Household Energy Consumption In China Research Articles

Characteristics, Drivers and Transitions of Household Energy Consumption in China: An Overview

Energy plays a crucial role in our daily lives, not only as a basis for survival and development, but also as a national strategy. This paper focuses on household energy consumption, which is a key factor in promoting economic development and social progress. Globally, household energy consumption accounts for 25-30% of the total energy consumption, and in China it accounts for 12.4% of the total national energy consumption, making it the second largest force after the first major energy consumer. Since household energy consumption is closely related to climate change, ecological quality, and population health, this paper analyzes the current situation of household energy in China, and conducts a literature review from three key aspects: first, it discusses in depth the characteristics and trends of household energy consumption, and reveals its important position in the global and domestic consumption patterns; second, it examines the drivers that influence household energy consumption, including household size, economic level, geographic location, and many other factors; finally, it focuses on household energy transition and explores the key issues of sustainable energy and green low-carbon transition. Through the review of the literature, this paper aims to provide an in-depth understanding for future research and policy development to effectively address the environmental, ecological and social issues that may arise from household energy consumption.

Spatiotemporal characteristics, influencing factors, and trend prediction of household energy consumption in China

Spatiotemporal characteristics, influencing factors, and trend prediction of household energy consumption in China

Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective

Ensuring access to affordable energy for all is laid out among the 17 Sustainable Development Goals and it remains an important open question as to how the popularity and widespread application of artificial intelligence (AI) in the workforce impact household energy resources consumption. To systematically investigate the impacts of the application of artificial intelligence in the workforce on household energy consumption in China, empirical analysis is conducted using data from the China General Social Survey (CGSS) from May to September 2022. The findings are as follows: (1) AI significantly reduces household energy consumption. Controlling other factors constant, for a one-standard-deviation increase in the impact of AI, household energy consumption drops by an average of 10.751%. Robustness and endogeneity tests, including dealing with missing values, using different energy consumption and AI indicators, as well as applying instrumental variable method, placebo test and penalized regressions, confirm this conclusion. (2) Mechanism analysis shows that AI reduces energy consumption by lowering household income and increasing their financial fragility. (3) AI's impacts on different types of energy consumption are heterogeneous. Its negative effects are mainly observed in the significant reduction of electricity and gas consumption. Furthermore, it increases the probability of using solid fuels such as honeycomb coal, coal lumps, traditional biomass, etc., thereby increasing the reliance on low-grade energy resources and raising the risk of energy poverty. (4) AI has greater negative effects on those who do not have access to energy subsidies and households with poor energy security and stability, lower income and inadequate social security. Besides, its impacts on regions with higher levels of technological development are more prominent. (5) Feasible pathways to mitigate the adverse effects of AI are explored. It is found that improving labor protection can help alleviate its adverse consequences on energy consumption. This paper provides evidence on the impacts of technological disruption from a demand-based perspective. It highlights the need for better policies on energy, social security, income distribution and labor protection to weaken AI's effects on household energy consumption and prevent them from falling into energy poverty.

Measurement and analysis of direct and indirect household energy consumption: a case study of China

Household energy consumption is one of the important indicators reflecting the economic development and living standard across countries. Using China’s classified household energy consumption and daily expenditure data from 2011 to 2019, this paper first calculated the overall direct and indirect household energy consumption in China in recent years by means of energy classification and consumer lifestyle analysis (CLA), and then analyzed the characteristics and changes of household energy consumption structure, and the different trends between urban and rural areas in China. We found that 1) Coal consumption occupied the first place in indirect energy consumption, followed by electricity. In terms of the overall trends, whether direct or indirect energy consumption, the proportion of coal was declining while those of electricity and natural gas were increasing year by year. 2) Indirect energy consumption accounted for the majority of the total, and the largest share of that was about housing consumption both in urban and rural areas. The changes in the indirect energy consumption structure of the urban and the rural were quite different. Compared with the indirect energy consumption of the rural, that of the urban showed both a faster growth rate and a larger share in the total indirect consumption, which reflected the inequality trend at present in energy consumption intensity and structure between urban and rural areas in China.

Quality of Life and Relative Household Energy Consumption in China

AbstractIncreasing household energy consumption, mainly due to consumption upgrading, will create tough challenges for China if that country is to achieve peak carbon emissions in 2030 and carbon neutrality in 2060. However, this critical issue has not been explored comprehensively in the literature. Using China Family Panel Studies data and the distribution dynamics approach, this article is the first study to examine the relationship between quality of life (QOL) (proxied by consumption upgrading) and relative household energy consumption (RHEC). The results show that convergence clubs exist in all QOL groups for the RHEC, but they are more evident in the groups with lower middle and low QOL. This is encouraging because they suggest that an improvement in QOL does not necessarily lead to a higher level of energy consumption. The dataset was then divided into rural‐urban and regional subgroups to further explore the impacts of these different characteristics on energy consumption. Significant disparities are found among the same QOL groups between urban and rural households and among different regions. The results derived from this study lead to pragmatic policy suggestions in areas including energy saving, emissions reduction, and particularly alleviation of inequality.

