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This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

Abstract Although the “resource curse” hypothesis has been supported by many empirical studies focusing on the transnational and regional levels, there has always been a point of contention about the proper method of estimating and selecting natural resource indicators in literature. This paper proposes a mixed estimation method for panel data of 10 typical oil and gas resource-based cities in China from 1998 to 2015. The results show that resource industry agglomeration can mirror the distribution and dependence on the resource industry by location rather than by merely measuring the influence of the relative scale of resource extraction on economic growth. Using resource industry agglomeration as the main explanatory variable for regional economic growth verifies the resource curse hypothesis and shows the nonlinear characteristics of the negative correlation between resources and economic growth. Despite mostly similar indicator parameter estimates, marked differences exist in measured effects for material capital investments and technological innovation investments. The result of using resource industry agglomeration as the main explanatory variable is basically consistent with the economic theory and is more in line with observed reality than the alternative indicator. The research conclusions can provide evidence and data for index selection in the studies on the mediating effect of resource curse transmission and international comparison.

In the context of globalisation, is a country’s level of development an obstacle to its environmental performance? The main objective of this research is to identify the role played in the environmental performance of countries with different levels of development, globalisation, and environmental regulation, by the three dimensions and two new measures of globalisation, de jure and de facto. This analysis was accomplished by assessing the environmental curve which relates economic growth to environmental degradation, known as the environmental Kuznets curve, for a sample of 32 developed and 26 developing economies from 1995 to 2017. It was found that developed countries produced an inverted U-shaped curve and that globalisation had a mostly beneficial effect on the environment. In contrast, developing economies produced a U-shaped curve and globalisation was generally harmful. Globalisation caused reductions of 0.88% and 0.85% in the environmental degradation of developed countries, and increases of 0.20% and 0.52% in developing ones. Political globalisation produced different effects for each measure in developed countries and had no effect in developing countries. Economic globalisation suggests the relocation of polluting industries from developed to developing countries. As there is currently very little literature on the new measures of globalisation, this study provides fresh insights for policymakers devising appropriate measures to achieve sustainability in both developed and developing countries.

Achieving carbon-neutrality has become a global agenda following the ratification of the Paris Agreement. For the developing countries, in particular, attaining a low-carbon economy is particularly important since these economies are predominantly fossil-fuel dependent, to which Bangladesh is no exception. Therefore, this study specifically aimed at evaluating the environmental impacts associated with energy consumption and other key macroeconomic variables in the context of Bangladesh over the 1975-2016 period. As opposed to the conventional practice of using carbon dioxide emissions to proxy environmental quality, this study makes a novel attempt to use the carbon footprints to measure environmental welfare in Bangldesh. The outcomes from this study are expected to facilitate the carbon-neutrality objective of Bangladesh and, therefore, enable the nation to comply with its commitments concerning the attainment of the targets enlisted under the Paris Agreement and the United Nations Sustainable Development Goals declarations. The econometric analysis involved the application of methods that are suitable for handling the structural break issues in the data. The overall findings from empirical exercises reveal that aggregate energy consumption, fossil fuel consumption, and natural gas consumption boost the carbon footprint figures of Bangladesh. In contrast, nonfossil fuel consumption and hydroelectricity consumption are witnessed to abate the carbon footprint levels. Besides, economic growth and international trade are also evidenced to further increase the carbon footprints. Hence, these findings suggest that a clean energy transition within the Bangladesh economy can be the panacea to the nation's persitently aggravating environmental hardships. Furthermore, the causality analysis confirmed the presence of unidirectional causalities stemming from total energy consumption, fossil fuel consumption, natural gas consumption, hydroelectricity consumption, economic growth, and international trade to the carbon footprints. On the other hand, nonfossil fuel consumption is found to be bidirectionally associated with carbon footprints. In line with these aforementioned findings, several key policy suggestions are put forward regarding the facilitation of the carbon-neutrality agenda in Bangladesh.

There are substantial differences in carbon footprints across households. This study applied an environmentally extended multiregional input–output approach to estimate household carbon footprints for 12 different income groups of China’s 30 regions. Subsequently, carbon footprint Gini coefficients were calculated to measure carbon inequality for households across provinces. We found that the top 5% of income earners were responsible for 17% of the national household carbon footprint in 2012, while the bottom half of income earners caused only 25%. Carbon inequality declined with economic growth in China across space and time in two ways: first, carbon footprints showed greater convergence in the wealthier coastal regions than in the poorer inland regions; second, China’s national carbon footprint Gini coefficients declined from 0.44 in 2007 to 0.37 in 2012. We argue that economic growth not only increases income levels but also contributes to an overall reduction in carbon inequality in China.

The COVID-19 pandemic affects all of society and hinders day-to-day activities from a straightforward perspective. The pandemic has an influential impact on almost everything and the characteristics of the pandemic remain unclear. This ultimately leads to ineffective strategic planning to manage the pandemic. This study aims to elucidate the typical pandemic characteristics in line with various temporal phases and its associated measures that proved effective in controlling the pandemic. Besides, an insight into diverse country's approaches towards pandemic and their consequences is provided in brief. Understanding the role of technologies in supporting humanity gives new perspectives to effectively manage the pandemic. Such role of technologies is expressed from the viewpoint of seamless connectivity, rapid communication, mobility, technological influence in healthcare, digitalization influence, surveillance and security, Artificial Intelligence (AI), and Internet of Things (IoT). Furthermore, some insightful scenarios are framed where the full-fledged implementation of technologies is assumed, and the reflected pandemic impacts in such scenarios are analyzed. The framed scenarios revolve around the digitalized energy sector, an enhanced supply chain system with effective customer-retailer relationships to support the city during the pandemic scenario, and an advanced tracking system for containing virus spread. The study is further extended to frame revitalization strategies to highlight the expertise where significant attention needs to be provided in the post-pandemic period as well as to nurture sustainable development. Finally, the current pandemic scenario is analyzed in terms of occurred changes and is mapped into SWOT factors. Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution based Multi-Criteria Decision Analysis, these SWOT factors are analyzed to determine where prioritized efforts are needed to focus so as to traverse towards sustainable cities. The results indicate that the enhanced crisis management ability and situational need to restructure the economic model emerges to be the most-significant SWOT factor that can ultimately support humanity for making the cities sustainable.

This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO2 emissions over the period 1990-2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved.

Research on the nexus between energy consumption and economic growth is a fundamental topic for energy policy making and low-carbon economic development. Russia proves the third largest energy consumption country in the world in recent years, while little research has shed light upon its energy consumption issue till now, especially its energy–growth nexus. Therefore, this paper empirically investigates the dynamic nexus of the two variables in Russia based on the state space model. The results indicate that, first of all, Russia's energy consumption is cointegrated with its economic growth in a time-varying way though they do not have static or average cointegration relationship. Hence it is unsuitable to merely portrait the nexus in an average manner. Second, ever since the year of 2000, Russia's energy efficiency has achieved much more promotion compared with that in previous decades, mainly due to the industrial structure adjustment and technology progress. Third, among BRIC countries, the consistency of Russia's energy consumption and economic growth appears the worst, which suggests the complexity of energy–growth nexus in Russia. Finally, there exists bi-directional causality between Russia's energy consumption and economic growth, though their quantitative proportional relation does not have solid foundation according to the cointegration theory.