Inequality In Emissions Research Articles

Red versus blue states: Inequality in energy-related CO2 emissions in the United States (1997–2021)

The partisan divide over climate change issues in the U.S. has been increasing over time, particularly after the signing of the Kyoto protocol in 1997. This divide has posed a substantial hurdle to implementing a unified climate policy in the U.S. In this paper, I employ the Shapley value decomposition approach to measure the partisan gap in state-level per capita energy-related CO2 emissions. Despite a decrease in overall carbon emissions and stable per capita carbon inequality between states (measured by the Gini index), the inequality between the so called ‘red’ and ‘blue’ states widened over the period between 1997 and 2021. This is true regardless of whether each state is treated as a unit of analysis or assigned a weight equal to its population. Throughout the period, the divide by political party color was more pronounced than that by many other dimensions, such as income, climatic condition, and geographic location. These results also hold true when Mean Log Deviation is used as the measure of inequality. Driven primarily by disparity in transportation sector and coal use for electricity generation, the partisan gap was worse in 2021 than in 2020. While the partisan gap intensified, the carbon distribution changed from being top-concentrated to bottom-concentrated between 1997 and 2019, only to be reversed in the aftermath of the coronavirus pandemic in 2020 and subsequent economic recovery in 2021.

Emission inequality: Comparing the roles of income and wealth in Belgium and the United Kingdom

Many studies have investigated the distribution of greenhouse gas emissions associated with household consumption, highlighting that richer households have a substantially larger carbon footprint than poorer households. While these studies have typically used income or household expenditures as a proxy of households’ living standards, the association between emissions and wealth has hardly been studied. Wealth is not just an important component of households’ material living standards, known to be imperfectly correlated with income and expenditures, but it is also a very relevant dimension for climate policies. For instance, affluent households have more scope to invest in reducing emissions (e.g. insulation of their homes). Therefore, in this paper, we compare the inequality of emissions over wealth groups as well as groups defined by other living standard concepts such as income, expenditure and the joint distribution of income and wealth to add a focus on wealth to the analysis of emission inequality. Our study focuses on Belgium and the United Kingdom, which differ considerably in their level of wealth inequality. Our results highlight that the social distribution of emissions varies between expenditures, income, wealth and the joint distribution of income and wealth, with per capita emissions being more strongly associated with the joint distribution of income and wealth than with income alone. We also show that a significant share of households has both low income and low wealth, and may thus be lacking the means to prepare for a carbon-neutral future. Although increasing wealth taxation could provide much-needed revenues for low carbon investments, our results suggest that it would have a lower direct impact on the level of emissions and emission inequality compared to increasing taxes on high incomes.

Evolution and driving factors of inequality in CO2 emissions from agricultural energy consumption in China

The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China’s agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya–Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China’s agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

Unequal household carbon emissions and potential determinants in China: Evidence from nationwide household surveys

Reducing carbon emissions from households can significantly contribute to achieving carbon neutrality. This study examined household carbon emissions and explored potential issues of inequality in China from 2010 to 2018. We found that the average carbon emissions of all households increased over the years, with the housing category experiencing the highest growth rate of 52.25%. Household carbon emissions are not the same across different regions and income groups. Inequality in carbon emissions is the highest in the eastern part of the country, followed by the central and western regions, and the lowest in the northeast. Carbon emissions inequality is highest among middle-income households, followed by high-income households, and the lowest among low-income households. These differences can be attributed to various factors such as population, technology, and socio-economic status. This study recommends implementing regional carbon taxes and income differential tax policies to address household carbon emissions inequalities.

Impact assessment of poverty alleviation on carbon inequality: evidence from households in China

Inequality and climate change are major challenges for sustainable development, but a dilemma between the objectives has been widely observed. Based on the panel data of China Household Finance Survey (CHFS), inequality in carbon emissions across income groups is witnessed, which provides basics for the study. From a quasi-natural experiment, an increase of 9.9% in household per capita carbon emissions (HCEs) of the impoverished group is found after the Targeted Poverty Alleviation policies (TPA) in China, providing evidence for the enhancement of poverty alleviation measures on equal right for household carbon emissions. Specifically, dual mechanism of transfer payments and employment assistance acting as direct and indirect strategies to enhance family wealth are examined as the pathways to carbon equality. Further, a decline in household carbon emission intensity in the impoverished group is also observed after the treatment, which implies the accelerating role of TPA in low-carbon lifestyle formulation for the impoverished families. The findings of this paper confirm the positive effect of TPA policies on carbon equality for households, and also refute the "equality-pollution dilemma", which provide insights for policy makers in formulating equitable decarbonization policies and allocating the carbon budget.

