• Energy Research

The government of Argentina has recently declared its objective of turning the nation carbon-neutral by 2050. Thus, it is essential to identify the relevant factors which can facilitate the attainment of this environmental development target. Against this backdrop, this study aims to evaluate the impacts of renewable electricity output, trade globalization, economic growth, financial development, urbanization, and technological innovation on sectoral carbon dioxide emissions in Argentina during the 1971-2014 period. The findings, overall, suggest that enhancing renewable electricity output share in the total electricity output figure of the nation helps to curb carbon dioxide emissions generated from Argentina's energy, manufacturing and industry, residential and commercial buildings, and transportation sectors. Contrarily, greater trade globalization is evidenced to boost carbon dioxide emissions in almost all the aforementioned economic sectors. Besides, the findings also validate the existence of the carbon dioxide emission-induced environmental Kuznets curve hypothesis for all four sectors. In addition, financial development and urbanization are also evidenced to exert carbon dioxide emission-stimulating impacts, while technological innovation is witnessed to be necessary for curbing sector-based carbon dioxide emissions in Argentina. Accordingly, to decarbonize the economy, this study recommends the government of Argentina to adopt necessary policies for fostering renewable energy transition within the electricity sector, greening the trade globalization strategies, achieving environmentally sustainable economic growth, developing the financial sector by introducing green financial schemes, planning sustainable urbanization, and financing technological development-oriented projects.

The government of Argentina has recently declared its objective of turning the nation carbon-neutral by 2050. Thus, it is essential to identify the relevant factors which can facilitate the attainment of this environmental development target. Against this backdrop, this study aims to evaluate the impacts of renewable electricity output, trade globalization, economic growth, financial development, urbanization, and technological innovation on sectoral carbon dioxide emissions in Argentina during the 1971-2014 period. The findings, overall, suggest that enhancing renewable electricity output share in the total electricity output figure of the nation helps to curb carbon dioxide emissions generated from Argentina's energy, manufacturing and industry, residential and commercial buildings, and transportation sectors. Contrarily, greater trade globalization is evidenced to boost carbon dioxide emissions in almost all the aforementioned economic sectors. Besides, the findings also validate the existence of the carbon dioxide emission-induced environmental Kuznets curve hypothesis for all four sectors. In addition, financial development and urbanization are also evidenced to exert carbon dioxide emission-stimulating impacts, while technological innovation is witnessed to be necessary for curbing sector-based carbon dioxide emissions in Argentina. Accordingly, to decarbonize the economy, this study recommends the government of Argentina to adopt necessary policies for fostering renewable energy transition within the electricity sector, greening the trade globalization strategies, achieving environmentally sustainable economic growth, developing the financial sector by introducing green financial schemes, planning sustainable urbanization, and financing technological development-oriented projects.

In the current century, the G7 countries have attached more importance to energy security, and have prioritized low-carbon sources which have necessitated the consumption of nuclear and renewable energy resources to achieve a resilient low-carbon system. However, it is still not clear if the sacrifice has paid-off since the environmental quality in the majority of these countries is yet to be significantly improved. As such, this study employs advanced panel data econometric techniques that account for cross-sectional dependence and slope heterogeneity issues to explore the impacts of nuclear and renewable energy use in respect of CO2 emission mitigation in six of the seven G7 countries. The core objective of this study is to justify whether energy diversification through the promotion of nuclear and renewable energy consumption can assist the G7 nations in complying with their commitments concerning the Paris Climate Change and Sustainable Development Goals agendas. The overall findings from the econometric analysis affirm the abating role of nuclear energy on CO2 emissions. However, renewable energy consumption is found to be statistically insignificant in explaining the variations in the CO2 emission levels. On the other hand, economic growth is found to initially boost the CO2 emission level but mitigate it later on; thus, the authenticity of the environmental Kuznets curve hypothesis is established in the G7 context. Besides, the country-specific results suggest that nuclear energy significantly reduces CO2 emissions in all the countries, except in Canada and the USA. Also, renewable energy significantly curbs CO2 emissions only in Canada and France. Furthermore, the environmental Kuznets curve hypothesis is validated for Canada, France, the UK, and the USA. In line with these findings, it is pertinent for the G7 countries to boost nuclear energy use to reduce the fossil fuel dependency in the majority of the G7 nations to mitigate CO2 emissions. Moreover, it is also suggested that these nations adopt relevant policies to further green their consumption and production processes to ensure complementarity between economic growth and environmental development.

In the current century, the G7 countries have attached more importance to energy security, and have prioritized low-carbon sources which have necessitated the consumption of nuclear and renewable energy resources to achieve a resilient low-carbon system. However, it is still not clear if the sacrifice has paid-off since the environmental quality in the majority of these countries is yet to be significantly improved. As such, this study employs advanced panel data econometric techniques that account for cross-sectional dependence and slope heterogeneity issues to explore the impacts of nuclear and renewable energy use in respect of CO2 emission mitigation in six of the seven G7 countries. The core objective of this study is to justify whether energy diversification through the promotion of nuclear and renewable energy consumption can assist the G7 nations in complying with their commitments concerning the Paris Climate Change and Sustainable Development Goals agendas. The overall findings from the econometric analysis affirm the abating role of nuclear energy on CO2 emissions. However, renewable energy consumption is found to be statistically insignificant in explaining the variations in the CO2 emission levels. On the other hand, economic growth is found to initially boost the CO2 emission level but mitigate it later on; thus, the authenticity of the environmental Kuznets curve hypothesis is established in the G7 context. Besides, the country-specific results suggest that nuclear energy significantly reduces CO2 emissions in all the countries, except in Canada and the USA. Also, renewable energy significantly curbs CO2 emissions only in Canada and France. Furthermore, the environmental Kuznets curve hypothesis is validated for Canada, France, the UK, and the USA. In line with these findings, it is pertinent for the G7 countries to boost nuclear energy use to reduce the fossil fuel dependency in the majority of the G7 nations to mitigate CO2 emissions. Moreover, it is also suggested that these nations adopt relevant policies to further green their consumption and production processes to ensure complementarity between economic growth and environmental development.

