Energy Consumption Inequality Research Articles

Analyzing the regional inequality of renewable energy consumption and its driving factors: Evidence from China

To achieve the goal of “carbon peaking and carbon neutrality”, China is vigorously developing renewable energy. This paper aims to examine the major contributors to regional inequality in renewable energy consumption by analyzing the 30 provinces in China. We have analyzed the inequality of China's renewable energy consumption with Dagum Gini coefficient, and then use the Generalized Divisia Index Model (GDIM) to decompose the influencing factors contributing to the inequality of renewable energy consumption. The main conclusions are summarized as follows: First, renewable energy consumption was higher in the western region than in the central and eastern regions, and the regional inequality in renewable energy consumption have increased over time. Second, the study reveals that inter-group disparity is the primary source of regional inequality in renewable energy consumption in China. Third, at the national level, the results of the GDIM decomposition show that economic development continues to rely on fossil energy consumption, which negatively impacts the low-carbon transition of energy. Given China's complex geographical conditions, it is crucial for different provinces to develop their own strategies for renewable energy development, taking into account unique resources and challenges.

A step towards a just transition in the EU: Conclusions of a regression-based energy inequality decomposition

The conceptual and regulatory framework of the European just transition does not consider inequality in household energy consumption. This study addresses the causes of this inequality across the 27 Member States of the European Union (EU) in the period 2010–2020 to contribute to its reduction. To identify these causes, the regression-based inequality decomposition approach is used. The results show that the variation in per capita gross domestic product (GDP), which contributes 38.76% to the inequality of household energy consumption, is the main cause of this inequality. Moreover, the average contribution of GDP per capita in the inequality of household energy consumption is almost negligible in the most developed states. In contrast, it is much higher in the least developed states, suggesting that decoupling between household energy consumption and economic development has not been achieved in all Member States. To promote a just transition to climate neutrality by 2050, the energy transition framework should therefore be broadened to help the least developed states achieve decoupling and align their energy consumption with that of the most developed states.

A cross-country analysis of sustainability, transport and energy poverty

Poverty impacts people’s choices and opportunities and can perpetuate a disadvantaged status. Poverty remains a prevalent global issue due to disproportionate wealth distribution, which often translates to inequality in energy consumption and emissions. This research investigates if low-income households and minorities from four countries with very different national cultures, contexts, and levels of wealth experience a ‘double energy vulnerability’, a concept that simultaneously positions people at heightened risk of transport and energy poverty. Our research identifies that low-income households and minorities are at higher risk of simultaneously experiencing energy and transport poverty regardless of the national context in which they live. Our study also contests the achievement of Sustainable Development Goals (SDGs) by 2030, showing that even in relatively wealthy countries, many individuals still face energy and transport poverty. We conclude that global sustainable development requires significant shifts in policy action, resource distribution and investment in social services.

Impacts of targeted poverty alleviation on urban-rural residential energy consumption inequality: Evidence from 178 Chinese prefecture-level cities

China's targeted poverty alleviation (TPA) policy is a revolutionary approach to poverty governance with profound implications for eliminating poverty in rural areas. However, previous studies did not explore whether the TPA policy can reduce energy consumption inequality between urban and rural residents (UREI). Therefore, our study aims to investigate the impact of the TPA policy on UREI. We first construct UREI estimates for 178 prefecture-level cities in China covering the period from 2010 to 2020 using the Theil index. We then apply the difference-in-differences (DID) method to examine how the TPA policy affects UREI. Our empirical results confirm that the implementation of the TPA policy can significantly reduce UREI by 0.8%. Moreover, our dynamic effect analysis shows that the TPA policy has a lag effect on UREI that progressively deepens over time. Our heterogeneity analysis further indicates that the TPA policy has a significantly negative impact on UREI in the coastal region, while it has a significantly positive impact in the inland region. Based on these findings, we highlight several relevant policy implications for the Chinese government to enhance the benefits of rural-oriented policies in reducing UREI during the rural revitalization process.