Enlarged carbon footprint inequality considering household time use pattern

Examining household carbon emissions through a supply chain perspective reveals the climate impact of consumption behaviors and variations across societal structures and features. Despite the evident and expanding environmental inequality, strategies for its mitigation and prioritization remain debated. This study investigates the origins of carbon emission inequalities from household consumption, using Japan as a case study, a society characterized by aging demographics and comparatively equal income redistribution. By quantitatively analyzing household carbon footprints, we observe a U-shaped distribution in emissions as income levels increase. Notably, the carbon footprint sizes are strikingly similar between the lowest and highest income groups, yet inequalities emerge in education and investments in future generations. Integrating these findings, this study further conducts a scenario analysis to project shifts in future low-carbon lifestyles, indicating that middle-income groups are more prone to achieving personal-level decarbonization. This projection is vital in understanding how to effectively address carbon footprint inequalities, especially considering the entrenched preferences in wealthier demographics for investing in future generations.

Climate Change Paradox: The Least Responsible for It Encounters the Most of Its Implications

Carbon dioxide (CO2) emissions are a major cause of climate change. However, CO2 emissions data for 178 countries from 1960 to 2018 revealed inequality in global CO2 emissions. For example, we found that 50% of the world’s population (ca. 3.75 billion people) was responsible for just 8.9% of the global cumulative carbon emissions. These people are concentrated in low- and middle-income countries. Conversely, 10% of the world’s population (ca. 757 million people), concentrated in high-income countries, were responsible for 46.8% of the global emissions. Furthermore, the literature review disclosed evolution of CO2 emission inequalities within countries. A significant (p < 0.001) negative (r2 = −0.52) correlation was detected between carbon emissions and climate change impacts on national incomes. Such correlation indicated that countries most likely to experience the greatest effects of climate change are also those who make the smallest contributions to its underlying causes. Similar disparities were observed within countries where low-income groups who make the smallest contributions to climate change are subjected to its worst implications. Evaluations of the data from the literature showed that migration could be the result of climate change, though such migration does not happen in isolation. In other words, this kind of migration is frequently linked to other issues such as the fragility and lack of adaptability of the communities. Furthermore, reviews showed that climate change catalyzes instability and conflict. On the other hand, conflict damages the environment and climate in multiple ways. Therefore, it is necessary to collaborate to resolve these two issues concurrently.

Regional disparities, dynamic evolution, and spatial spillover effects of urban-rural carbon emission inequality in China

ObjectiveThis study recalculates the carbon emissions of urban and rural residents in China, analyzing the dynamic evolution trends of urban and rural carbon emissions. It explores the spatial spillover effects centered around the inequality in carbon emissions between urban and rural areas.MethodsThe study calculates the carbon emissions of urban and rural residents in each province based on the IPCC method. Non-parametric kernel density estimation is employed to depict the dynamic evolution characteristics of national, urban, and rural carbon emissions. The Theil Index is used to measure the disparities in urban and rural carbon emissions in major strategic regions, further applying the Theil Index to evaluate the inequality of urban and rural carbon emissions across provinces. This helps identify the driving factors affecting the inequality of urban and rural carbon emissions and their spatio-temporal effects.FindingCarbon emissions from urban and rural residents in China present a divergent development pattern. Urban emissions have increased, with inter-provincial disparities widening; rural emissions tend to stabilize, with slight growth in inter-provincial gaps. The overall inequality of carbon emissions in various regions of China experiences a three-phase journey of rise, decline, and stabilization. Urban inequality first increases then decreases, while rural inequality gradually lessens, showing clear regional and urban-rural differences. Market and government factors significantly impact the inequality of urban and rural carbon emissions. The development of the digital economy aids in reducing inequality and generates significant spatial spillover effects. The relationship between economic development level and carbon emission inequality is U-shaped. Industrial structure optimization can reduce urban-rural inequality, but its spatial spillover effect is not significant. Government intervention has limited effects, while environmental regulations may increase inequality. Opening up to the outside world helps reduce inequality, and the impact of population density is complex.

