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China's carbon neutrality target requires early carbon decoupling of economic growth. Utilizing the input-output and programming technique, we investigate the carbon mitigation potential of industrial restructuring along with the substitution of non-fossil energy for electric production. Given the constraints of manufacturing stabilization and employment volatility magnitude, this paper finds that industrial restructuring can mitigate carbon emissions by 7.47 %. Besides, non-fossil energy substitution in electric production can strengthen the inhibiting effect, reducing carbon emissions from 7.47 % (currently about 31.5 % for non-fossil power generation) to 28.99 % (about 80 % in the future). This paper also simulates several scenarios for growth rates and estimates the prospective carbon reduction for the fourteenth Five-Year Plan in China. We indicate that the rising share of non-fossil energy is the linchpin to reducing energy-related carbon emissions, which can achieve absolute decoupling if the share of non-fossil energy in power generation reaches 67.1 % under different growth scenarios. This paper argues that carbon-based performance indicators, e.g., carbon intensity and carbon emissions, are more appropriate for local bureaucrats than energy-based ones. We provide valuable implications for the carbon decoupling path. • This paper combines the input-output technique and programming model. • Industrial restructuring can mitigate carbon emissions by 7.47 %. • Non-fossil energy substitution can further amplify the emission reduction effect. • The rising share of non-fossil fuels is the linchpin to achieving absolute decoupling. [ABSTRACT FROM AUTHOR]

To reflect the trend of electricity consumption (EC) in China's Pearl River Delta (PRD) under a balanced environment and economy, this paper proposes an EC forecasting framework from the perspective of optimal economic growth. The historical GDP statistics of the PRD are calibrated with data from the new "NPP-VIIRS-like" nighttime light dataset from 2000 to 2020, and two simulation scenarios of optimal economic growth are constructed according to the carbon emission reduction rate. Finally, based on the electricity data from 2000 to 2017, an error correction model is constructed to predict and compare the trend of EC in the PRD under different carbon emission scenarios. The results demonstrate the following. (1) The economic growth path under low-carbon constraints is more closely aligned with the actual economic development of the PRD. (2) The electricity demand required to sustain optimal economic growth in the PRD under low-carbon constraints is projected to reach saturation around 2037, approximately a decade earlier than the scenario without carbon constraints. The results of the projections are expected to guide future work on power system planning and economic development assessment in the context of carbon reduction. • The balance between environmental resources and economic development is considered. • The optimal economic growth path under the low-carbon goal is measured. • Calibration of regional statistics with the nighttime light dataset "NPP-VIIRS-like". • The error correction model is built as a short-term regulation mechanism for power prediction. • Predicted electricity demand for optimal economic growth in the PRD under different scenarios. [ABSTRACT FROM AUTHOR]

Decoupling of electricity CO 2 emissions (ECE) is pivotal in achieving China's "double carbon" goal. However, empirical studies primarily focus on the decoupling of ECE from the production side of a specific country or region, thereby ignoring the spatial separation of electricity production and consumption due to the highly connected electricity network. Decoupling of ECE from the consumption side is also crucial. In this study, the IPCC inventory method and quasi-input-output (QIO) model were comprehensively used to establish an electricity CO 2 emission accounting framework covering both the production and consumption sides. The Tapio and Logarithmic Mean Division Index (LMDI) models were used to explore the decoupling relationship between ECE and economic growth and the driving factors. Results ultimately show the following:(1) During 2007 to 2020, the decoupling situation experienced a process from weak decoupling to strong decoupling and finally to expansive negative decoupling; (2) The economically developed eastern regions and the western regions that are affluent in renewable energy resources showed different decoupling states; (3) Renewable energy in the southwest and nuclear electricity generation in the east promotes production-side decoupling, while fossil energy electricity generation in the north inhibited production-side decoupling. Industrial restructuring in the northeastern region and the western electricity-generating provinces has contributed to the decoupling at the consumption side. The research is helpful for China's national and provincial electricity sectors to set up a comprehensive emission reduction policy based on shared responsibility allocation from the production and consumption sides. • Consumption-side decoupling complements the emission reduction policy. • Decoupling on the production and consumption sides is of great difference. • The decoupling process showed an inverted U shape. • The renewable energy effect promotes the decoupling on the production side. • The industrial structure effect promotes the decoupling on the consumption side. [ABSTRACT FROM AUTHOR]