Energy inflation and consumption inequality

This paper examines the effects of higher energy prices on consumption inequality for a large panel of 129 advanced and developing economies during the period 1970–2013. The results suggest that energy inflation increases the Gini measure of consumption inequality and reduces (increases) the share of consumption of lower (higher) income deciles. These effects are larger in developing economies, in countries with limited access to finance, in those with weaker monetary policy frameworks, during periods of economic slack and in cases where government transfers do not compensate the poorer deciles during times of adverse income shocks.

The impact of internet use on rural household energy transition: moderating effect based on social interaction

Introduction: Household energy transition is the key to changing and upgrading China’s energy consumption pattern. Directly using traditional biomass fuels is not only one of the reasons why the opportunity between urban and rural areas is inequality but also a critical symbol of the inequality of energy consumption within rural areas.Method: This study investigates the association between two information acquisition mechanisms, namely, Internet use and social interaction, and rural household energy transition, using CGSS 2015. After converting the consumption of each fuel to standard coal, according to the energy ladder theory, this study classifies the main types of household energy into three categories: primitive fuels, transition fuels, and advanced fuels. Then this study uses the ordered probit model to empirically analyze 1023 rural household samples in China.Results: The results show that, compared to rural households that never use the Internet, an increase in the frequency of Internet use significantly enhances the probability of rural households using advanced fuels, while decreasing the probability of using primitive and transition fuels simultaneously. However, the effect direction of social interaction works is the opposite of Internet use completely. The intrinsic mechanism result shows that although social interaction reduces the strength of the role of Internet use in rural household energy transition, it has not yet completely offset the positive effect of Internet use on the rural household energy transition.Discussion: The results of this study provide references for removing the blocking barriers to contact and use of the Internet by rural residents, improving the perceived quality of obtained information through social interaction, and solidly promoting rural energy transition and sustainable development of resources and the environment.

Per capita CO2 emission inequality of China's urban and rural residential energy consumption: A Kaya-Theil decomposition

With the increasing affluence, the differences in CO2 emission between urban and rural residential sectors are remarkable and show an increasing trend. In case of China, residential sector accounts for a substantial share of the national CO2 emission, bringing greater pressure to achieve the goal of carbon peak. Analyzing the emission inequality trend and its drivers is essential for formulating effective CO2 emission reduction policies. However, the existing literature lacks relevant analysis from the viewpoint of urban-rural disparity. Hence, this study decomposes the CO2 emission inequality of China's urban and rural residential consumption into four factors by combining the Theil index and Kaya decomposition. The results suggest that, in 2005–2020, the per capita CO2 emission of rural residential consumption increased to a higher extent than those of urban households, with large differences in spatial distribution. Decomposition of the per capita CO2 emission inequality for residential sector shows that the primary source is the inequality within the groups, mainly from the urban intra-group inequality. Based on the static decomposition, energy intensity appears as the main factor of urban–rural inequality. The dynamic decomposition shows that there have been differences in the factors of the change in the Theil index between urban and rural areas across sub-periods.

Inequality in urban household energy consumption for 30 Chinese provinces

Reducing inequality in energy consumption is critical for sustainable development and the achievement of climate goals. Using an environmentally extended input-output analysis, this study measured the urban household energy consumption of different income groups in China for the years 2012, 2015, and 2017. Gini coefficients were used to measure inequality within each province, while the regional environment inequality index was used to measure inequality between provinces. The energy consumption showed a decreasing trend from the eastern coast to the western interior. In contrast, the per capita energy consumption showed an increasing trend from the southeastern coast to the northwestern interior. In 2015, the high-income groups accounted for 45% of the country's total energy consumption, while the low-income groups accounted for only 4%. Between 2012 and 2017, the level of inequality in energy consumption between provinces gradually increased, while the level of inequality within provinces gradually decreased. Among the various consumption categories, the Gini coefficients for necessities were generally smaller, whereas those for services were generally larger. However, the differences between consumption categories gradually decreased.

Energy consumption inequality in China: What can an agent-based model tell us?

China is a major energy consumer, however, related empirical research on China's unequal energy consumption is very limited. Therefore, according to the data from 30 provinces and cities, this study aims to establish a simulation model to analyse the Gini coefficient (the Lorenz curve) of China's energy consumption, and identify the main factors affecting the Gini coefficient through dynamic scenario analysis. During the simulation cycle (from 2022 to 2081), the average Gini coefficient of energy consumption fluctuates between 0.30 and 0.41, which indicates the inequality is slightly high. But the maximum value fluctuation ranges from 0.40 to 0.50, which indicates the inequality is high. The author also found that three factors—technological level, government subsidies, and growth rate of energy supply—can significantly affect the Gini coefficient of energy consumption. It is necessary to promote the technological level, increase subsidies for energy production, and promote the growth of total energy supply to significantly reduce inequity in energy consumption.

