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This study evaluates the impacts of renewable energy, environmental taxes, environmental technology, and financial development on carbon emissions in OECD economies from 1995 to 2015 by employing system-GMM and quantile regression approaches. Our empirical analysis indicates that environmental tax negatively affects carbon emissions; economic growth impedes environmental quality by increasing carbon emissions. Further, renewable energy consumption, environmental technology, and financial development improve environmental quality by decreasing carbon emissions. We suggest that changes in policymaking to promote sustainable economic growth and environmental quality should be prevent environmental degradation, but also inspire greater investments in new technologies and energy expertise in the renewables industry.

This paper examines whether the 1997 Asian financial crisis affected the renewable energy/carbon dioxide (CO2) emissions relationship differently when compared to the 2008 global financial crises. Using the Dynamic Panel Data Model, we examine separately the impact of the 1997 crisis and the 2008 crises on the stated relationship for annual data between the 1987-2018 period for a group of high, upper-middle, and lower middle-income countries. Our findings suggest that the results were crisis and country specific. For the overall sample, the relationship between the two variables was positive (and significant post-1997 and pre-2008 crises) but negative post-2008 crisis. In contrast, the positive relationship remained unchanged for the lower middle-income subsample through the two crises. We also find evidence that the 1997 Asian crisis altered the relationship differently than the 2008 financial crisis especially for the upper and middle-income groups. Clearly, reduction of CO2 emissions may not be guaranteed even if host countries adopt renewable energy sources since country income levels and the nature of the crisis may matter. Future research may consider how the degree of pollution controls and differential costs of renewable energy adoption in countries may alter this relationship.

Abstract Ensuring household access to affordable, reliable, sustainable and modern energy for all the people is one of the 17 United Nations Sustainable Development Goals (SDGs). China has achieved 100% electricity access, while the traditional solid fuels such as firewood are still widely used in its rural area. This paper, using a long-term and large micro dataset and multinomial logit model, investigates quantitatively the determinants of cooking fuel choice in rural China. The results show that in addition to the previous knowledge on household income, occupation is crucial to the cooking fuel transition. In average, if the head of household changes its occupation from farm to non-farm, the possibility of using firewood would reduce by around 14–21%. The impact of income is slightly small. A 10% increase in income may result in 0.5% of possibility of firewood use. These conclusions are robust after considering the possible energy ladders using ordered logit regressions (OLR) and generalized OLR. After controlling other factors such as income and occupation, we have not found concrete evidence on the influences of education and gender of the household head and household member numbers. To accelerate the fuel transition, in addition to increase the household income, the government should pay attention to create more non-farm work opportunities for the rural.

The impacts of renewable energy adoption and environmental sustainability ratings on the validity of the environmental Kuznets curve and the pollution haven hypothesis are examined using annual balanced panel data from 64 middle and low-income countries and spanning the 2005–2014 period. We show that the GDP per capita/CO2 emissions per capita relationship is an inverse S curve for the full sample of low and middle-income countries and for each subsample. The renewable energy/CO2 emissions per capita relationship is an inverse N curve for the full and the middle-income samples, but a V curve for the low-income sample. The foreign direct investment net inflows/CO2 emissions per capita relationship is an N curve for the full and the middle-income samples, and a positive relationship in the low-income subsample. High levels of government environmental sustainability ratings in low-income countries with relatively higher incomes can attract foreign direct investment net inflows while reducing pollution. In contrast, middle-income countries with high environmental sustainability ratings can attract foreign direct investment net inflows only if they allow small increases in pollution.

