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Studying and analyzing energy consumption and structural changes in Pakistan's major economic sectors is crucial for developing targeted strategies to improve energy efficiency, support sustainable economic growth, and enhance energy security. The logarithmic mean Divisia index (LMDI) method is applied to find the factors' effects that change sector-wise energy consumption from 1990 to 2019. The results show that: (1) the change in mixed energy and sectorial income shows a negative influence, while energy intensity (EI) and population have an increasing trend over the study period. (2) The EI effects of the industrial, agriculture and transport sectors are continuously rising, which is lowering the income potential of each sector. (3) The cumulative values for the industrial, agricultural, and transport sectors increased by 57.3, 5.3, and 79.7 during 2019. Finally, predicted outcomes show that until 2035, the industrial, agriculture, and transport incomes would change by -0.97%, 13%, and 65% if the energy situation remained the same. Moreover, this sector effect is the most crucial contributor to increasing or decreasing energy consumption, and the EI effect plays the dominant role in boosting economic output. Renewable energy technologies and indigenous energy sources can be used to conserve energy and sectorial productivity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Bai, Raza. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Carbon dioxide emissions (CO 2 es) are presently a hot topic of worldwide concern. It is of great significance for lessening CO 2 es to wholly understand the transformation pattern of CO 2 es among countries, industries, and the main factors (i.e., emission effect, energy intensity, economic development, population size, carbon per unit of land, land per capita, and environmental impact per capita effects) influencing CO 2 es. Thus, to mitigate the country's CO 2 es efficiently, it is necessary to determine the driving factors of its emissions and damage variations. For this, we use the logarithmic mean Divisia index method. This research decomposes the major two dimensions, such as carbon sources and carbon damage variations from 1986 to 2020, into eight factors. The results show that Pakistan's CO 2 es increased continuously during the period, with an average annual growth rate of 4.76%. Growing the country's CO 2 es over 1986-2020, the key influencing factors are economic development, population, and land, while energy intensity and emission factors are the main forces in mitigating CO 2 es. The carbon source and carbon damage dimensions reached 68.75 Mt and 208.56 Mt, respectively, which led to a rise in CO 2 e. The entire set of factors is averagely moving around the major outcomes that provide significant policy measures. Finally, to efficiently reduce CO 2 e, Pakistan should concentrate on specific industrial paths and implement challenging, comprehensive governance to attain a low-carbon chain throughout the process. Thus, based on empirical results, this research put forward policy suggestions for cleaner production to reduce CO 2 emissions further, and environmental policies must be tailored to local conditions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The transport sector is a key engine of Bangladesh's quick oil demand growth. It accounted for 64.4% of overall Bangladesh oil consumption in 2019 and is, therefore, a third contributor to CO 2 emissions and related pollutants. The substitutability of energy and non-energy factors is the key issue in framing and planning energy policies. Therefore, we determine a translog production function for the transport sector, including inputs labor, capital and energy. The research analyzes factor output and substitution possibilities from 1990 to 2019. Outcomes show (a) labor output elasticity is higher, followed by energy and capital. (b) All the substituting factors are rising return to scale, with relatively high substitution (around 1.63-2.05, 1.05-1.06, 0.77-0.92) between capital-labor, capital-energy and labor-energy, which proposes that the substitution between capital-labor and capital-energy could be attained through updating technology. Therefore, by giving maximum capital to the transport sector, appropriate energy-conserving technology could be maximally encouraged, and capital-energy substitutability would have better results in the future. (c) Though, technical progress is calculated to be between 0.009 and 0.14 between the various inputs. The input labor-energy is quicker substitutes with their relative difference in technological progress, while capital also presents proof of convergence. By assigning additional capital to the transport sector, energy-saving technologies could be enhanced and CO 2 emissions reduction could be achieved. Finally, advancement in capital and skilled labor and, thus, substitution between energy-labor and the transition of labor-capital can be achieved., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author.)