Inequalities in Regional Level Domestic CO2 Emissions and Energy Use: A Case Study of Iran

An increasing amount of CO2 emissions from the household sector of Iran led us to analyze the inequality and understand the possible driving force behind the CO2 emissions. The study of inequality provides information to policy-makers to point policies in the right direction. By considering the differences in the socio-economic factors of provinces, the study aims to analyze the inequality in CO2 emissions and different kinds of energy consumption, including oil, gas and electricity, for the household sector of Iran’s provinces between 2000 and 2017. For this aim, the Theil index and Kaya factor, as a simple and common method, were considered to evaluate the inequality in both CO2 emissions and energy consumption, and determine the driving factor behind CO2 emissions. According to the results, inequality in oil and natural gas consumption were increasing, electricity was almost constant; however, CO2 emissions experienced a decreasing trend for the study period. The Theil index changed from 0.4 to 0.65 for oil, from 0.18 to 0.22 for natural gas, from 0.17 to 0.15 for electricity, and from 0.2 to 0.14 for CO2 emissions between 2001 and 2017. In addition, the results of the inequality study indicated that most of the inequalities belong to within-group inequalities in energy consumption and CO2 emissions. The results of the Kaya factor indicate that the second factor, energy efficiency, with a 0.21 value was the main driving factor of inequalities in CO2 emissions; however, the first factor, energy consumption, can be a potential factor for inequality in the following years, as it increased from 0.00 to 0.11 between 2001 and 2017. It seems that by removing the energy subsidy policy in 2010 and 2013, low-standard and energy-wasting old vehicles were the most effective factors of energy inefficiency in the household sector, which need more accurate policy-making.

Analysis of the efficiency and structure of energy consumption in the industrial sector in the European Union countries between 1995 and 2019

The industrial sector is one of the most important sectors of the global economy, having a huge impact on the development of individual countries and regions. This sector covers a wide and diverse range of activities, which makes it of key importance for the economy of the European Union (EU) countries. As a result, the processes related to energy transformation and climate policy are increasingly connected with the sector in question. The need to improve the competitiveness of the economy and the implementation of climate and energy strategies means that this sector, like the entire EU economy, must rapidly enhance its energy efficiency and the structure of energy consumption. The following paper addresses this problem by presenting the results of a comprehensive study of the structure and volume of energy consumed by this sector in the period between 1995 and 2019. Based on this study, quantitative changes and the structure of energy consumed in this sector in the studied period were determined for the entire EU and its individual countries. The use of the Gini coefficient and the Lorenz curves allowed for the determination of the inequality of energy consumption in the industrial sector. The coefficients of variation and the dynamics of changes in energy consumption, both in total and from individual sources, for the EU countries were also determined. The aim of this part of the study was to indicate directions and the intensity of changes related to the structure and consumption of energy in this sector. In the next stage, groups of similar countries were created and compared in terms of the structure of energy consumed by the industrial sector in 1995 and 2019 (using the Kohonen's neural network). Relationships between the amount of energy consumed by the industrial sector in the entire EU and the basic economic and climate parameters of the economy were also delineated. The energy intensity of this sector and the dynamics of its changes in individual EU countries over the analyzed period were also specified. The results proved a great diversity of the EU countries and the improving energy efficiency and structure of energy consumed by the industrial sector. The research, together with its results, significantly broaden the knowledge of changes in the volume and structure of energy consumption in the industrial sector for the EU countries. The results make it possible to assess the actions of individual countries and the current state of implementation of EU climate and energy policy. They should also be used to develop future assumptions of this policy.