Unequal transfer and its policy implications of carbon emissions and economic benefits embodied among Central Plains urban agglomeration

Tracing the carbon emissions and economic benefits embodied in trade is crucial for the equitable allocation of mitigation responsibilities, particularly among cities in China, where studies on this topic are lacking. Therefore, this study selected the Central Plains Urban Agglomeration (CPUA) as a representative region. It compiled carbon emissions inventories following the 2006 IPCC guidelines and employed the multi-regional input-output model to investigate the trade-attributed embodied carbon emissions and value-added. Additionally, it estimated the unequal transfers of these emissions and value-added by introducing the City Carbon Emissions Inequality index (CCEI). The results indicate that the CPUA received net carbon emissions of 454.99 and 330.95 Mt. from outside regions from 2012 to 2017. Nearly half of the territorial carbon emissions were driven by the consumption of other cities, and Zhengzhou and its surrounding cities transferred the most carbon emissions to the outer-ring cities by consuming the primary products produced in these cities. The construction sector was the largest exporter of both embodied emissions and economic benefits, while the energy and service industries were the largest importers of carbon emissions and economic benefits. Such imbalanced transfers contributed to carbon inequality, with the CCEI mean increasing from 0.31 to 0.38 for the exacerbation of intercity imbalances in development. Significant carbon inequality occurred between Zhengzhou and its upstream cities, e.g., Luoyang and Shangqiu, and among some neighboring cities, e.g., Yuncheng-Jincheng and Luoyang-Jiyuan. Our findings provide evidence of a need for compensation mechanisms and collaborative strategies for carbon mitigation in the urban agglomeration.

International inequality in energy use and CO2 emissions (1820–2020)

Global inequality is made up of two components: inequality within countries and between countries. Over the last two centuries, the second component has strongly shaped global inequality. However, little is known about its evolution over time, and nothing at all about inequality in energy use and greenhouse gas (GHG) emissions. This article presents a comprehensive reconstruction of international divergence and convergence from the side of energy consumption and CO2 emissions over two centuries. From 1820 to 1919, inequality between countries increased and so did inequality in GHG emissions. This increase was followed by ups and downs until the 1970s, when a decline of international inequality began. Convergence in both energy consumption and GHG emissions accelerated after 2000.

Measuring the rebound of Japan's per-industry household carbon footprints and emission inequalities during the COVID-19 pandemic in 2020–2021

This study examined the COVID-19 crisis’ impact on household carbon footprints (CFs) in Japan associated with consumption changes from 2020 to 2021, focusing on the employment industries of household heads. We emphasized the influence of associated lifestyle shifts on inter-household emission inequalities, as indicated by the CF-Gini coefficient. Most of the average per-capita CFs were 2.9 % (range: -7.9–5.2 % among industries) lower in 2020 than pre-COVID-19 levels. However, in 2021, the average per-capita CF increased by 3.6 % (-12.2–17.2 %), and the CFs of most employment industries rebounded. This was likely due to the movement restriction relaxation stemming from increased COVID-19 vaccination and state-of-emergency declaration differences. Hence, lifestyle changes caused the CF-Gini to fall below pre-COVID-19 crisis levels, and the rebound of consumption demands became evident. Thus, greater attention should be directed toward demand, specifically for technological innovations and economic support measures that reduce the CF and emission inequalities.

Artificial intelligence and carbon emissions inequality: Evidence from industrial robot application

To figure out equitable and inclusive strategy to mitigate inequality of carbon emissions, we investigate the solution to narrowing carbon inequality from the perspective of developing artificial intelligence by using the generalized method of moments model and employing a panel dataset from 74 countries during 2000–2019. The asymmetric impact of artificial intelligence on carbon inequality is also checked. In addition, we examine the moderating and mediating effects in the nexus between artificial intelligence and carbon inequality. We find that (1) artificial intelligence has a negative causal relationship with carbon inequality, which indicates that developing artificial intelligence is essential for narrowing carbon inequality. (2) With the increase of the quantile of carbon inequality, artificial intelligence exerts a more remarkable inhibiting effect on carbon inequality, which implies that when the level of carbon inequality is more severe, the implementation of artificial intelligence proves to be a more potent tool for narrowing the disparity of emissions. (3) With the help of climate finance, artificial intelligence becomes even more effective in reducing carbon inequality, verifying the synergistic effect of climate finance and artificial intelligence on carbon inequality eradication. (4) Energy structure transition and industry structure transition are pathways through which artificial intelligence affects carbon inequality. Some concrete policy implications are drawn from the above main findings.

