Inequality In Emissions Research Articles

Is global carbon inequality getting better or worse? A decomposition analysis of carbon inequality in intraincome and interincome groups

PurposeThis 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.Design/methodology/approachThe 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.FindingsThis 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.Practical implicationsTo 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.Originality/valueIn 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 inequality of China's regional residential CO2 emissions

Driven by continuous income increases and the urgent need to improve living conditions, CO 2 emissions generated from residential energy consumption have gradually become the main source of China's CO 2 emissions growth. Because of both natural and social factors, China has significant CO 2 emission inequalities, however, there is few literature on residential carbon inequality and its driving factors. Using the provincial panel data of Chinese residential sector from 2005 to 2017, this article examines residential CO 2 emission inequality (carbon inequality) and its driving factors from a static and dynamic perspective to provide empirical support for the formulation of emission reduction policies and the allocation of regional emission reduction quotas. The results indicate that residential carbon inequality grew from 2005 to 2017. The energy intensity disparity was the main contributor in promoting carbon inequality increases, and its effects demonstrated an increasing trend. Per capita income disparity was the second largest factor in the growth of residential carbon inequality, with a contribution of approximately 20%. Additionally, the urban and rural structure also positively widened carbon inequality, but its contribution decreased. Conversely, the energy structure disparity actively facilitated a reduction of carbon inequality, although such active effects were minor. Based on these results, policies relevant narrowing the regional gaps of energy intensity, per capita income, and urbanization were proposed for decreasing carbon inequality of China's residential sector.

The regional disparity of per-capita CO2 emissions in China’s building sector: An analysis of macroeconomic drivers and policy implications

There are significant regional differences in CO2 emissions in China’s building sector. Analyzing and understanding this geographic inequality and its drivers is crucial for balanced regional development and greenhouse gas (GHG) emissions reduction. In this paper, we estimated the CO2 emissions of China’s building sector at the provincial level and then calculated the Theil Index of per-capita CO2 emissions generated from different building types. Based on these results, a Kaya identity was applied to analyze the drivers of the inequality in CO2 emissions across China. We found that the inequality index of the different types of buildings makes a significant difference. In general, the Theil Index for public buildings and urban buildings is higher than that for rural buildings. Income, energy intensity and energy mix are the principal drivers of regional disparity of per-capita emissions. Economic growth helps to narrow regional disparities for residential buildings, but its contribution is not significant for public buildings. For all building types, energy intensity is the primary contributor to emissions inequality, and the imbalanced implementation of energy efficiency policies is a leading factor. Energy mix plays an increasing role in the regional disparities of per-capita CO2 emissions, especially for rural buildings. Reducing these regional disparities is crucial to China’s goal of achieving peak GHG emissions and reaching carbon neutrality. This paper highlights the importance of per-capita CO2 emissions in formulating carbon peak planning, allocating regional emissions reduction targets, formulating building energy policies and allocating low-carbon resources.

The factors of regional PM2.5 emissions inequality in China

Since the reform and opening up, China's economy has developed rapidly, which has also caused environmental problems such as industrial emissions. PM2.5 (particulate matter with a diameter of less than 2.5 microns) emissions seriously threaten people's health. Therefore, it is necessary to study the emission reduction of PM2.5. This study combines the Data Envelopment Analysis (DEA) and Logarithmic Mean Divisia Index (LMDI) methods to originally construct the inequality indicator and explore the influence of different factors on the inequality of per capita PM2.5 from the regional aspect. This study decomposes the “emission efficiency” of per capita PM2.5 emissions into more important effects. It reveals that, in East China, the energy-oriented technology gap (ETG) had the strong reducing effect on the national per capita PM2.5 emissions; the energy-oriented technology efficiency (ETE) and economic development level (EDL) had the strong promoting effect. In Central China, the potential emission intensity (PEI) has the strong reducing effect on the national per capita PM2.5 emissions, followed by the EDL; the ETG and energy-biased technology (EBT) effect had the strong promoting effect. In West China, the ETE had the strong reducing effect on the national per capita PM2.5, followed by the PEI; the ETG had the strong promoting effect, followed by the EBT and output-oriented technology gap (YTG). The ETE had the greatest improving effect on the inequality indicator, and the PEI and EDL had the greatest reducing effect. Policy suggestions are put forward based on regional differences in East China, Central China and West China.

