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This study is aimed at better understanding the evolution of inequality in carbon emission in intraincome and interincome groups in the world, and then to uncover the driving factors that affect inequality in carbon emission.

The approach is developed by combining the Theil index and the decomposition technique. Specifically, the Theil index is used to measure the inequality in carbon emissions from the perspective of global and each income group level. The extended logarithmic mean Divisia index was developed to explore the driving factors.

This study finds that the inequality in carbon emissions of intraincome group is getting better, whereas the inequality in carbon emission of interincome group is getting worse. And the difference in global carbon emissions between income groups is the main source of global carbon emission inequality, which is greater than that within each income group. In addition, the high-income group has transferred their carbon emissions to upper-middle income group by importing high-carbon-intensive products to meet the domestic demand, while lower-middle-income group do not fully participate in the international trade.

To alleviate the global carbon inequality, more attention should be paid to the inequality in carbon emission of interincome group, especially the trade between high-income group and upper-middle income group. From the perspective of driving factors, the impact of import and export trade dependence on the per capita carbon emissions of different income groups can almost offset each other, so the trade surplus effect should be the focus of each group.

In order to consider the impact of international trade, this study conducts a comprehensive analysis of global carbon emissions inequality from the perspective of income levels and introduces the import and export dependence effect and the trade surplus effect into the analysis framework of global carbon emission inequality drivers, which has not been any research carried out so far. The results of this paper not only provide policy recommendations for mitigating global carbon emissions but also provide a new research perspective for subsequent inequality research.

The purpose of this study is to analyze and empirically test the impact of Economic Freedom [(EF) measured by size of the government] and inequality on environmental pollutants in addition to macroeconomic variables like per capita GDP, governance indicators, etc. along with existence of non-linear (Kuznets) postulation between economic growth and per capita emissions.

The paper examines the select Asian nations' data attributes, first qualitatively using correlation data technique, followed by empirical testing using differenced Generalized Methods of Moments (GMM). Using the data of selected Asian countries for the period from 1981 to 2016, the authors have applied a dynamic panel technique.

The key findings that emerge from the study are as follows: first, there is weak evidence for the existence of the Kuznets curve based on the empirical results; second, the results indicate that increased EF (by lower government size) could enable to contain carbon emissions; third, there is a negative relationship between democracy and environmental quality (corroborating to the existing studies on carbon emissions); and fourth, there is a strong statistical evidence that increasing income inequality pairs with greater emissions in the middle range of Gini.

The paper conforms to the universally held conviction that government interventions are essentially less productive and the desirability of a reduced size of the government in realizing sustainable green growth with equity.

In an era of liberalization and privatization, it is argued that the role of the government needs to be redefined if not necessarily truncated.

The current paper incorporates Gini (inequality measure) through its intercountry range dummies to study the differential effect of Gini on carbon emissions. Also, in some of the recent studies, distributional issues have surfaced explicitly in the discussion of income–climatic change relationship, but EF largely remains missing. The purpose of the current study is to investigate the same empirically.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

The purpose of this paper is to quantitatively examine if varying household consumption activities at different income levels drove CO₂ emissions to different degrees in Mexico from 1990 to 2014.

The paper applied a simple expenditure-CO₂ emissions elasticity model – a top-down approach – using data from consumption-based CO₂ emission inventories and the “Household Income and Expenditure Survey” and assuming a range of 0.7-1.0 elasticity values.

The paper results show a large carbon inequality among income groups in Mexico throughout the period. The household consumption patterns at the highest income levels are related to significantly more total CO₂ emissions (direct + indirect) than the household consumption patterns at the lowest income levels, in absolute terms, per household and per capita. In 2014, for example, the poorest household decile emitted 1.6 tCO₂ per capita on average, while the wealthiest decile reached 8.6 tCO₂ per capita.

The results suggest that it is necessary to rethink the effect of consumption patterns on climate change and the allocation of mitigation responsibilities, thus opening up complementary options for designing mitigation strategies and policies.

