Factors Influencing the Spatial Difference in Household Energy Consumption in China

نویسندگان

  • Yongxia Ding
  • Wei Qu
  • Shuwen Niu
  • Man Liang
  • Wenli Qiang
  • Zhenguo Hong
  • Tomonobu Senjyu
چکیده

What factors determine the spatial heterogeneity of household energy consumption (HEC) in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model and panel dataset for 30 provinces in China over the period 1997–2013, this paper investigated influences of the income per capita, urbanization level and annual average temperature on HEC, and revealed the spatial effects of these influencing factors. The results show that the income level is the main influencing factor, followed by the annual average temperature. There exists a diminishing marginal contribution with increasing income. The influence of urbanization level varies according to income level. In addition, from the eastern region to western region of China, variances largely depend upon economic level at the provincial level. From the northern region to southern region, change is mainly caused by temperature. The urbanization level has more significant impact on the structure and efficiency of household energy consumption than on its quantity. These results could provide reference for policy making and energy planning.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Spatial analysis of the factors influencing households direct energy consumption and CO2 emission in Ardabil

Spatial analysis of the factors influencing households’ direct energy consumption and CO2 emission in Ardabil Problem Statement Carbon management and its production resources are important not only for the preservation of non-renewable resources but also for the prevention of global warming and its adverse consequences. Direct consumption of fuel and energy by households plays a major role ...

متن کامل

Estimation of Household Energy Demand Function: Evidences from 28 Provinces of Iran

Nowadays, demand for energy is one of the important and applicable issues in different countries. Energy demand is of great importance from the viewpoints devastating impact on the environment and in terms of economic costs. The household sector is the major consumer of energy study of the factors influencing the energy consumption can have beneficial results in terms of the application of appr...

متن کامل

The spatial spillover effect of technical efficiency and its influencing factors for China’s mariculture — based on the partial differential decomposition of a spatial durbin model in the coastal provinces of China

Using mariculture data from China’s nine coastal provinces from 2003 to 2015, this paper first evaluates the technical efficiency through data envelopment analysis (DEA). Then, this paper analyses the spatial spillover effect of technical efficiency and its influencing factors with a spatial panel Durbin model (SDM). The results indicate that there are obvious regional differences in the techni...

متن کامل

Analysis of Spatial Disparities and Driving Factors of Energy Consumption Change in China Based on Spatial Statistics

The changes of spatial pattern in energy consumption have an impact on global climate change. Based on the spatial autocorrelation analysis and the auto-regression model of spatial statistics, this study has explored the spatial disparities and driving forces in energy consumption changes in China. The results show that the global spatial autocorrelation of energy consumption change in China is...

متن کامل

Identifying Factors Affecting Household Energy Consumption Using Data Mining Methods

Due to increasing population and decreasing energy sources, this research studies the consumption of domestic energy. The purpose of this study is to predict the factors affecting household energy consumption. To do this, we use 3 algorithms, M5Rules, K-nearest neighbor and random forest, available in Weka software. In this study, the feature correlation algorithm is used to select the most imp...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016