Energy justice and gaps in sustainable development: A convergence testing and clustering study

The purpose of the study is to examine the dynamics of carbon emissions inequality and its effect on energy justice, whether carbon footprints have increased or decreased across countries, sectors, and households over time. We use convergence analysis, which is a methodology that effectively reveals carbon footprint dynamics. Our database contained carbon footprint data from different sectors across 180 countries between 1980 and 2020. We account for the non-linearity of the carbon footprint convergence or divergence process over time and individual heterogeneity across countries and sectors (data pre-filtering, carbon footprint convergence testing, and club clustering). Our results demonstrate a significant disparity in carbon footprints across various sectors and countries, especially among the top 1 % of earners. The wealthiest individuals worldwide have not converged towards a common trajectory, indicating high levels of carbon footprint inequality. This investigation assumes that the carbon footprint convergence or divergence process is not linear over time, allowing for fluctuations in carbon emissions inequality. Future research may explore the factors contributing to this non-linearity and its implications for energy justice. Our findings highlight global cooperation's importance in promoting sustainable production practices and a fair distribution of energy-related responsibilities. Energy production and consumption burdens are not equitably distributed, posing a significant challenge to achieving energy justice. This study provides a comprehensive understanding of the dynamics of carbon emissions inequality and its impact on energy justice. It employs a unique methodology and a multidimensional database, providing new insights into the carbon footprint disparity across sectors and countries.

Carbon emission inequality and fairness from energy consumption by prefecture-level cities in China

This paper focuses on the conceptualization and quantification of carbon emission inequality and fairness from energy consumption. In order to more accurately measure the carbon emissions generated by electricity consumption in each city, we firstly propose a new method for calculating the carbon emission factor for electricity, and calculates the carbon emissions from energy consumption in 282 prefecture-level cities in China from 2003 to 2019. Through the application of the Theil-Kaya decomposition mechanism and the improved Atkinson index, we conducted an in-depth study of the carbon emission inequality and fairness indicators from energy consumption. The results show that (1) Although China's overall inequality has declined, it remains significant in the western region, with its inequality indicator fluctuating from 0.548 in 2003 to 0.683 in 2019.(2) The decomposition of the drivers of inequality indicators shows that the contribution of GDP per capita to inequality is increasingly being replaced by energy intensity and the energy carbon emission factor, with energy intensity emerging as the main driver, contributing more than 40% to inequality in 2019, both overall and in the three regions.(3) The results for the fairness indicator, on the other hand, show a certain degree of divergence. Further Dynamic Time Warping fitting analysis shows that regardless of how the public's sensitivity to carbon emissions varies, the change trends of the fairness and inequality indicators for carbon emissions in the eastern region show a high degree of convergence, even in the two most extreme cases. The fit is poorest in the western region, but improves significantly if public's sensitivity to carbon emissions increases. (4)To sum up, some policies that are consistent with the context of the times, such as the East-West regional counterparts and the construction of a new type of power system, are worthy of priority consideration by the Government.

Globalisation and carbon dioxide emissions inequality in OECD countries

AbstractEconomic growth has been crucial in contributing to carbon dioxide (CO2) emissions from the Industrial Revolution, and it affects CO2 emissions heterogeneously with different income levels. Therefore, studying the role of economic growth on inequality in carbon emissions is imperative. This paper analyses the determinants of CO2 emissions inequality in the panel dataset of 37 Organisation for Economic Co‐operation and Development (OECD) countries from 1990 to 2019. Age dependency, globalisation, and institutional quality reduce CO2 inequality in the OECD economies. However, gross domestic product per capita increases CO2 inequality. The results are robust to utilise different panel data estimation techniques. This paper provides the first evidence in the literature of determinants of CO2 inequality across the OECD countries. It is suggested that governments in the OECD economies offer a blueprint for a sustainable society of green economic growth. Other potential policy implications are also discussed.