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Energy consumption inequality decrease with energy consumption increase: Evidence from rural China at micro scale

How to achieve no poverty and reduce inequalities are among the core mission of the United Nations sustainable development goals. These goals also play an important role in China's poverty alleviation. In this paper, energy consumption is used as a proxy to measure living standards. Based on the data of 1010 Chinese households in 100 villages, energy consumption status and corresponding inequality at the village level were analyzed. The results showed that the per capita energy consumption of rural areas in China in 2018 was 862.94 kg coal equivalent, among which the main types were biomass and electricity. The regression analysis shows that the latitude and altitude, the distance to county center of the villages, average age, education level, and financial assets of the villagers are the main factors affecting the energy consumption of the villages. With the increase of per capita energy consumption, the Gini coefficient and Theil index both showed a downward trend, meaning energy poverty alleviation and inequality reduction are simultaneously achieved in rural development. The results of this study identify the key factors needed to increase energy consumption and energy efficiency at the village level and provide valuable reference for China's rural energy transformation.

Energy inequality in the Eurasian Economic Union

This paper aims at assessing energy inequality, which is at the center of SDG7, in the Eurasian Economic Union – a recently created international organization with arguably the closest integration in the energy sphere for all member states: Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia. The research was performed with the use of cross-disciplinary methods, including literature review, analysis of policy documents (applied policy analysis), and two quantitative tools widely used for energy policy analysis – the decomposition of energy consumption based on the Logarithmic Mean Divisia Index and the inequality estimation by using the Theil index. The study identified contribution of three types of factors to energy consumption of the entire Eurasian Economic Union: economic growth − the increase of GDP, the relative structural changes in the economy, and energy intensity shifts. Theil index allowed determining the level of inequality in the region's energy consumption. The quantitative analyses demonstrated that in 2000–2017 the increase of GDP and energy intensity in the region were the main reasons that had determined the growing energy consumption. Theil index analysis showed that inequality of GDP-related energy consumption is decreasing, whereas the population-related inequality is increasing. Additionally, policy implications for inclusive and sustainable energy integration in the region are discussed. The required policy changes range from introducing amendments to the Eurasian Economic Union Treaty and structural changes to very precise science and technology policy tools.

Reforming energy prices to achieve sustainable energy consumption in the agriculture sector of Iran’s provinces: Using game approach

The agriculture sector of Iran’s provinces, as one of the main factors of Iran’s total CO2 emissions, has an increasing trend in fossil energy consumption due to lacking a specific energy market and irrational pricing by the government. Hence, it is necessary to focus on approaches that can determine optimum prices for controlling both energy consumption and CO2 emissions. In this regard, the study aims to find an optimum price and sustainable amount of fossil energy consumption (including gasoline, natural gas, and electricity) in the agriculture sector of Iran’s provinces during 2001–16. We proposed both cooperative and non-cooperative game models based on competitive and seller monopoly markets to find an equilibrium price and demand with Nash equilibrium. Cost and demand-supply function coefficients estimated after the formulation of the problems in the markets, and then game-based models optimized to find reformed prices and demands. Empirical results highlight that both proposed game-based models can modify different types of energy consumption, as well as energy prices. Also, it seems that the cooperative game model can provide optimum prices for different groups of energy users, smooth the inequality in energy consumption, and prevent a sharp reduction in both GDP and agricultural production. On the contrary, the non-cooperative game model was appropriate for the next years.

Global redistribution of income and household energy footprints: a computational thought experiment

Non-technical summary Global income inequality and energy consumption inequality are related. High-income households consume more energy than low-income ones, and for different purposes. Here, we explore the global household energy consumption implications of global income redistribution. We show that global income inequality shapes not only inequalities of energy consumption but the quantity and composition of overall energy demand. Our results call for the inclusion of income distribution into energy system models, as well as into energy and climate policy. Technical summary Despite a rapidly growing number of studies on the relationship between inequality and energy, there is little research estimating the effect of income redistribution on energy demand. We contribute to this debate by proposing a simple but granular and data-driven model of the global income distribution and of global household energy consumption. We isolate the effect of income distribution on household energy consumption and move beyond the assumption of aggregate income–energy elasticities. First, we model expenditure as a function of income. Second, we determine budget shares of expenditure for a variety of products and services by employing product-granular income elasticities of demand. Subsequently, we apply consumption-based final energy intensities to product and services to obtain energy footprint accounts. Testing variants of the global income distribution, we find that the ‘energy costs’ of equity are small. Equitable and inequitable distributions of income, however, entail distinct structural change in energy system terms. In an equitable world, fewer people live in energy poverty and more energy is consumed for subsistence and necessities, instead of luxury and transport. Social media summary Equality in global income shifts household energy footprints towards subsistence, while inequality shifts them towards transport and luxury.