Climate change has become a more pressing issue as time goes on, the role of green growth and green innovation emerges as a driving force for cleaner economic growth and a healthy environment by reducing environmental contamination. Environmental pollution is influenced by a wide variety of factors, as evidenced by numerous research studies. The impact of green growth and green innovation, as well as ICT on CO2 emissions has not been adequately examined in these research studies. This study highlights the importance of green growth (GG) and green innovation (GIN) for sustainable development. Our study aims to fill the gap by investigating how green growth impacts CO2 emissions in Pakistan, specifically in light of green innovations and ICT. A key innovation of this research is its incorporation of ICT interaction with green growth and green innovation. The results from augmented ARDL analysis constitute that green growth and green innovation significantly contribute to improving environmental sustainability in Pakistan. But in contrast, ICT shows a significant positive relationship with CO2 emissions. Similarly, the interaction between GG*ICT upsurge CO2 emissions, however, the role of the interaction term GIN*ICT is positive in enhancing environmental quality. As a result, policymakers and regulators should focus on promoting a green growth agenda and green innovation to mitigate CO2 emissions and achieve sustainable development goals. • An increase in green growth enhances environmental quality. • Green innovations are conducive to carbon reduction. • ICT impedes environmental sustainability. • The moderating role of ICT with green innovation fosters environmental quality. • The moderating role of ICT with green growth hinders environmental sustainability. [ABSTRACT FROM AUTHOR]

Bangladesh has traditionally relied on fossil fuels for meeting its energy demand whereby this major South Asian economy has not been able to safeguard its environment from greenhouse gas emission-related adversities. Moreover, by ratifying several international environmental agreements, especially the Paris Accord and the Sustainable Development Goals, the government of Bangladesh has expressed its solidarity in abating greenhouse gas emissions through the deployment of relevant environmental policies. Hence, this study assesses the impacts of petroleum consumption, economic growth, and technological innovation on carbon emissions in Bangladesh using quarterly frequency data from 1972Q1 to 2020Q4. Overall, apart from confirming the cointegrating relationships among the variables, the regression findings reveal that higher petroleum consumption and economic growth stimulate environmental degradation by boosting carbon dioxide emissions while technological innovation reinstates environmental well-being by curbing the Bangladesh's emission figures. Additionally, technological innovation is seen to moderate the relationship between petroleum consumption and carbon emissions by jointly reducing the emissions with petroleum consumption. Lastly, the causality analysis shows that petroleum consumption, economic growth, and technological innovation causally influence carbon emissions. Based on these key findings, it is recommended that Bangladesh mitigates its petroleum dependency, blends environmental objectives into its economic growth policies, and develops its technological stock. • Determinants of environmental well-being in Bangladesh are analyzed. • Petroleum consumption and economic growth boost carbon emissions. • Technological innovation reduce carbon emissions. • Technological innovation moderates the petroleum consumption-carbon emissions nexus. • Petroleum consumption and technological innovation jointly reduce carbon emissions. [ABSTRACT FROM AUTHOR]

The manufacturing industry makes the greatest contribution to China's carbon emissions, so reducing emissions among its high-emission subsectors is important to achieve China's overall reduction goals. Innovation is crucial to the green transformation and development of high-emission subsectors. Previous studies have hardly considered the effect of innovation factors on carbon emissions and decoupling of high-emission subsectors. This study incorporated innovation factors into the GDIM (generalized dividing index method) and DEI (decoupling effort index) models and decomposed them into three variables, the innovation input scale, innovation input carbon intensity, and innovation input efficiency, in order to compare the impact of different factors on carbon emissions and decoupling of high-emission subsectors. This approach expands the application scope of the GDIM method and helps to formulate the green transformation policies of the high-emissions manufacturing sector. The results were as follows. (1) The innovation input scale is the primary factor leading to the increase in carbon emissions. The cumulative increase of carbon emissions in the high-emission sectors from 1995 to 2019 was 3.45 billion tons. Innovation input carbon intensity is the primary factor that inhibits the carbon emissions growth. (2) There were significant differences in the degree of decoupling between the high-emission sectors in manufacturing in different periods. The decoupling effect of the manufacture of non-metallic mineral sector was the best; it achieved strong decoupling in 2015–2019, with the DEI reaching 2.17. (3) Decoupling efforts with regard to the carbon intensity of outputs and innovation inputs are the key factors that determine the decoupling of economic growth and carbon emissions in the high-emission subsectors of the manufacturing industry. • Factor decomposition and the decoupling effect of carbon emissions in manufacturing. • The GDIM and DEI are combined to identify the drivers of decoupling. • Most high-emission sectors of manufacturing are weakly decoupled or not decoupled. • The carbon intensity of the output and innovation inputs are key factors. • This study contributes to targeted interventions towards low-carbon manufacturing. [ABSTRACT FROM AUTHOR]

