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