Analysis of rural residential energy consumption and corresponding carbon emissions in China

Energy Policy ◽  
2012 ◽  
Vol 41 ◽  
pp. 445-450 ◽  
Author(s):  
Chunsheng Yao ◽  
Chongying Chen ◽  
Ming Li
2015 ◽  
Vol 16 (1) ◽  
pp. 96-111 ◽  
Author(s):  
Sally Caird ◽  
Andy Lane ◽  
Ed Swithenby ◽  
Robin Roy ◽  
Stephen Potter

Purpose – This research aims to examine the main findings of the SusTEACH study of the carbon-based environmental impacts of 30 higher education (HE) courses in 15 UK institutions, based on an analysis of the likely energy consumption and carbon emissions of a range of face-to-face, distance, online and information and communication technology (ICT)-enhanced blended teaching models. Design/methodology/approach – An environmental assessment of 19 campus-based and 11 distance-based HE courses was conducted using questionnaire surveys to gather data from students and lecturers on course-related travel: the purchase and use of ICTs and paper materials, residential energy consumption and campus site operations. Results were converted into average energy and CO2 emissions, normalised per student per 100 study hours, and then classified by the primary teaching model used by lecturers. Findings – The main sources of HE course carbon emissions were travel, residential energy consumption and campus site operations. Distance-based HE models (distance, online and ICT-enhanced teaching models) reduced energy consumption by 88 per cent and achieved significant carbon reductions of 83 per cent when compared with campus-based HE models (face-to-face and ICT-enhanced teaching models). The online teaching model achieved the lowest energy consumption and carbon emissions, although there were potential rebound effects associated with increased ICT-related energy consumption and paper used for printing. Practical implications – New pedagogical designs using online and distance-based teaching methods can achieve carbon reductions by reducing student travel via residential and campus accommodation. Originality/value – Few studies have examined the environmental performance of HE teaching models. A new classification of HE traditional, online and blended teaching models is used to examine the role of ICTs and the likely carbon impacts.


2012 ◽  
Vol 32 (24) ◽  
pp. 7716-7721
Author(s):  
王丹寅 WANG Danyin ◽  
唐明方 TANG Mingfang ◽  
任引 REN Yin ◽  
邓红兵 DENG Hongbing

2017 ◽  
Vol 11 (4) ◽  
pp. 541-556 ◽  
Author(s):  
Yongxia Ding ◽  
Shuwen Niu

Purpose This paper aims to analyze the internal relationships and tendency of residential energy consumption, income and carbon emissions. Design/methodology/approach Taking 30 provinces of China as the analysis unit and dividing them into two types of urban and rural consumer groups, the panel data model was built. In addition, panel unit root test, panel cointegration test and panel Granger causality test were also used. Findings The results showed that there are long-run equilibrium relationships between the three variables, which show the regular tendency in the spatial process. The elasticity coefficients of residential energy consumption and CO2 emissions vary across the three regions and decline continuously from the western to central and eastern regions. In addition, geographic location is also an important factor on the energy consumption and CO2 emissions in residential sector. Originality/value This paper provides some points for policies on cutting energy use and pollution in residential sector.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3864
Author(s):  
Qiucheng Li ◽  
Jiang Hu ◽  
Bolin Yu

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.


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