Urban and rural differences with regional assessment of household energy consumption in China

This paper explores the crucial factors driving the changes in household energy consumption (HEC) in China during 2005–2017. We propose a decomposition framework based on the Kaya identity and the logarithmic mean Divisia index (LMDI) method to decompose the change in HEC into energy structure effect, energy intensity effect, regional structure effect, per capita consumption effect and population scale effect. We use the model to shed light on the differences of these five factors affecting HEC between urban and rural and among regions while retaining their energy-use characteristics respectively. The results suggest that: (1) Energy intensity and regional structure reduced HEC, whereas population scales, per capita consumption, and energy structure stimulated HEC growth. (2) Rural energy structure contributed larger shares of the increment in HEC. Rural per capita consumption increased generally much more energy consumption than urban counterpart in coastal developed economic regions. Rural population scale curbed the growth of HEC, while urban population scale drove the growth of HEC. (3) Although energy intensity decreased energy consumption at regional level, the differences were found between regions. Moreover, the impacts of regional structure differed significantly between regions, but insignificantly at provincial level. Finally, some policy recommendations will be made based on these suggestive conclusions.

Impact of marginal and intergenerational effects on carbon emissions from household energy consumption in China

As an important part of urban carbon emissions, the carbon emissions from household energy consumption are increasing with the continuous improvement of Chinese urbanization. This study divides family population into 4 groups: adolescents (aged 0–17), young people (aged 18–44), middle-aged people (aged 45–59), and elderly people (aged 60 and older) and develops a calculation model for carbon emissions of household energy consumption in accordance with the latest standards of the World Health Organization based on Chinese Family Panel Studies in 2016. Results showed that the marginal and intergenerational effects coexist in various types of household energy consumption: Families with 3–5 people have the most economical consumption scale and the largest marginal sharing effect; multigenerational families or families with a large proportion of middle-aged and older people are beneficial in reducing household energy consumption. This paper suggests it is important to fully consider the impact of the intergenerational effect, marginal effect, and cultural shock caused by the electronic information age on household energy consumption when formulating standards of household energy consumption.

Convergence and distribution dynamics of energy consumption among China's households

Whether there will be a long-run equilibrium (steady state) in energy demand per capita is a critical question for energy and environmental policy makers. While many studies have been done on energy production and energy consumption, little attention has been paid to whether disparities in relative household energy consumption (RHEC) converge, and how the use of aggregated data has serious limitations. This paper is the first study to investigate the convergence and dynamics of household energy consumption in China. The results are helpful to Chinese policy makers when trying to identify the key groups for priority interventions. The study finds that variability in the RHEC is very high and that many households will likely change their energy consumption patterns in the coming years. Overall, Chinese households have two convergence clubs. The current dynamics will probably lead to lower energy consumption for most households. The study suggests that policy makers should pay particular attention to households that have too low or too high RHEC level, mainly in rural areas and in the western region.

Dynamic driving and counterfactual decomposition of the influencing factors of household energy consumption among provinces in China

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified.

Features, Driving Forces and Transition of the Household Energy Consumption in China: A Review

Household energy consumption has been a major contributor to the increase in global energy demand and carbon emission, and the household sector has also become one of the most crucial factors shaping the management of developments towards sustainability. However, there is still a knowledge gap regarding the household energy consumption in China. Due to the vast territory and the differences among regional conditions, it is critical to conduct a systemic review to illustrate the overall situation as well as the detailed mechanisms of the household energy consumption in China. By employing both qualitative and quantitative methods, two key features of the household energy consumption in China are presented; one is regarding the total amount and the structure of the household energy consumption, and the second is the significant urban-rural gap. The driving forces are investigated from the perspective of external determinants and internal determinants, which consist of seven key factors; finally, the transition roadmap towards the sustainable energy system for the household level are presented based on the text analysis from the four key policy documents. Weaknesses in the current research on the energy geography of household level also exist, such as the lack of single factor research and the lack of integration and comprehensive analysis. Therefore, future studies need to strengthen the research of regional household energy consumption structure, spatial-temporal process, and its motivation mechanism, and sustainable development of energy, so as to explore space-social structure of household energy consumption and spatial-temporal interaction.

Household energy consumption in rural China: Historical development, present pattern and policy implication

Household energy consumption in rural areas is strongly related to living standards, poverty alleviation, air pollution and health, but lacks solid analysis due to limited data. This paper first presents a systematical overview of rural household energy consumption in China from 1985 to 2013. To quantify and illustrate the pattern of rural household energy consumption, we use a comprehensive household survey, the Chinese Residential Energy Consumption Survey (CRECS, 2013) to illustrate the energy consumption by seven types of energy and five types of end-use demand. Moreover, we compare the rural household energy consumption in terms of quantity, fuel mix and demand structure by North-South regions, East-Middle-West areas and various countries. We identify the biomass still dominate Chinese rural household energy supply while cooking and space heating are the most energy-intensive demand. The overall energy efficiency for a rural household is 33%, mainly attributed to the massive use of biomass. Policy implications are summarized and discussed.

