• Energy Research
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AbstractAfter China's economy entered a “new normal,” their economic development model shifted from an energy‐intensive to an energy‐saving, given that China's electricity and heating industry accounts for about half of the country's energy consumption and carbon emissions. Based on the sample data from 2005 to 2020, this paper adopts the energy consumption method and the extended index decomposition model to explore carbon emissions of the electricity and heating industry in the early and late period of the economic new normal. The results show that: (1) carbon emissions from the electricity and heating industry showed a growing direction in the economic new normal period. However, compared with the early period of economic new normal, the increasing speed of carbon emissions from the electricity and heating industry slowed down significantly in the late period. This point also directly reflects that the extensive development mode of energy utilization has been alleviated after the electricity and heating industry entered the economic new normal. (2) Compared with the early period, the energy structure effect on the emission reduction was enhanced after entering the economic new normal. Meanwhile, the investment efficiency effect has changed from promoting to inhibiting. (3) Compared with the early period, the promotion impact of the investment scale effect on carbon emissions in the electricity and heating industry has no significant change after entering the economic new normal. Nevertheless, it is noteworthy that the emission reduction impact of the energy intensity effect is weak. This paper not only provides empirical evidence for evaluating the emission reduction effects of the Chinese electricity and heating industry before and after the economic new normal but also shares policy insights for precise emission reduction in the electricity and heating industry in the later stage of the economic new normal.

The present study investigates the impact of economic growth, hydropower generation, and urbanization on Malaysia’s CO2 emissions. This study applies Quantile Autoregressive Lagged (QARDL) technique for the period of 1965Q1 to 2018Q4. The Granger-causality in quantiles is applied to confirm the causal nexus among the modeled variables. The outcomes demonstrate that hydropower generation decreases the detrimental effects of CO2 emissions at the range of high quantile levels. Furthermore, urbanization, except for higher quantiles, exhibits negative impacts on CO2 emissions. Also, the QARDL coefficients confirm the presence of the Environmental Kuznets Curve hypothesis from median to higher quantiles. Besides, the Granger-causality test confirms the two-way causality among CO2 emissions and hydropower generation in Malaysia’s economy and the same for the other series. The policymakers should enhance the market attractiveness of hydropower generation projects through incentives for the investors.

Since China has entered the economic "new normal," China's industries pay more attention to green and low-carbon development. However, the transportation industry is still one of the three industries with high carbon emissions at present. Based on this, this paper first constructed two scenarios for the early and late stages of economic "new normal." Furthermore, using the extended structural decomposition model, input-output method, and energy consumption method, this paper studied the carbon emissions status and emissions reduction effect of China's transportation industries in the early and late stages of economic "new normal." The results showed as follows. (1) Compared with the early stage of economic "new normal," the energy intensity of transportation industries and optimization of energy consumption structure played a better role in emissions reduction after entering the economic "new normal." However, the input structure effect reflecting generalized technological progress did not play a significant role. (2) Compared with the early stage of economic "new normal," low-carbon energy such as liquefied petroleum gas, natural gas, and liquefied natural gas played a more significant role in the energy structure effect with the emissions reduction effect showing an obvious enhancement trend over time after entering the economic "new normal." (3) In the early or late stage of economic "new normal," the final demand effect was the main driving factor for the growth of CO2 emissions in the transportation industry. Meanwhile, compared with the early stage of economic "new normal," the final demand effect had a stronger driving effect in the late stage of economic "new normal." In these two periods, the second industry and the third industry were the main contributors to the final demand effect. This paper provided a basic theoretical analysis basis for carbon emission control of transportation industry under the "new normal" of the Chinese economy, and also provided a realistic guidance path for the transportation industry to carry out more accurate emission reduction from the level of energy varieties on the demand side and industry on the demand side.

In recent years, blockchain technology has generally provided a wide range of application values in various fields. However, interdisciplinary research on blockchain technology and carbon trading companies is currently rare. Based on this, this paper takes the integration of blockchain technology and carbon trading companies as the background and draws on relevant theories such as blockchain technology, carbon trading mechanisms, and major technological changes to study the influencing factors of carbon trading companies applying blockchain technology by combining theoretical deduction with an empirical test. The results show that (1) the number of companies in China's eight carbon trading pilots shows an obvious regional imbalance. Among them, more companies participated in the carbon trading pilot in Shenzhen and Beijing while less in Tianjin and Hubei. Meanwhile, the participating companies in the eight carbon trading pilots are mainly concentrated in eight industries, including electric power, petrochemical, chemical, building materials, iron and steel, nonferrous metals, papermaking, and domestic civil aviation. (2) The willingness of carbon pilot companies to use blockchain technology is stronger; the time for carbon pilot companies to learn and master blockchain technology is shorter, otherwise, the longer. Therefore, priority can be given to applying blockchain technology in carbon pilot industries with strong use willingness. (3) If more companies participate in carbon trading, the easier it is for companies to learn to use blockchain technology in the early stage. Therefore, if the pilot for the application of blockchain technology is carried out in carbon trading companies, the two carbon pilots in Shenzhen and Beijing can be given priority. This paper further enriches the relatively scarce existing interdisciplinary literature on blockchain technology and carbon trading in theory and also provides guidance for the effective application of blockchain technology by carbon trading companies in reality.