Methane and nitrous oxide emissions from municipal wastewater treatment plants in China: A plant-level and technology-specific study

Wastewater treatment is an important source of greenhouse gases (GHGs). Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants (MWWTPs) in China. A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs. Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases. China's methane (CH4) and nitrous oxide (N2O) emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg, respectively, with the uncertainty range of −30% to 37% and −30% to 26% at 95% confidence interval. We find an emission inequality across cities, with the richest cities emitting two times more CH4 and N2O per capita from municipal wastewater treatment than the poorest cities. The emitted CH4 and N2O are dominated by Anaerobic/Anoxic/Oxic-, Sequencing Batch Reactor-, Oxidation Ditch-, and Anoxic/Oxic-based MWWTPs of less than 20 years old. Considering the relatively young age structure of China's MWWTPs, the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management. The emission differences among our estimates, previous studies, and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors, implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.

The impact of geopolitical risk on CO2 emissions inequality: Evidence from 38 developed and developing economies

This paper analyses the impact of geopolitical risk on carbon dioxide (CO2) emissions inequality in the panel dataset of 38 developed and developing economies from 1990 to 2019. At this juncture, the empirical models control for the effects of globalisation, capital-labour ratio, and per capita income on CO2 emissions inequality. The panel cointegration tests show a significant long-run relationship among the related variables in the empirical models. The panel data regression estimations indicate that geopolitical risk, capital-labour ratio, and per capita income increase CO2 emissions inequality. However, globalisation negatively affects CO2 emissions inequality in the panel dataset of 38 developed and developing countries. The pairwise panel heterogeneous causality test results align with these benchmark results and indicate no reverse causality issue. Potential policy implications are also discussed.

Carbon Emissions in the U.S.: Factor Decomposition and Cross-State Inequality Dynamics

This paper examines the determinants of inequality in the distribution of CO2 emissions across U.S. regions. We implement a factorial decomposition of CO2 per capita based on extended Kaya factors, that is, carbon intensity of fossil fuel consumption, energy mix, energy intensity of GDP, economic growth in terms of labor productivity and employment rate. Results reveal that U.S. states display marked differences in most factors. We identify energy intensity as the main source of emissions inequality. Based on the within and between group inequality components we also explore the effect of geographical, geological, climatic and human development partitions of U.S. states’ groups. Findings indicate that the within-group inequality had been the main contributor to the whole inequality. Finally, some economic policy implications are also discussed; explaining the unequal distribution of emissions is vital to establish differentiated targets and work towards successful mitigation proposals.

Income-based U.S. household carbon footprints (1990–2019) offer new insights on emissions inequality and climate finance

Current policies to reduce greenhouse gas (GHG) emissions and increase adaptation and mitigation funding are insufficient to limit global temperature rise to 1.5°C. It is clear that further action is needed to avoid the worst impacts of climate change and achieve a just climate future. Here, we offer a new perspective on emissions responsibility and climate finance by conducting an environmentally extended input output analysis that links 30 years (1990–2019) of United States (U.S.) household-level income data to the emissions generated in creating that income. To do this we draw on over 2.8 billion inter-sectoral transfers from the Eora MRIO database to calculate both supplier- and producer-based GHG emissions intensities and connect these with detailed income and demographic data for over 5 million U.S. individuals in the IPUMS Current Population Survey. We find significant and growing emissions inequality that cuts across economic and racial lines. In 2019, fully 40% of total U.S. emissions were associated with income flows to the highest earning 10% of households. Among the highest earning 1% of households (whose income is linked to 15–17% of national emissions) investment holdings account for 38–43% of their emissions. Even when allowing for a considerable range of investment strategies, passive income accruing to this group is a major factor shaping the U.S. emissions distribution. Results suggest an alternative income or shareholder-based carbon tax, focused on investments, may have equity advantages over traditional consumer-facing cap-and-trade or carbon tax options and be a useful policy tool to encourage decarbonization while raising revenue for climate finance.

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.