An overview of the inequality in China’s carbon intensity 1997–2016: a Theil index decomposition analysis

Although China has experienced an overall decline in CO2 emissions intensity from 2009 to 2016, the intensity from one province to another varies considerably. As China seeks to reduce CO2 emissions intensity further, understanding how intensity differs provincially and regionally, as well as why, will be important for developing equitable management strategies. The Kaya-Theil model has been extensively applied to analyze the emission inequality; however, there have been no studies focusing on the inequality in carbon intensity in the different sectors and from different resource types in China. Here, we develop a comprehensive analysis on the inequality in China’s carbon intensity from both sectoral and energy perspectives from 1997 to 2016. The Theil index is decomposed into the within-region inequality and between-region inequality based on four economic development strategies. We used the LMDI decomposition analysis to identify the driving factors of the inequality (GDP share, emission coefficients, energy structure, energy intensity and economic structure). We find that after a decline in the inequality from 2003 to 2009, the inequality in the total carbon intensity increased by 28.4% from 2009 to 2016, mainly from an increase in the inequality from the industry sector (+ 53.1%), construction sector (+ 47.6%) and coal (+ 40.6%). The within-region inequality was the main source of the inequality in the carbon intensity, accounting for more than 60% of the inequality of the total carbon intensity from 2009 to 2016. Further decomposition identified the energy intensity disparity as the key driving factor of the carbon intensity inequality, inducing a 26.5% increase of the inequality from 2009 to 2016. Moreover, our results demonstrate how the structural transformation of energy and economic structure impact the inequality in carbon intensity.

Who emits CO2? Landscape of ecological inequalities in France from a critical perspective

This article provides a panorama of greenhouse gas (GHG) emission inequalities between French households. It presents in a detailed and critical manner the methodological conventions that are used to compute “household emissions”, including the related assumptions. The most common responsibility principle, the “consumer responsibility”, assigns to households the emissions of the products that they consume, resulting in the carbon footprint. It focuses attention on the contributions of individuals, on their choices, and it may obscure the role of non-individual actors and also the collective component of GHG emissions, and it neglects the dimensions of responsibility that are not related to consumption choices. We estimate the distribution of household carbon footprints based on data from the 2011 French Household Budget Survey. Household emissions tend to increase with income, but they also show a strong variability linked to geographical and technical factors that force the consumer to use fossil fuels. Based on sectoral surveys (ENTD 2008; PHEBUS 2013), we also reconstruct household CO2 emissions linked to housing and transport energy. For transport, emissions are proportional to the distance travelled due to the predominant use of private cars. Urban settlement patterns constrain both the length of daily commuting and access to less carbon-intensive modes of transport. For housing, while the size of the dwelling increases with income and distance from urban centres, the first factor to account for variability of emissions is the heating system: this has little to do with income but more to do with settlement patterns, which constrain access to the various energy carriers. Finally, we discuss the difficulties, both technical and conceptual, that are involved in estimating emissions from the super-rich (the top 1 percent).

