• Energy Research

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.

Carbon dioxide emission and GHGs are associated with fossil fuels which have adverse effects on the environment. The key intention of this paper was to determine the asymmetric effect of CO2 emission on expenditures, trade, FDI, and renewable energy consumption in Pakistan. An asymmetrical technique (nonlinear autoregressive distributed lag) was employed to validate the constructive and adverse relation among variables. Furthermore, the Granger causality test was also used to verify the unidirectional association amid variables. Study outcomes revealed that the adverse shocks of renewable energy consumption exposed expressively to upsurge CO2 emission in the short-run dynamics. Conversely, constructive shocks of renewable energy consumption display an adversative association with CO2 emission. Furthermore, the decreasing trend in foreign direct investment tends to impede the detrimental effects of CO2 emission. Additionally, the variable expenditures also create the non-eco-friendly impacts and manifest the positive linkage through CO2 emission. Trade possesses statistically insignificant linkage with environmental degradation. The results also disclose that positive as well as negative variations in the foreign direct investment expose to degrade the environmental eminence. Long-run results suggest the direct association between downward trend in renewable energy consumption and CO2 emission signifying that the pollution level decreases, and the upward trend in renewable energy consumption, however, demonstrates insignificantly positive effects. The results also disclose that positive as well as negative variations in the FDI lead to degrade the CO2 emission. Moreover, it is found that the expenditures soar the issue of pollution again in the long run. Finally, the consequence of trade on CO2 emission is adverse, as the outcome suggests. In order to improve the environmental policies for sustainable growth, the study provides direction toward a sustainable environment by reducing carbon dioxide emission.

Electricity is a versatile form of energy that plays a vital role in fulfilling the daily requirements of human life. The primary aim of this study was to investigate and explore the link between economic growth, electricity access, energy use, and population growth in Pakistan for the period 1990–2016. An autoregressive distributed lag (ARDL) bounds testing approach to cointegration was applied to investigate the causality link between the study variables. These tests shed light on the long-run connection among the variables; further, the results revealed that the electricity access to the total population, electricity access to the urban population, energy usage, population growth, and urban population growth had a significant impact on economic growth, while the electricity access to the rural population and rural population growth had a negative impact on the economic growth in Pakistan. According to these findings, this study recommends that the government of Pakistan pay further attention to increasing its electricity production from different sources, including hydroelectric, solar, oil, and gas, and nuclear in order to fulfill the country’s demands.

The electric power industry has a dominant contribution to economic development in China, and growth in the industry needs to help the economy grow, protect the environment, and give people access to electricity. The current study’s main goal is to assess the rural and urban populations’ access to electricity, energy use, and economic development in China using yearly data ranging from 1995 to 2017. We applied two unit root tests to check the variables’ stationarity and a symmetric autoregressive distributed lag (ARDL) approach to discover the variable links using long-run and short-run estimates. The Granger causality test was also used in this study under a vector error correction model (VECM) to assess the variables’ unidirectional connection. Short-run results demonstrate that total population access to electricity, urban population access to electricity, and energy use have positive links with economic development, with probability values of (0.004), (0.000), and (0.007), respectively. Similarly, long-run evidence shows that variables such as total population access to electricity, urban population access to electricity, and energy use have a positive relationship with economic growth, with p-values of (0.005), (0.000), and (0.047), respectively. Unfortunately, throughout the investigation, the variable electricity availability to the rural population demonstrated an adverse relationship with China’s economic growth. Furthermore, the Granger causality test results under the vector error correction model (VECM) show that all variables have unidirectional links. China’s implementation of new plans regarding energy consumption has a significant impact on both future energy supply and the country’s ability to stay sustainable. It will be able to maintain the stability of its energy levels as long as it sticks to suitable choices and policy options. Undoubtedly, China is a huge user of energy and an emitter of CO2 emissions; therefore, possible conservative strategies and policies are required from the Chinese government to use clean energy sources to fulfill its energy demand.

This study aims to examine the impact of coal energy consumption on the economic progress in Pakistan by using annual time series data during 1972–2019. Three-unit root tests were employed to rectify the variables’ stationarity. The quantile regression approach with the extension of cointegration regression test was utilized to check the variables interaction with the economic progress. The outcomes of the quantile regression uncover that coal energy consumption in power sector and coal energy consumption in brick kilns have adverse influence to the economic progress, while total coal energy consumption has a productive association with the economic progress. Similarly, the findings of cointegration regression analysis uncover that via FMOLS (Fully Modified Least Squares) and DOLS (Dynamic Least Squares) that variables coal energy consumption in power sector and brick kilns have an adverse connection with the economic progress, while total coal energy consumption uncover a productive linkage to the economic progress in Pakistan. Pakistan is still facing a deep energy crisis because of the lack of energy production from cheap sources. New possible policies are required in this direction to improve the energy sector by paying more attention to the alternative energy sources to foster the economic progress.