Calculation and decomposition of regional household energy consumption in China: based on perspectives of urbanization and residents’ consumption

ABSTRACTDemographic urbanization caused great changes in scale of residents’ consumption and residents’ lifestyle and then impacted changes of regional household energy consumption. This paper expanded Logarithmic Mean Decomposition Index method through introducing variables of urbanization and residential consumption into the model. It also analyzed the influences of six factors as energy structure, energy intensity, population scale, urbanization, residential consumption, and consumption inhibit on regional household energy consumption. Results showed that in 2003–2012, impact of urbanization on regional household energy consumption of Chinese three areas was significantly higher than population size. The “population gathered in eastern region” phenomenon caused eastern region getting the largest population scale effect. Driving force of residential consumption on regional household energy consumption was much higher than the other five effects. Due to the comparative advantage of residential consumptio...

Factors Influencing the Spatial Difference in Household Energy Consumption in China

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.

Driving Forces of Direct Carbon Emission From Urban and Rural Household Energy Consumption in China

In China, economic growth stimulates urban expansion and rural household income and consumption expenditure. The study calculates direct carbon emission from the energy consumption of Chinese urban and rural household and applies LMDI (Logarithmic Mean Divisia Index) decomposition model to identify the driving forces that influence variations in residential direct carbon emission. The result shows that direct carbon emission of urban residents is always higher than that of rural and there is still a significant gap between them. Income lever effect and energy structure effect present positive impact on both urban and rural residential emission, while the emission intensity effect plays a negative role. In addition, population size plays positive effect on urban residential direct carbon emission, while negative role on rural. The study concludes with the policy implications

Direct and Indirect Household Energy Consumption in China

Nowadays, China has paid much attention to industrial energy consumption. In fact, household energy consumption, close related to everyones daily life, is playing a more and more important role. In this paper, we utilize input-output model to obtain the value of indirect household energy consumption. We find out the structures of direct and indirect consumption and the gap between rural and urban energy consumption. The results show that the energy consumption structure is cleaner than before, and the gap between rural and urban energy consumption is narrowing. We make the suggestions that clean coal technology is badly needed and supplying more natural gas is helpful.

Energy consumption practices of rural households in north China: Basic characteristics and potential for low carbon development

Reducing the climate impact of rural household energy consumption in China is complicated since it is bound up with deeply routinized daily practices and dependent from existing infrastructural systems of energy supply. To assess the potential for low carbon development we first estimate the overall CO2 emissions of rural households, followed by a more in depth description and characterization of the different energy use practices within the households. Space heating turns out to be the largest emission source among domestic energy practices in north China. We present lifestyle and context related factors that help to explain existing differences in domestic energy use practices of households. The potential for low carbon development is discussed both at the demand side and the supply side. At the demand side, the use of more efficient technologies and cleaner energy sources for space heating seems to be a high potential measure for achieving low carbon households. At the supply side the reduction of rural domestic CO2 emissions could be effectively supported by making available to householders renewable and cleaner energy sources and technologies. In order to be effective, such low carbon energy options should take into account the (income) characteristics and lifestyles of rural householders.

Empirical analysis of rural household energy consumption in China

Rural household energy consumption in China influences people's living conditions, environmental issues and economic development. So it is worthwhile to study the rural household energy consumption and its developmental propensity in rural China. In this paper, we analyse the characteristics of energy consumption and how it changes over time. Panel data regression method is used to analyse the factors which influence energy consumption, along with differences among three regions in China. The result shows that rural household energy consumption is closely related to urbanisation and historical periods of energy consumption. If there is a 1% increase in both urbanisation and energy consumption in the previous period, then current energy consumption will increase 0.74?0.92% and 0.25?0.60% respectively.

05/00935 Study on affecting factors and standard of rural household energy consumption in China

05/00935 Study on affecting factors and standard of rural household energy consumption in China

On household energy consumption for rural development: a study on Yangzhong county of China

Villages of Yangzhong County, typical of comparatively well-off countryside in Eastern China, are in a period of rapid transformation of their energy consumption from non-commercial to commercial. A five-year questionnaire of rural household energy consumption showed marked change in energy consumption structure, rapid increase in electricity and LPG consumption, decrease in straw and stalks and coal energy consumption, relatively stable per capita energy consumption, but a little increase in effective energy consumption. It is shown that per capita energy consumption relates to per capita income, average number of persons per household, and per capita output of crops. This paper discussed the nature of rural household energy consumption, the general features of comparatively well-off rural household energy consumption in China, etc.

Survey of rural household energy consumption in China

Based on comprehensive energy surveys of 3240 households in six different regions, we present the level and structure of rural household energy consumption. There are large differences among regions which depend on locality and availability of fuels. Energy consumption per household accounts for 700–1200 kgce (we use 7000 kcal/kgce), 40–60% of which is used for cooking; 60–90% of total household energy consumption is in the form of biomass. The average energy-conversion efficiency using biomass fuels is in the range 10–20%. Where the strain of traditional patterns of biomass use on the resource base became too severe, the balance between local agricultural and hillside ecosystems has unraveled and caused accelerating destruction of limited land resources. Higher income households need more commercial energy, especially in the form of electricity. Rural household energy will continue to depend mainly on biomass.