As the largest carbon emission emitter, China has made a commitment to the international community to achieve carbon neutrality before 2060. While most literature suggests such a goal could be achieved mainly through slowing down economic growth, promoting energy transformation, and adjusting the industrial structure, little is known about how improving the economic development quality would have an impact on China's carbon emissions and achieving carbon neutrality goal. Here based on the environmental Kuznets curve model and scenario analysis, we explored future courses of carbon neutrality, in terms of CO 2 emissions, in China under different scenarios of economic development quality. Results suggest that under the conventional, accelerated, and enhanced improvement scenarios, China could reach a carbon peak in 2027, 2026, and 2025 (3.5075, 3.5074, and 3.5066 billion tonnes, respectively), and then achieve the zero carbon emission goal in 2050, 2044 and 2040, respectively. However, achieving such an ambitious trajectory is contingent upon significant improvements in the economic development quality that China should focus on at present and in the future. • We aimed to study when China can reach carbon neutrality in terms of CO 2. • The economic development quality would have great impacts on achieving China's carbon neutrality goal. • The Environmental Kuznets Curve model and scenario analysis were adopted. • China can reach carbon neutrality before 2050 through improving economic development quality. [ABSTRACT FROM AUTHOR]

The present study was conducted to investigate the effect of energy intensity and economic growth on environmental quality in three populous countries in the Middle East region, including Iran, Iraq, and Turkey. For this purpose, the environmental Kuznets curve (EKC) hypothesis was tested along with comparison of ecological footprint (EF) and carbon dioxide (CO2) emission indicators during 1971–2015. According to stationary properties of the variables, the auto-regressive distributed lag (ARDL) approach was used to study the existence of short- and long-run relationships. The empirical results provided the evidence supporting inverted U-shaped nexus for per capita income and environmental degradation by employing two environmental indicators in Turkey. In addition, the hypothesis was confirmed by employing EF index and was rejected by employing CO2 emissions in Iran and Iraq. Besides, the results showed that energy intensity is one of important sources of environmental degradation in all the studied countries and there was a significant positive relationship between energy intensity, CO2 emissions, and EF in all the studied countries. • EF and CO2 were compared in validation EKC hypothesis in Iran, Iraq, and Turkey. • There is a significant positive impact of energy intensity on CO2 and EF. • EKC hypothesis was confirmed by employing EF and CO2 in Turkey. • In Iran and Iraq, EKC hypothesis was approved by employing EF and rejected by CO2. [ABSTRACT FROM AUTHOR]

Planning process focusing on Energy-Environment-Economy nexus heavily relies upon the results of causality studies for policy and decision guidance. These studies are mostly aimed to determine the true direction of the causal-path among key variables such as energy consumption, economic growth and GHGs emissions. However, there are some weak points attached to already available methods and their variants such as Granger type causality tests and Peter and Clark (PC) algorithms based on Graph theoretic approach. Swanson and Granger (1997) [89] used the vector autoregressive (VAR) residuals in the PC algorithms to find the causal ordering in time series. However, these residuals carry only contemporaneous information about cross-variable effect and remove the past information. This study modified the original PC algorithms based on modified R-residuals test to analyze the causal relationship between energy consumption, economic growth and GHGs emissions in Pakistan. The results reveal that, unidirectional causality is running from economic growth towards CO 2 emissions. However, no causality is running from energy consumption towards economic growth and vice-versa. This is due to the fact that, a significant portion of energy is consumed in residential and transportation sectors, both of which does not contribute to economic growth in long-run. [ABSTRACT FROM AUTHOR]