Household pathway selection of energy consumption during urbanization process in China
Introduction
China is currently in the rapid process of urbanization, which is the key development stage of transition to a middle-income country [1], and urbanization is considered by policy-makers as a necessary element to build a comprehensive well-off society. Urbanization is a major determinant explaining energy consumption growth [2], [3], [4], [5], which plays an important role in determining the energy and carbon profiles in China. As shown in Fig. 1, China’s urbanization rate increased from 26.41% in 1990 to 52.57% in 2012, indicating an increment of 409.87 million urban dwellers. The primary energy consumption, which was driven by urbanization, increased from 987.03 million tonnes of coal equivalent (Mtce) in 1990 to 3617.30 Mtce in 2012 – equivalent to an increase of 266.48%. The annual average growth rate of energy consumption in China was 5.96% during 1990–2012 [6].
China’s residential energy consumption was driven by the accelerated urbanization process. As shown in Table 1, with a doubled urbanization rate, China’s urban household energy consumption increased by ten times in 2011 compared with 1990. According to CDRF [7], China’s urbanization rate will reach 65–70% in 2030, indicating a 12.4–17.4% increase in the next 18 years. Therefore, China’s urbanization process will increasingly impose pressure to the future energy consumption, and residential energy consumption will be the most important area for campaigns to conserve energy and reduce emissions in China.
Although urbanization and industrialization are seen as interdependent processes during economic development, urbanization exerts a number of independent influences on energy use [8]. We summarize the influences into two aspects: first, energy consumption shows rigid growth characteristic due to the large-scale infrastructure construction; second, household energy consumption patterns change with lifestyle changes during the urbanization process.
It is worth noting that household energy consumption patterns, which are characterized by effects of “path lock-in” [9], [10], [11],1 have long-term impacts on energy consumption. It indicates that the future energy demand and related greenhouse gas emissions will be locked in by the current energy consumption patterns. Path lock-in or path dependence has embodied the essential meanings of urban development and residents’ willingness to conserve energy. For example, residential transportation energy consumption is determined by city scale, traffic condition and lifestyle, and household power consumption is influenced by the number as well as the quality of home appliances.
Transformation of lifestyles in rapid urbanization has resulted in growing demand for modern fuels [12] and generated fundamental changes in energy use [13]. Household pathway selection of energy consumption, which can be influenced by energy policies and strategies, will have long-term impacts on China’s energy consumption during the urbanization process. In other words, the urbanization process provides an opportunity to create the efficient energy consumption patterns for urban residents. However, decision-makers in China fail to fully recognize the opportunity that exists in improving the efficiency of the urban system as a whole [14].
The contributions of our study in advancing the existing literature are as follows: first, based on micro-level household data, the present paper is the first case that analyzes the electricity, heating and transport energy consumption of rural and urban households in China; second, our finding highlights the evidence of the relationship between household lifestyles and residential energy demand, which proves the “path lock-in effect” of residential energy consumption during urbanization process in China; third, China’s urban development strategy for reducing energy consumption and emissions are suggested for policy-makers.
The remainder of this study is organized as follows. Section 2 is literature review. Section 3 provides data collection and presentation. Section 4 describes methodology. Empirical results and discussions are shown in Section 5. Section 6 summarizes our findings and suggests policy recommendations.
Section snippets
Literature
Research on the relationship between urbanization and residential energy consumption has attracted considerable attention from researchers and analysts, who mainly concentrate on two aspects: the empirical estimation of energy demand functions and the econometric analysis of residential energy consumption behavior.
Empirical studies of household energy demand highlight the relationship between energy demand and economic growth or economic transition. For instance, Kraft and Kraft [15] conducted
Variables and data collection
In order to obtain the information of residential energy consumption, we use the survey data from China’s Residential Energy Consumption Survey (CRECS) to analyze household pathway selection of energy consumption.
Urban household energy consumption behavior is differentiated due to China’s large population and extensive land. In order to clarify the difference of residential energy consumption among regions in China, we choose samples of ten provinces in the Mainland China, including three
Analysis of variance (ANOVA)
This paper uses ANOVA to explore the impacts of different factors on household energy consumption. We apply the ANOVA method because it can effectively explain the differences among groups.
Analysis of variance (ANOVA), a statistical technique, which analyzes variability in data in order to infer the inequality among population means. ANOVA was first developed by R.A. Fisher in the 1920s and 1930s. The ANOVA uses F-tests to examine a pre-specified set of standard effects. ANOVAs are useful in
Results of ANOVA
In our data set, for the variable of “whether households are sensitive to the tiered pricing for household electricity”, the F value equals 35.97 and P value equals 0 (Column 1 in Table 5). Results indicate that variable (i) “whether residents are sensitive to the tiered pricing for household electricity” has a significant impact on the electricity use. Moreover, variable (i) also has a significant influence on gas use (P value is 0.018). As gas is a substitute to electricity, the consumption
Conclusion and policy implications
Based on the surveyed data of ten provinces, this paper is the first case to explore factors that influence household energy consumption and analyze the residential energy consumption structure in China. Based on the results of analysis of variance (ANOVA), this paper applies the Tobit model and the OLS model to investigate impacts of variables of “the tiered pricing for household electricity”, “solar energy usage”, “automobile ownership”, “rural or urban areas”, “household income” and “city
Acknowledgements
The authors appreciate Shiying Pan for English language editing of this paper. The paper is supported by National Natural Science Foundation of China (Grant Nos. 71303199 and 71373218), Ministry of Education Foundation of China (Grant Nos. 13YJC790123, 11JBGP006 and 13JZD010), Fundamental Research Funds for the Central Universities (Grant Nos. 201122G008 and 2014221001), Major Program of the National Social Science Foundation of China (Grant No. 13&ZD167) and Social Science School of Xiamen
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