Racial disparities in energy poverty in the United States

This study uses data on residential energy consumption from large nation-wide surveys in 1990, 1997, 2005, and 2015 to assess the racial inequality in residential energy consumption. The results indicate that the overall inequality in energy consumption/cost varies little over the past 25 years while showing widespread energy poverty in the U.S. In terms of racial differences, African-American households are more vulnerable than white and Asian households, and about one-third of them lived in energy poverty by 2015. However, the share of households in energy poverty witnessed the greatest growth among white households during 1990–2015. In addition, the energy burdens of different racial groups vary greatly with respect to energy types, end-use demands, and regions, given the differences in climate and households’ socio-economic characteristics. The study suggests that besides low-income African-American households, urgent attention should be given to the increasing number of white households in energy poverty.

A Social Welfare Theory-Based Energy-Efficient Cluster Head Election Scheme for WSNs

Inequality of energy consumption in the wireless sensor networks (WSNs) leads to the decline of energy efficiency and the shortening of the network lifetime. In this article, the social welfare theory is adopted to promote energy equilibrium during the process of Cluster Head (CH) election. To the best of authors' knowledge, it is for the first time that the CH election is controlled by the systematical social theory. To this end, Atkinson's Inequality Measure is applied to elect the optimal CH. Besides, a novel concept of expected energy efficiency welfare is proposed to determine the CH, with the aim of achieving energy equilibrium within each cluster. Subsequently, a novel Social Welfare theory-based Energy-efficient Cluster head Election (SWECE) scheme is proposed and detailed. Finally, extensive experiments are conducted to evaluate its performance with regards to energy efficiency and network lifetime by extensive comparisons with the existing classic and the latest intelligent clustering strategies. The results have verified its effectiveness on improving energy efficiency and prolonging the network lifespan of WSNs.

Inequality in energy consumption: statistical equilibrium or a question of accounting conventions?

Understanding inequality energy consumption at the global level delivers key insights for strategies to mitigate climate change. Recent contributions [4, 28, 48, 49] have studied energy inequality through the lens of maximum entropy. They claim a weighted international distribution of total primary energy demand should approach a Boltzmann-Gibbs maximum entropy equilibrium distribution in the form of an exponential distribution. This implies convergence to a Gini coefficient of 0.5 from above. The present paper challenges the validity of this claim and critically discusses the applicability of statistical equilibrium reasoning to economics from the viewpoint of social accounting. It is shown that the exponential distribution is only a robust candidate for a statistical equilibrium of energy inequality when employing one particular accounting convention for energy flows, the substitution method. But this method has become problematic with a higher renewable share in the international energy mix, and no other accounting method supports the claim of a convergence to a 0.5 Gini. We conclude that the findings based on maximum entropy reasoning are sensitive to accounting conventions and critically discuss the epistemological implications of this sensitivity for the use of maximum entropy approaches in social sciences.

Inequality of household energy and water consumption in China: An input-output analysis

Household consumption activities affect energy and water consumption directly and indirectly. Based on input-output modeling, this paper divided Chinese urban and rural residents into 12 groups, and investigated the impact of the consumption activities of residents with different levels of income on China's energy and water consumption from the perspective of consumers. Two main results were found. 1) In 2012, the energy consumption caused by the consumption activities of the highest-income urban residents accounted for 17.3% of the total energy consumption. For water resources, the per capita water withdrawal and consumption of the highest-income urban residents reached 481.21 m3 and 284.45 thousand m3, 6 times more than that of the low-income rural residents. 2) We identified medium and medium-high income urban residents as the key groups of residents. From the perspective of the industrial sectors, the key sectors for high energy consumption and water usage included the Electricity and Agricultural sectors, and we identified the Electricity sector as the key sector for the water and energy nexus of the residential sectors. The conclusions of this paper have pertinence for policymaking, and they provide an appropriate policy basis for guiding residents' energy and water consumption.