The paper represents an alternative approach for studying CO₂ emissions responsibility in Mexico from the demand side, which has been practically absent in previous studies. The paper thereby opens a way for studying and discussing climate change in terms of consumption and equity in the country.

This paper builds on the findings of Bridge (2021) and attempts to understand the major ethical, equity, and leadership issues that may arise when governments plan massive infrastructure and amelioration programs such as the United States’ Green New Deal (GND). The methodology developed here could be applied to the plans being created in other developed countries such as Canada and Korea.

A qualitative approach was used to analyse the ethical issues associated with the Green New Deal via semi-structured interviews with 34 published authors of academic articles dealing with the ethics of climate change. Two industry experts were also consulted for reference.

This paper identifies three key themes arising from the proposed implementation of the Green New Deal. Firstly, the GND has the potential to present equity, justice, and ethical issues that must be considered as part of any intended adoption. Secondly, the GND will present opportunities for economic and climate success, but some groups may suffer due to its implementation. Thirdly, those that have the capacity, wealth, leadership, and ability should lead climate change initiatives. This may require market solutions in the short-term to reach 2050 net zero targets.

This paper is the first qualitative study undertaken on the Green New Deal, contributing to the development of the scant literature on this topic and also informing the practical implementation of wholesale infrastructure plans.

The purpose of this study is to examine how renewable energy consumption moderates the relationship between inequality and carbon dioxide (CO₂) emissions for Brazil, Russia, India, China and South Africa (BRICS). The nexus between energy use and geopolitical tensions has also been explored.

This study has used distinctive data sets from 1990 to 2018 to explore the interconnections on emission, energy use, inequality and geopolitics. To do away with the difficulties related to heterogeneity and cross-sectional dependence (CD), this paper uses recent estimation methods that are robust to panel heterogeneity and CD.

The results of the panel augmented mean group (AMG) estimation and common correlated effects mean group (CCEMG) estimation verify the environmental Kuznets curve. The findings show that a 1% rise in Gini inequality leads to a 0.24% rise in the CO₂ emission (AMG) method and a 0.17% rise in emissions CCEMG (method). As far as the moderating impact of renewable energy upon Gini measure of inequality is concerned, it is −0.10 AMG and CCEMG methods of estimation, respectively. However, the moderating impact of renewable energy on the geopolitical index leads to a mitigating impact on CO₂ emissions, 0.55% decline in AMG method.

This research makes a distinctive contribution by investigating for the first time to the best of the authors’ knowledge the main pillars of sustainable ecological development in the context of the BRICS nations.

The purpose of this examine the impact of income inequality and shadow economy on environmental degradation given the growing income inequality, shadow economy and ecological degradation in developing countries. Thus, this study is motivated to offer empirical insight into how income inequality and shadow economy influence the environment in African countries.

Data from 29 countries in Africa between 2000 and 2017 were used, while the novel method of moments quantile regression of Machado and Silva (2019) and Dumitrescu and Hurlin (D-H) (2012) granger causality is used as the estimation techniques.

The results established the presence of cross-sectional dependence and slope heterogeneity in the panel, while Westerlund panel cointegration confirmed the long-run cointegration among the variables. The results from the quantile regression suggest that income inequality increases environmental degradation from the 5th to the 30th quantiles, while from the 70th quantiles, income inequality reduces ecological degradation. The shadow economy negatively influences environmental degradation across the quantiles, strengthening environmental quality. Per capita income (economic growth) and financial development positively impact environmental degradation throughout the quantiles. However, urbanization reduces environmental degradation from 60th to 95th quantiles. The D-H causality established a two-way relationship between income inequality and environmental degradation, while one-way from shadow economy, per capita income and urbanization to environmental degradation were established.

This study provides fresh insights into the nexus between shadow economy and environmental quality in the presence of higher levels of income inequality for the case of African region. The study applies quantile analysis via moment proposed by Machado and Silva (2019). This technique shows that the impact of income inequality and shadow economy on environmental degradation is heterogeneous across the quantiles of ecological footprints in Africa.