CO2 emissions inequality through the lens of developing countries

There is increasing interest in CO2 emissions inequality between and within countries, and concerns about the impacts of COVID-19 on vulnerable groups. In this study, the CO2 emissions inequality based on the different consumption category data of disaggregated income groups in eight developing countries is analyzed with the application of input-output model. We further examine the effects of the COVID-19 outbreak on CO2 emissions inequality based on the hypothetical extraction method, and the results reveal that the outbreak has decreased the CO2 emissions inequality and emissions over time. However, the shared socioeconomic pathway scenario simulation results indicate that long-term CO2 emissions inequality will persist. Targeted poverty elimination measures improve the utility of the low- and lowest-income groups and reduce CO2 emissions inequality. Reducing the excessive consumption on the demand side as well as improving the energy efficiency and increasing the share of renewable energy in the energy consumption on the supply side will provide more informed options to achieve multiple desirable outcomes, such as poverty elimination and climate change mitigation.

Multi-sectoral determinants of carbon emission inequality in Chinese clustering cities

Based on the data of 285 prefecture-level cities, hierarchical cluster analysis and a decomposition approach using the Gini coefficient were used to explore multi-sectoral determinants of the carbon emission inequality in Chinese clustering cities. The results indicate that the emission disparity of the industrial consumption sector is the main source of emission inequalities in clustering city groups. Compared with the base period, the emission inequality of each clustering city group decreased in the reporting period, which was mainly attributed to changes in emissions per capita, whereas an impact of population mobility on emission inequality was not detected. Our results have important implications for Chinese city governments that are to adopt differentiated emission reduction policies.

Driving factors of CO2 emission inequality in China: The role of government expenditure

China has reached a consensus regarding the total control of carbon dioxide (CO2) emissions; however, regional emission inequalities still exist. The reduction of carbon emissions is a public good and indicates a strong positive externality, which is difficult to solve within the market. Such reductions are highly dependent on governmental contributions. Therefore, using the Theil index and the logarithmic mean Divisia index decomposition approach, this paper integrates government expenditure into an analysis framework, investigating the driving factors of emission inequality and the status and changes of China's CO2 emission inequality from 2007 to 2015, attributing emission inequality to disparities in governmental expenditures, energy consumption, and other socioeconomic factors. The empirical results show that imbalances in economic development, population distribution, and energy structure were prerequisites for a regional emission inequality, while disparities in government expenditure also played an important role. Among these factors, disparities in the expenditure structure were the main cause for emission inequality. The findings of this paper provide guidelines for the government to set carbon emission reduction quota and implement reasonable differentiated emission reduction policies.

Carbon footprint, municipality size and rurality in Spain: Inequality and carbon taxation

By using an environmentally extended multi-regional input-output model, this paper analyses the Spanish households’ carbon footprint for the 2008–2017 period considering the municipality size as well as the urban or rural residential zone where families live. Results show that, on a per capita basis, inhabitants of medium-large municipalities emit fewer carbon emissions than those settled in small ones (between 0.34 and 0.54 tCO2/cap depending on the year studied). This carbon unbalance is mainly explained by the higher direct carbon footprints of dwellers who reside in small municipalities and, in special, in rural zones. Furthermore, applying inequality measures through a consumption-based carbon footprint Gini coefficient, we show that both income and CO2 emissions inequality are lower in small municipalities. In the light of the findings, in Spain, the application of a carbon pricing on direct and indirect carbon footprints will be regressive, disproportionally affecting people of small municipalities and rural areas. Accordingly, household carbon inequalities must be contemplated to avoid poorly designed climate change mitigation policies.

Historical evolution of global inequality in carbon emissions and footprints versus redistributive scenarios

Ambitious scenarios of carbon emission redistribution for mitigating climate change in line with the Paris Agreement and reaching the sustainable development goal of eradicating poverty have been proposed recently. They imply a strong reduction in carbon footprint inequality by 2030 that effectively halves the Gini coefficient to about 0.25. This paper examines feasibility of these scenarios by analyzing the historical evolution of both weighted international inequality in CO2 emissions attributed territorially and global inequality in carbon footprints attributed to end consumers. For the latter, a new dataset is constructed that is more comprehensive than existing ones, and footprints are found to be more unequal than territorial emissions. In both cases, we find a decreasing trend in global inequality, partially attributed to the move of China from the lower to the middle part of the distributio. Still, realization of the redistributive scenarios would require an unprecedented reduction in global inequality far below historical levels. Moreover, the territorial emissions data, available for more recent years up to 2017, show a saturation of the decreasing Gini coefficient at a level of 0.5. This observation confirms an earlier prediction based on maximal entropy reasoning that the Lorenz curve converges to the exponential distribution. This saturation further undermines feasibility of the redistributive scenarios, which are also hindered by structural tendencies that reinforce carbon footprint inequality under global capitalism. One way out of this conundrum is a fast decarbonization of the global energy supply in order to decrease global carbon emissions without relying crucially on carbon inequality reduction.

