Exploring the influencing factors and decoupling state of residential energy consumption in Shandong

Abstract This paper aims at analyzing the current situation of residential energy consumption in Shandong, identifying the influence factors governing energy consumption based on the LMDI (Log Mean Divisia Index) method, and describing the decoupling relationship between residential energy consumption and residential income based on the Tapio decoupling method. The main results are as follows: (1) The residential energy consumption structures of urban and rural have become multilevel. Furthermore, the gap in per capital residential energy consumption between urban and rural regions narrowed. (2) The energy intensity had an obvious inhibitory effect on decreasing urban residential energy consumption. Per capital income and population structure increased the urban residential energy consumption over the study period. However, per capital income and energy intensity played a more significant role in promoting rural residential energy consumption. And the population structure decreased rural residential energy consumption. During the study period, the contributions from both energy consumption structure and total population effect were negligible. (3) Since 2000, the decoupling index for both urban and rural resident gradually declined, which also shows that residential energy consumption in urban and rural regions was gradually less depend on residential income.

[1]  Ming Zhang,et al.  Analysis of rural residential commercial energy consumption in China , 2013 .

[2]  Yi-Ming Wei,et al.  China’s carbon emissions from urban and rural households during 1992–2007 , 2011 .

[3]  P. Tapio.  Towards the theory of decoupling : Degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001 , 2022 .

[4]  B. W. Ang,et al.  Handling zero values in the logarithmic mean Divisia index decomposition approach , 2007 .

[5]  Guohao Zhao,et al.  An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure , 2016 .

[6]  Manfred Lenzen,et al.  Structural decomposition of energy use in Brazil from 1970 to 1996 , 2009 .

[7]  Yi-Ming Wei,et al.  The impact of household consumption on energy use and CO 2 emissions in China , 2011 .

[8]  Xiaoli Zhao,et al.  Residential energy consumption in urban China: A decomposition analysis , 2012 .

[9]  Shinji Kaneko,et al.  Decomposing the decoupling of CO2 emissions and economic growth in Brazil , 2011 .

[10]  Á. Pardo,et al.  Decoupling factors on the energy–output linkage: The Spanish case , 2007 .

[11]  Yinyin Wu,et al.  Regional differences in China's fossil energy consumption: an analysis for the period 1997–2013 , 2017 .

[12]  Wenwen Wang,et al.  Decoupling analysis of electricity consumption from economic growth in China , 2017 .

[13]  Roberto Schaeffer,et al.  Decomposition analysis of the variations in residential electricity consumption in Brazil for the 1980-2007 period: Measuring the activity, intensity and structure effects , 2009 .

[14]  Yongchen Song,et al.  Decomposition of energy-related CO2 emission over 1991-2006 in China , 2009 .

[15]  K. Blok,et al.  The direct and indirect energy requirement of households in the European Union , 2003 .

[16]  Bin Su,et al.  Decomposing the decoupling indicator between the economic growth and energy consumption in China , 2015 .

[17]  Danae Diakoulaki,et al.  Decomposition analysis for assessing the progress in decoupling industrial growth from CO2 emissions in the EU manufacturing sector , 2007 .

[18]  Lizhen Huang,et al.  Shelter and residential building energy consumption within the 450 ppm CO2eq constraints in different climate zones , 2015 .

[19]  Huanan Li,et al.  Study on affecting factors of residential energy consumption in urban and rural Jiangsu , 2016 .

[20]  Yue-Jun Zhang,et al.  Decomposing the changes of energy-related carbon emissions in China: evidence from the PDA approach , 2013, Natural Hazards.

[21]  J. Sathaye,et al.  Transitions in Household Energy Use in Urban China, India, the Philippines, Thailand, and Hong Kong , 1991 .

[22]  Baizhan Li,et al.  Building energy efficiency for sustainable development in China: challenges and opportunities , 2012 .

[23]  Cheng Xing-lei.  Decoupling Between Urban and Rural Construction Land , 2008 .

[24]  S. Pachauri,et al.  Direct and indirect energy requirements of households in India , 2002 .

[25]  B. W. Ang,et al.  Decomposition of aggregate CO2 emissions: A production-theoretical approach , 2008 .

[26]  Chen Baiming.  Analyzing Decoupling Relationship between Arable Land Occupation and GDP Growth , 2006 .

[27]  D. Hu,et al.  Input, stocks and output flows of urban residential building system in Beijing city, China from 1949 to 2008 , 2010 .

[28]  William Chung,et al.  A study of residential energy use in Hong Kong by decomposition analysis, 1990-2007 , 2011 .

[29]  Li Yan-mei.  Structural Decomposition Analysis of China's Indirect Household Energy Consumption , 2008 .

[30]  B. W. Ang,et al.  Decomposition analysis for policymaking in energy:: which is the preferred method? , 2004 .

[31]  J. Sun.  Changes in energy consumption and energy intensity: A complete decomposition model , 1998 .

[32]  Jining Chen,et al.  Decomposition of energy-related CO2 emission in China: 1957–2000 , 2005 .

[33]  René Kemp,et al.  Index Decomposition Analysis of Residential Energy Consumption in China: 2002-2010 , 2014 .

[34]  Lizhen Huang,et al.  A global overview of residential building energy consumption in eight climate zones , 2016 .

[35]  Baizhan Li,et al.  Urbanisation and its impact on building energy consumption and efficiency in China , 2009 .