The excessive growth of carbon emissions (CO2E) from industrial energy use not only exacerbates global warming and severely curbs the sustainable development of the economy and society. As a high energy-consuming sector second only to the fossil energy division, the power and heavy division, China's chemical industry should have received more attention for its CO2E. However, there are limited literatures on energy CO2E in China's chemical sector at present. Based on this fact, this current paper uses the energy utilization approach, the input–output analysis approach, and the extended structural decomposition method to evaluate the energy-related CO2E of China's chemical sector from 2007 to 2017. (1) China's chemical sector energy-related CO2E showed a trend of first growth and then a slow decline, demonstrating that the rapid growth of China's chemical sector energy-related CO2E has been effectively controlled; However, it should be noted that the chemical industry is still dominated by high-CO2E energy-related CO2E at the current stage. (2) Input structure and energy intensity effects have a reduced influence on the growth of energy-related CO2E in China's chemical sector. This is due to upgrading energy use technology and optimizing the generalized technology progress rate in the chemical sector. (3) Energy structure and final demand effects have encouraged the growth of the chemical sector's energy-related CO2E. It shows that the industrial system's demand for chemical products is constantly expanding, and the chemical products still have the characteristics of high carbonization. Also, the chemical sector's supply-side energy utilization structure has not been significantly enhanced.

The study explores the association between economic complexity, globalization, renewable and non-renewable energy consumption on the ecological footprint in the case of India from 1990–2018. The autoregressive distributed lag (ARDL) is applied to measure the long-run elasticity, while the vector error correction model (VECM) is applied to classify the causal path. The empirical findings demonstrate that economic complexity, globalization process, and renewable energy consumption play a dominant role in minimizing environmental degradation. In contrast, economic growth and non-renewable energy consumption are more responsible for increasing the pollution level in both the short and long run. Furthermore, the VECM outcomes disclose that there is long-run causality between ecological footprint and economic complexity. Moreover, the empirical outcomes are robust to various robustness checks performed for analysis to the consistency of our main results. The Indian government/policymakers should encourage a more environmentally friendly production process and eco-friendly technologies in exports to minimize environmental degradation.

First and foremost, the present study seeks to traverse the informal sector characterized by a shadow economy in the presence of financial development, economic growth, and stock market performance on environmental pollution in Nigeria from 1981 to 2019. The dynamic autoregressive distributed lag (DARDL) approach was used to measure the short- and long-run elasticities, while spectral causality is applied to categorize the causal directions. Findings from the study revealed that the structural break unit root test revealed that all variables are stationary at first difference. The ARDL bound test confirmed the existence of long-run association among the used variables. The ARDL long-run results reveal that economic growth, financial development, and stock market performance are significantly responsible for carbon emission in Nigeria, while the shadow economy significantly improves environmental quality in Nigeria. Findings from the spectral causality results show a unidirectional causal relationship between financial development, economic growth, trade, stock market performance, and shadow economy to carbon emission in Nigeria. The empirical findings of this study provide some perceptive policy recommendations to overcome the adverse effect of carbon emissions in the environment.

The Mexico, Indonesia, Nigeria, and Turkey (MINT) countries have practiced significant levels of economic growth over the years. However, these countries have not managed to protect their environmental quality in tandem. Thus, the aggravation of environmental indicators traversing these countries radiates a shadow of uncertainty on their achievement of economic growth sustainability. In this regard, green investment and technological innovations are commonly considered as an effective aspect geared to minimize CO2 emissions, as these increase energy efficiency and involve cleaner production. Thus, this study investigates the effect of green investment, economic growth, technological innovation, non-renewable energy use, and globalization on the carbon dioxide (CO2) emissions in MINT countries from 2000 to 2020. After checking the stationary process, this study applied fully modified ordinary least square and dynamic ordinary least square methods to estimate the long-run elasticity of the mentioned regressors on CO2 emissions. The outcomes show that non-renewable energy and technological innovations significantly increase environmental degradation. In contrast, the globalization process and green investment significantly reduce it in the long run. Moreover, the interaction effect of green investment and globalization significantly overcomes the pressure on the environment. Similarly, the moderation effect of technological innovation and globalization significantly reduces the emission level in the region. Moreover, the U-shaped environmental Kuznets curve hypothesis was observed between economic growth and carbon emission across the MINT countries. Furthermore, the findings of the Dumitrescu and Hurlin’s panel causal test disclose that bidirectional causality exists between green investment, globalization, technological innovations, non-renewable energy, and CO2 emissions. This study also recommends some valuable policy suggestions to governments in general and to policymakers specifically which are aimed to endorse environmental sustainability in the MINT countries.

Most countries, notably those that signed the Paris Climate Agreement, prioritize achieving the zero carbon or carbon neutrality aim. Unlike earlier studies, this one assesses the contribution of environmental policy, clean energy, green innovation, and renewable energy to the E7 economies’ achievement of carbon neutrality goals from 1990 to 2019. Findings emanating from the study show that the EKC hypothesis is valid in E7 countries. Implying that emissions in the E7 countries increased with the kick-off of development but declined later due to possible potent environmental regulatory policies put in place. Similarly, across all models, renewable energy (REN), green innovations (GINNO), environmental tax (ETAX), and technological innovations (TECH) were found to exert a negative and significant impact on carbon emissions in the E7 countries both in the short and long run. On the other hand, economic expansion (GDP) positively impacts environmental deterioration. Furthermore, the country-specific result shows that, on average, Brazil, India, China, Russia, Mexico, and Indonesia have significant environmental policies aiding carbon abatement. Except for Brazil, Mexico, and Indonesia, the income growth in the rest of the countries does not follow the EKC proposition. Furthermore, the causality result revealed a unidirectional causal relationship between GDP, REN, and GINNO to CO2 emission. No causality was found between ETAX with CO2, while a bi-directional causality exists between technology and CO2 emissions. Based on the finding, policymakers in the E7 countries should move away from fossil fuels because future electricity output will not be sufficient to reduce emissions considerably. Environmental regulations, encouraging technological innovation, adopting green and sustainable technology, and clean energy sources, among other things, demand radical and broad changes.