Focus on the provincial inequalities in energy consumption and CO2 emissions of Iran's agriculture sector.

Analyzing and understanding the driving factors behind CO2 emissions is noticeable due to increasing the awareness about CO2 emissions, and it is a highlight in Iran's agriculture sector because of the increasing amount of CO2 emissions, inefficient government policies, and rising fossil energy consumption in last decade. By considering the regional differences to investigate this aim, the Theil index and Kaya factor used to analysis the provincial inequality in CO2 emissions, energy consumption, and identify the driving factor. Using the Theil approach helps us to find out the inequality trend in CO2 emissions and energy consumption and also inequality across different provinces. In that way, the Kaya identity applied to analyze the factor behind the inequality in CO2 emissions. The empirical result shows some points, primary, according to the criteria and weights in the grouping methodologies, the GDP, due to the lower level of contribution in within-group inequality, is better than the population. Further, by assessing the inequality in the consumption of different forms of energy and CO2emissions across the provinces, most of the inequality was related to within-group, and the Theil trends are decreasing in gas and electricity; this trend is unclear and fluctuated in petroleum products and increase in CO2 emissions. Secondly, the first and second phases of subsidizing targeting have reduced the consumption and inequality of petroleum products and CO2emissions in the short term. Still, the inequality in CO2 emissions continues to increase recently. Thirdly, the national inequality in CO2emission mainly attributed to energy factors across provinces, and an increase in the energy inequalities helps to explain the CO2 inequality increase.

Exploring carbon emissions and international inequality in a globalized world: A multiregional-multisectoral perspective

The phenomenon of economic convergence has been investigated from different perspectives, aiming to analyze whether economies move towards a common growth path or tend to diverge over time, and the consequences of this for economic cohesion. However, these consequences for the evolution of CO2 emissions in the study of global convergence of CO2 emissions, and the implications in terms of pollution, inequality, and income-dependence have received less attention in the literature of convergence. The increasing globalization of economies and the rising fragmentation of supply chains imply many countries involved in the production chains and, in consequence, a vision is needed of worldwide emissions associated with these processes. In this paper, we use the multisectoral and multiregional perspective provided by a multiregional input-output model (MRIO), and the associated databases, to analyze the evolution of inequality in CO2 emissions, paying attention to the roles played by regional specificities and/or productive structures. MRIO models and indicators presented, provide the basis to assess to what extent countries and/or sectors are walking towards a common path or, on the contrary, tend to be more unequal over time. Given the role that structure, final demands and international trade play in these models, we can offer a novel structural view of the convergence issue. Moreover, MRIO models also allow analyzing this question combining the perspectives of production and consumption, and their relationship through international trade. Moreover, our paper attempts to shed light on the discussion about the global and regional process of generation of emissions, paying special attention to cluster analysis and to the existence of common trends by groups of countries. Empirically, the information provided by the most recent edition of the World Input-Output Database (WIOD) and environmental accounts compatible with this database, is used. In our view, the results contribute new dimensions and insights to the issue of international inequality in terms of environmental pressures and opens new debates on the relocation of environmental damage, comparative advantage, and the environmental footprint.