Carbon dioxide emission and greenhouse gas emissions are considered core issue in the world that influence agricultural production and also cause climate change. The present study seeks to investigate the linkage of methane emissions, nitrous oxide emissions, carbon dioxide emission, and greenhouse gas emissions with agricultural gross domestic product in China. The long-term association was checked by using an autoregressive distributed lag (ARDL) bounds testing approach, fully modified least squares method, and canonical cointegrating regression analysis. The results from long-run analysis exposed that carbon dioxide emission and greenhouse gas emissions have positive coefficients that demonstrate the long-run linkage with the agricultural gross domestic product having p values of 0.5709 and 0.3751, respectively. Similarly, results also revealed that agricultural methane emissions and agricultural nitrous oxide emissions have a negative association with the agricultural gross domestic product having p values of 0.1737 and 0.0559. China is a huge emitter of CO2 emission and greenhouse gas emissions. Possible conservative policies are required to form the Chinese government to tackle this challenge to decrease CO2 emission in order to increase agricultural production.

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations.

Greenhouse gases are considered an immense threat for the environment and humanity on the planet, and also cause the climatic change. The present analysis key aim was to explore the effect of CO2 emission on foreign investment, renewable energy utilization, and population growth in Pakistan. The ARDL bounds testing technique was applied to investigate the variables' interaction via short- and long-run analysis. Furthermore, pairwise Granger causality method was also utilized to check the causal relation amid the study variables. Outcomes expose that CO2 emission has an adverse interaction with renewable energy with probability value (0.5497), while the variable foreign investment and population growth exposed a constructive association with carbon dioxide emission with probability values (0.3548) and (0.4217) consistently. Similarly, the results through long-run analysis expose that CO2 emission has an adverse influence to renewable energy usage with P-value (0.4646). Moreover, the results also uncovered that foreign investment and population growth has positive interaction with CO2 emission and having probability values (0.3577) and (0.5715). Solid steps are required from the Pakistani government regarding the demonization of CO2 emission in order to upsurge the economic progress.

Although urban agglomerations have introduced substantial contributions to the economies around the globe, it has also led to the serious environmental challenges. However, this situation may vary across the development levels. The existing knowledge offers a gap in terms of both theoretical and empirical grounds. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) is previously not known to incorporate land agglomeration and the intensity of energy use. Besides, the investigation of linkages among the variables of interest across the development levels within a country is not known to be considered by the existing knowledge. This study systematically investigates the heterogeneous dynamic causality among the intensity of energy use, land agglomeration, carbon dioxide emissions (CO2), and economic progress across the development levels in the Chinese economy, considering 29 provinces for the period 2000 to 2018. To this end, a long-term co-integration association is tested and found existent among the variables of interest. A dynamic common correlated effects mean group approach is applied for impact analysis. The key findings include: The impacts of economic progress and land agglomeration on CO2 are found positive and significant in the country panel and western zone of China (WZC). It turned to be neutral in the case of the central zone of China (CZC) and significantly negative in the eastern zone of China (EZC). To this end, economic progress presented a ‘development ladder-based CO2 mitigation effect,’ while the land agglomeration exposed the ‘land agglomeration ladder-based CO2 mitigation effect’. Further, the causalities extracted are: first, economic progress is found in positive bilateral linkages with the intensity of energy use and land agglomeration for all the panels. Second, a positive and unilateral causal bridge is found operating from land agglomeration to the intensity of energy use and from the intensity of energy use to CO2. Third, a unilateral linkage of mixed nature is exposed to exist from land agglomeration to CO2, with positive causal links for country panel and WZC, negative causal links for EZC, while a neutral linkage is found for CZC. Fourth, a bidirectional link with mixed causalities appeared in the country panel and WZC. Economic progress increased CO2 in WZC. Next, a negative bilateral link is observed between the two variables in EZC. Additionally, this link remained neutral in CZC. Based on empirics, it is revealed that the development level matters in determining the links among the variables of interest.