Many studies have computed the carbon dioxide emissions (CO 2 Es) associated with energy consumption, overall population, imports, manufacturing industries, and financial development in various countries. However, past studies have ignored the impact of CO 2 Es on fossil fuel energy, domestic economy, rural-urban unemployment, rural-urban population, services value-added, and fiscal deficit, especially in the context of Pakistan. Thus, to avoid the problems of mis-specification, sustainable growth, and carbon reduction simultaneously, it is necessary to study how to accomplish the time-varying relationship between factors. The present study applied autoregressive distributed lag (ARDL) model for cointegration between CO 2 Es and its determinants to test long-run and short-run effects from 1975 to 2018. The findings are as follows: first, in the short run, CO 2 Es, fossil fuel, and services value added show the unidirectional causality, while CO 2 Es, economic growth, rural-urban population, rural-urban unemployment, and fiscal deficit have bidirectional causality among them. Second, in the long run, we found bidirectional causality between CO 2 Es and its determinants. Finally, the diagnostic estimations, cumulative sum, and cumulative sum of squares check the long-run association between the selected variables and present the constancy of coefficients. The empirical outcomes give new insights for policymakers to regulate renewable technology investment in the energy sector for the improvement of environmental excellence. Related to the key results, the focused policies are presented below., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Several studies have quantified the carbon dioxide (CO 2) emissions associated with energy consumption, agriculture value added, food crop production, forest covered area, and forest production in various countries. However, past studies have ignored the long-term and short-term effects of these factors on CO 2 . This study used data from 1980 to 2018 and applied the autoregressive distributed lag model (ARDL) technique to test long-run and short-run effects of these factors on CO 2 emission in the Pakistani context. The results revealed that in short-run food crop production, forest covered area and forest production have capacity to reduce CO 2 emission. However, in long run, energy consumption and agriculture value added along with food crop production, forest covered area, and forest production are negatively and significantly related to CO 2 emission which shows that these sectors, in long run, have capacity to mitigate emissions. Additionally, results also show that food crop production and forest covered area are more effective to reduce CO 2 emission as compared to other sectors. The robustness of the results was supported by using additional models and tests. This study provides scholars with valuable insights and also helps government authorities and policymakers to develop comprehensive strategies to reduce carbon emissions., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The transport sector has become one of the major economic, huge fossil fuel energy consumption, and carbon dioxide (CO 2 ) emitting sector of Pakistan. This study applies the logarithmic mean Divisia index (LMDI) and Tapio's decoupling approach to estimate decoupling state and mitigation potential of CO 2 emissions from the transport sector during 1984-2018. LMDI technique is applied to detect the influencing variables (i.e. carbon coefficient, fuel consumption, total energy consumption, and turn over economy), which oversee CO 2 emissions. The outcomes show that CO 2 coefficient effect is the factor which is decreasing CO 2 emissions while economic growth (EG) effect is the factor which is growing CO 2 emissions. The decoupling index is also applied to influencing factors which reflect the EG factors on CO 2 emissions from the transport sector. The consequences confirm that during 1984-2018, the CO 2 emissions show an expensive coupling with EG. Weak decoupling occurred only in the sub-periods 1999-2003, 2004-2008, and 2009-2013. Similarly, the CO 2 emissions occurred from only three decoupling grades. Furthermore, a mitigation model based on the above impacting variables estimates the mitigation rate of CO 2 emissions and showed that the CO 2 mitigation seemed in 1999-2003, 2004-2008, and 2009-2013. Finally, forecasting outcomes of Tapio decoupling index show a weak decoupling during 2018-2030. Therefore, based on the empirical outcomes, this study puts forward a few policy suggestions to efficiently enhance the decoupling between Pakistan's transport CO 2 emissions and EG., Competing Interests: Declaration of competing interest We declare that there is no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This study aims to examine the impact of public-private partnerships (PPP) investment in energy, technological innovations (TI), economic growth (EG), exports, and foreign direct investment (FDI) on CO 2 emissions in Brazil over the period from 1984 to 2018. In doing so, we employ the Ng-Perron unit root test to examine the stationarity and autoregressive lag distributed (ARDL) model for cointegration between CO 2 emissions and its determinants. The outcomes are as follows: first, in the long run, the PPP investment in energy deteriorates the environmental quality by increasing CO 2 emissions, while TI has a significant negative effect on CO 2 emissions. It is also found that the exports and FDI degrade the environmental quality and the relationship between EG and CO 2 emissions is inverted U-Shaped, presence of the EKC hypothesis. Second, in the short run, PPP investment in the energy sector is negatively influencing, while TI has a positive association with carbon emissions. The empirical findings provide new insights for policymakers to regulate PPP investment in the energy sector for the improvement of environmental quality in Brazil. Graphical abstract.

This study examines the effect of financial development (FD) and foreign direct investment (FDI) on the environmental quality for the panel of 90 belt and road countries from 1990 to 2017. This study advances the knowledge of financial development by using the new comprehensive index, which is based on access, depth, and efficiency of financial markets and financial institutions and incorporated foreign direct investment as an important determinant of environmental quality. By applying the Driscoll-Kraay standard error pooled ordinary least square method, the empirical findings reveal that FD deteriorates the environmental quality by increasing the CO 2 emissions, while FDI improves environmental quality and the relationship between economic growth (EG) and CO 2 emissions is inverted U-shaped, i.e., presence of EKC hypothesis. The energy consumption and urbanization pollute the environment, while trade openness enhances the quality of the environment. Furthermore, the Dumitrescu-Hurlin (DH) panel causality test result confirms that the bidirectional causality exists among FD, trade openness, energy consumption, and urbanization with CO 2 emissions. The empirical results provide new insights for policymakers and also have several implications for the betterment of environmental quality.