Unveiling Key Drivers of Indirect Carbon Emissions of Chinese Older Households

The rapid urbanization and growing population aging have become salient features in China. Understanding their impacts on household emissions is crucial for designing mitigation policies for household carbon emissions. By integrating Chinese older household survey data with an unconditional quantile regression model, this paper examines the heterogeneous impacts of household characteristics on indirect carbon emissions of older Chinese households. There are three main findings: (1) The effects of urbanization on emissions at different quantiles of carbon emissions appear to be inverted U-shaped, which means that the rise of urbanization level increases carbon emissions more at the middle than at the bottom or the top, and helps to alleviate carbon emission inequality, (2) though carbon emissions rise with the increase of income, there is a clear urban-rural divide in the effects of income on carbon emissions, and (3) the rise in the share of well-educated people contributes to the increase in carbon emissions. The higher the degree of education is, the larger the impact is. These findings contribute to understanding the determinants of carbon emissions and are helpful for policymakers to design targeted policies in reducing carbon emissions from the consumption-side.

Rising carbon footprint inequality in the Philippines

The literature is abundant with studies analyzing inequality in carbon emissions at the macroeconomic level, but very limited at the household level. The issue of household carbon footprint inequality is relevant in mitigating climate change through curbing household emissions. This study investigates household carbon footprint inequality in the Philippines and decomposes it into consumption sources applying the standard method used in analyzing income inequality. Results show that the richest 20% of the population has an aggregate share of more than 50% in the total household emissions. Between 2000 and 2006, the Gini coefficient of carbon footprint increases from 0.455 to 0.475. This implies that there is a high and worsening carbon footprint disparity among Filipino households. This disparity in emissions is more pronounced among rich and poor households relative to the middle-income households depicting a non-monotonous kind of relationship between household income and carbon emissions. This suggests that variations in lifestyle and consumption preferences determine overall household emissions inequality. In addition, the decomposition analysis suggests that inequality in carbon footprint is mainly driven by energy-intensive consumption such as fuel, light and transportation. At any affluence level, promotion of less carbon-intensive or energy-efficient consumption allows for the reduction of not just the emissions level, but also the disparity in household carbon footprint.

Measurement of air-pollution inequality through a three-perspective accounting model

China is suffering from serious air pollution. Regional air quality varies significantly due to intensive inter-provincial trades, diversified resource endowments and complicated economic structures. This study breaks the limitations of measuring environmental inequality only from a single perspective and establishes a three-perspective atmospheric pollutant equivalents accounting model (or APE accounting model) for air-pollution inequality assessment under environmentally-extend multi-regional input-output framework. From three perspectives of local production (i.e. production-based), final demand (i.e. consumption-based) and primary supply (i.e. income-based), APE emissions, APE transfers and environmental Gini coefficient are investigated to exam emission responsibilities of various impact factors, evaluate the impacts of inter-provincial trades on pollutants transfers, and characterize regional emission inequalities at both provincial and sectoral levels. The results indicate that local emitters are merely parts of contributors to air pollution. Direct emitters like Hebei Province, primary suppliers like Inner Mongolia and final consumers like Shandong Province induce large amounts of air pollutants as embedded within various economic activities. Because of unequal supply-demand levels and complex exchange mechanisms, three-perspective APE emissions are significantly heterogeneous, especially in mining, construction, energy and material-transformation sectors. Particularly, inequality of the mining sector in embodied emissions has the highest environmental Gini coefficient (0.881). This model provides a framework to assess regional environmental inequality and its findings provide scientific bases for the formulation of desired regional air pollution control policies.

Air pollution inequality and health inequality in China: An empirical study.