In recent literature, scholars discussed the role of export diversification in environmental quality. However, most studies analyzed the role of export diversification in influencing carbon dioxide emissions with mixed results. However, since carbon dioxide emissions specifically capture the environmental effects of energy utilization, a change in the level of carbon dioxide emissions cannot be regarded as a comprehensive measure of environmental deterioration. Also, many previous studies use the original form of the Theil index to measure export diversification, and during the interpretation of the results, they disregard the fact that the lower value of the Theil index indicates higher diversification and vice versa. In this context, to address these gaps in the literature, a study on the contribution of export diversification in ecological footprint is necessary to understand the ecological impacts of export diversification. Therefore, this study analyzes the contribution of export diversification in ecological footprint covering the period between 1965 and 2017 using the STIRPAT model in the context of India which is required to fulfill the demands for resources of over 1.3 billion people. The study relied on the environmental Kuznets curve hypothesis framework to understand the role of export diversification in ensuring environmental sustainability. Using the newly developed Augmented ARDL test, the study established that variables of interest are cointegrated. In the long-run estimation, export diversification reduces the ecological footprint of India and helps establish the inverted-U-shaped nexus between ecological footprint and economic growth. Thus, the environmental Kuznets curve hypothesis was evidenced to hold for India. This important finding divulges that India can control the level of environmental footprints, and therefore decrease environmental degradation by continuously increasing export product diversification. Also, India is on the right path to achieve a reduction in ecological footprint associated with more development when accounting for export diversification in the model. Moreover, energy intensity boosts environmental deterioration, while population density reduces it. Finally, the study discusses strategies to achieve environmental sustainability through increasing export diversification.

Abstract The Chinese government aims to mitigate climate change while also reducing local air pollution; this requires co-control of greenhouse gases and pollutants. Here, we develop a method combining an elasticity analysis and a multi-regional input–output model, to measure changes in the emissions of greenhouse gases and pollutants and corresponding socio-economic costs caused by the adjustments in intermediate input, inter-regional trade, and final demand transactions for 30 provinces in China. A filter framework is proposed to identify the key structural transactions that can significantly co-control both emission types with small socio-economic impacts. The results show that 13 effective co-control spots can simultaneously reduce greenhouse gases and pollutants. Among these, eight co-controls are associated with low economic costs, which we refer to as ‘sweet spots’. Sweet spots cover agricultural inputs in the food and tobacco sectors of Inner Mongolia, Sichuan, Liaoning, and Hubei; self-inputs in the agriculture of Henan; self-inputs in the food and tobacco sector of Shandong; fixed capital formation of agriculture in Hebei; and urban household consumption of agricultural products in Guangdong. This finding is important, as climate measures mostly side-line the agricultural sector so far, both in China and in other parts of the world.

The 4th industrial revolution and global decarbonisation are frequently referred to as two interrelated megatrends. Particularly, where the 4th industrial revolution is expected to fundamentally change the economy, society, and financial systems, it may also create opportunities for a zero-carbon future. Therefore, in the context of UK's legally binding commitment to achieve a net-zero emissions target by 2050, we analyse the role of economic growth, R&D expenditures, financial development, and energy consumption in causing carbon dioxide (CO2) emissions. Employing the bootstrapping bounds testing approach to examine short- and long-run relationships, our analysis is based on historical data from 1870 to 2017. The results suggest the existence of cointegration between CO2 emissions and its determinants. Financial development and energy consumption lead to environmental degradation, but R&D expenditures help to reduce CO2 emissions. The estimated environmental effects of economic growth support the EKC hypothesis. While a U-shaped relationship is found between financial development and CO2 emissions, the nexus between R&D expenditures and CO2 emissions is analogues to the EKC. In the context of the efforts to tackle climate change, our findings suggest policy prescriptions by using financial development and R&D expenditures as the key tools to meet the emissions target.

Household air pollution caused by solid fuel use for cooking is prevalent in rural China and generates various environmental and health problems. Various potential impact factors on cooking fuel decision such as income, education, modern energy, and infrastructure are examined. However, the role of family structures has been ignored. A survey on household energy consumption pattern interrelating socio-economic and demographic factors was conducted in ten villages in Northern China using stratified random sampling technique. The number of family member eating together influences households' cooking fuel decision-making significantly. The numbers of school-age children and family members under 6 and above 60 years old have no significant influence on the household's cooking fuel decision-making respectively. Compared with families with neither child nor the elderly, those with no child but at least an elderly member have 0.103 lower probability of choosing clean fuels as their primary cooking fuel. Hence, the elderly owns a heavyweight in the household fuel decision-making process in rural China, and the government should formulate policies more in line with the background of the times to deal with rural energy issues.