gas heating compensation standard and willingness to make clean energy choices in typical rural areas of northern China

被引:52
|
作者
Yan, Yutong [1 ]
Jiao, Wenxian [1 ,2 ]
Wang, Kang [3 ,4 ]
Huang, Yatao [1 ]
Chen, Jingyang [1 ]
Han, Qingfeng [5 ]
机构
[1] Henan Univ, Coll Environm & Planning, Kaifeng 475001, Peoples R China
[2] Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow, Minist Educ, Kaifeng 475001, Peoples R China
[3] East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
[4] Univ Colorado, Inst Arctic & Alpine Res, Boulder, CO 80309 USA
[5] Stat Bur Juye Cty, Juye 274900, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
C2G project; Heating compensation standard; Minimum data method; Logistic regression model; Environmental perception; SERVICES; IMPACT;
D O I
10.1016/j.enpol.2020.111698
中图分类号
F [经济];
学科分类号
02 ;
摘要
The implementation of the coal-to-gas (C2G) project is the key to achieving the transition to clean energy and improving air quality in rural areas in the north of China. Based on the survey data of 374 households in the town of Mishan, which is in the city of Jincheng in Shanxi Province, the C2G heating compensation standard was calculated using the minimum data method, and the key factors affecting farmers' choice of clean energy were analyzed using logistic regression models. The results were as follows. (i) The C2G project almost doubled the heating expenditure of farmers. (ii) When the compensation standard increased, the ratio of newly added C2G heating area and newly reduced pollutant emissions increased non-linearly. To achieve an environmental goal of reducing particulate matter by 40%, the government will need to compensate each household by 3.56 CNY/m(2) per month, which is 1.35 times the current compensation standard. When the monthly compensation is 9 CNY/m(2), the comprehensive best economic and environmental benefits can be achieved. (iii) The per capita annual income of households and the permanent population of households are the most significant variables affecting farmers' choice of clean energy. Introducing environmental perception variables, such as adaptive efficacy perception and self-efficacy perception, can help to identify the willingness of farmers to choose clean energy.
引用
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页数:11
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