China's residents experience unequal exposure to air pollution in different regions, and the corresponding health consequences have increased remarkably. To ensure sustainable development, China should monitor health inequality and its potential determinants. This study empirically examines the health inequalities (represented by perinatal and tuberculosis mortalities) caused by air pollution inequalities (represented by SO2 and NOx emissions) from 31 Chinese provinces in the period 2006 to 2015, using the generalized method of moments (GMM) and quantile regression (QR). The GMM results reveal a strong positive relationship between SO2/NOx emission inequality and tuberculosis mortality inequality. In contrast, the QR results show that perinatal mortality inequality is closely related to emission inequality across all percentiles for SO2 emission and at the 75th percentile for NOx emission. Our findings help policymakers to identify health disparities and be mindful of air pollution inequality as a factor in the elimination of health inequality.

What are the implications of the Paris Agreement for inequality?

ABSTRACTClimate change is a major planetary challenge. Its consequences threaten the provision of Earth-system services and sustainable development. The impacts and the capacities to adapt vary across countries and different incomes, as do the historical and current emissions of greenhouse gases (GHGs) and thus the responsibility for anthropogenic climate change. This has generated a complex debate about the inequities inherent in the climate challenge. This paper analyses the potential implications of the full implementation of the first round of Nationally Determined Contributions (NDCs) of the Paris Agreement for countries’ per capita GHG emissions and the related inequality measures of the Gini coefficient and Lorenz curve. The distribution of annual and cumulative GHG emissions per capita for selected years and periods pre- and post-Paris of two NDC scenarios are assessed to derive implications for desired increases in ambition levels. The results show that the NDCs, while not meeting the Paris targets to limit temperature increase if levels of ambition remain the same after 2030, lead towards a more equitable future in terms of GHG emissions.Key policy insightsThe NDCs lead to decreases in GHG emissions inequality (lower Gini coefficients) across countries compared to 1990.The rate of decrease in inequality 2016–2030 slows down compared to 1990–2015.Conditional pledges in the NDCs lead to smaller reductions in GHG emissions inequality than unconditional pledges.This highlights tension between the pursuit of decreasing GHG emissions inequality and the ambition to lower overall global GHG emissions.

Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis

CO2 emission inequality among countries is a key issue in international climate negotiations. In view of the growing popularity of the consumption-based emission accounting system in climate policy studies, analyzing the emission inequality from the consumption perspective can help policymakers design emission abatement scenarios that are fairer to all parties. Using a new approach based on the Theil index and the index decomposition analysis (IDA) technique, this paper examines global per capita consumption-based emission inequality in 1995–2009. The sources and determinants of both the status and evolution of the emission inequality are quantified. The empirical results show that the global emission inequality was sourced mainly from the emerging economies, particularly China and India. The global inequality decreased at an accelerating rate during the period studied. The narrowing disparity among countries in per capita consumption level drove, while the expanding disparity in consumption-based emission intensity largely hindered, the inequality reduction. Comparing the consumption-based emission inequality with that under the production-based principle reveals that the latter partly masked the inequality in the distribution of global CO2 emissions through production outsourcing. More detailed results and discussions are presented.

Club convergence and spatial distribution dynamics of carbon intensity in China’s construction industry

Climate change caused by carbon emissions continuously threatens sustainable development. Due to China’s immense territory, there are remarkable regional differences in carbon emissions. The construction industry, which has strong internal industrial differences, further leads to carbon emission disparity in China. Policymakers should consider spatial effects and attempt to eliminate carbon emission inequality to promote the sustainable development of the construction industry and realize emission reduction targets. Based on the classic Markov chain and spatial Markov chain, this paper investigates the club convergence and spatial distribution dynamics of China’s carbon intensity in the construction industry from 2005 to 2014. The results show that the provincial carbon intensity in the construction industry is characterized by “convergence clubs” during the research period, and very low-level and very high-level convergence clubs have strong stability. Moreover, the carbon intensity class transitions of provinces tend to be consistent with that of their neighbors. Furthermore, the transition of carbon intensity types is highly influenced by their regional backgrounds. The provinces with high carbon emissions have a negative influence on their neighbors, whereas the provinces with low carbon emissions have a positive influence. These analyses provide a spatial interpretation to the “club convergence” of carbon intensity.