Abstract The present study aims to analyse the role of technological innovation, globalization, and renewable energy to reduce environmental degradation in Pakistan by using the time series data from 1980 to 2018. The study used the quantile autoregressive distributed lag (QARDL) model for empirical estimation. According to the analysis, economic growth is positively and significantly associated with carbon dioxide emissions. The study also validates the EKC hypothesis in the case of Pakistan. Moreover, we found that technological innovation and renewable energy are negatively associated with the environmental degradation. This relationship is significant at all the quantiles. Our analysis shows that globalization is also an important source to bring an increase in CO2 emissions in Pakistan. Our empirical analysis also supports the negative role of cleaner energy for mitigating emissions in the short-term. The results from Granger causality also reveal the bidirectional causality from GDP, Innovation, and renewable energy to carbon dioxide emissions, however, there exists a unidirectional causality from GDP to globalization for Pakistan. The study provides useful policy directions for the policymakers in Pakistan.

Abstract The present study aims to analyse the role of technological innovation, globalization, and renewable energy to reduce environmental degradation in Pakistan by using the time series data from 1980 to 2018. The study used the quantile autoregressive distributed lag (QARDL) model for empirical estimation. According to the analysis, economic growth is positively and significantly associated with carbon dioxide emissions. The study also validates the EKC hypothesis in the case of Pakistan. Moreover, we found that technological innovation and renewable energy are negatively associated with the environmental degradation. This relationship is significant at all the quantiles. Our analysis shows that globalization is also an important source to bring an increase in CO2 emissions in Pakistan. Our empirical analysis also supports the negative role of cleaner energy for mitigating emissions in the short-term. The results from Granger causality also reveal the bidirectional causality from GDP, Innovation, and renewable energy to carbon dioxide emissions, however, there exists a unidirectional causality from GDP to globalization for Pakistan. The study provides useful policy directions for the policymakers in Pakistan.

Abstract Transportation infrastructure is a pillar of economic development as well as a main contributor to climate change. Therefore, it is necessary to transform the transport sector investment into climate-resilient, low-carbon transportation choices in order to achieve sustainable transportation infrastructure. In case of China, this transformation might be necessary from the perspective of the “New-style Urbanization” strategy, and for fulfilling this strategy, policy realignment is required. To address this policy-level void in the literature, we explore the influence of public private partnerships investment in transport sector, renewable energy consumption, urbanization on transport-induced carbon emissions in China. For this purpose, we apply Quantile Autoregressive Distributed Lagged (QARDL) method during 1990Q1-2018Q4. Based on the results of the study, a multipronged sustainable development goal (SDG) framework has been suggested, under which SDG 11, SDG 13, and SDG 8 are addressed, while using SDG 17 as a vehicle.

Abstract Transportation infrastructure is a pillar of economic development as well as a main contributor to climate change. Therefore, it is necessary to transform the transport sector investment into climate-resilient, low-carbon transportation choices in order to achieve sustainable transportation infrastructure. In case of China, this transformation might be necessary from the perspective of the “New-style Urbanization” strategy, and for fulfilling this strategy, policy realignment is required. To address this policy-level void in the literature, we explore the influence of public private partnerships investment in transport sector, renewable energy consumption, urbanization on transport-induced carbon emissions in China. For this purpose, we apply Quantile Autoregressive Distributed Lagged (QARDL) method during 1990Q1-2018Q4. Based on the results of the study, a multipronged sustainable development goal (SDG) framework has been suggested, under which SDG 11, SDG 13, and SDG 8 are addressed, while using SDG 17 as a vehicle.

Abstract The quality of public service transportation highly depends on the country's context, including investment, infrastructure development, and technology-based innovation in the transport sector. The core innovation of the present study is the asymmetric impacts of the airline, railway, waterway, and road on environmental pollution in China. This research analyzed and highlighted the most susceptible transportation system in China, using the newly developed Non-linear Autoregressive Distributed Lag (NARDL) model from 1985 to 2018. The results of the NARDL are positive shock and negative shock between CO2 emission and four mode-specific transportation development that led to an increase in environmental cost in the short run. The study findings divulged that airline, road, and waterway operational mileage per capita of both positive and negative transportation shocks had worsened the environmental pollution in China. On the other hand, the railway is successfully improving environmental quality in China. In order to enforce policies, local authorities should be supportive of urban public services (e.g., buses and metro) and improve public transportation services. Simultaneously, policymakers may also introduce new creative ideas for a sharing economy, such as shared bicycles and automobiles to reduce the use of private vehicles. These insights of the study could assist policymakers to improve policies for the four specific modes of transportation to better adapt to climate change and associated environmental stressors in China.