A Study on Decoupling of Carbon Emissions from Beijing-Tianjin-Hebei Transport Industry

Recent measures of carbon dioxide emissions from the steel industry of China have indicated a high rate of total CO2 emissions from the industry, even compared to the rest of the world. So, CO2 emission reduction in China’s steel industry was analyzed, coupling the whole process and scenarios analysis. First, assuming that all available advanced technologies are almost adopted, this study puts forward some key potential-sectors and explores an optimal technical route for reducing CO2 emissions from the Chinese steel industry based on whole process analysis. The results show that in the stages of coking, sintering, and iron making, greater potential for reducing emissions would be fulfilled by taking some technological measures. If only would above well-developed technologies be fulfill, the CO2 emissions from 5 industry production stages would be reduced substantially, and CO2 emissions per ton of steel could be decreased to 1.24 (ton/ton-steel) by 2020. At the same time, the scenarios analysis indicates that if mature carbon-reducing technologies are adopted, and if the difference between steel output growth rate and the GDP growth rate could be controlled below 3%, CO2 emissions from China’s steel industry would approach the goal of reducing CO2 emissions per GDP unit by 40%–45% of the 2005 level by 2020. This indicates that the focus of carbon dioxide emissions reduction in China lies in policy adjustments in order to enhance technological application, and lies in reasonably controlling the pace of growth of GDP and steel output.

As the second largest CO2 emission department, transportation industry's carbon peak and carbon reduction are very important for China to smoothly achieve carbon peak by 2030 and carbon neutrality by 2060. This paper analyzes the influencing factors from the perspectives of population, economy, technology and transportation equipment structure, subdivides 20 scenarios to predict the carbon emissions of the transportation industry of the whole China and various regions based on scenario analysis method, explores the carbon peak path, and puts forward corresponding policy recommendations. The study found that (1) from the overall trend of carbon emissions, the total carbon emissions of China's transportation industry showed an overall upward trend from 2010 to 2019 while the growth rate of carbon emissions showed a downward trend. (2) From the perspective of influencing factors, population size, urbanization rate, economic scale, traffic development, traffic carbon intensity, and highway mileage have positive effect on the growth rate of China's transportation CO2 emissions. The increase in the proportion of energy structure and railway cargo turnover has the negative effect on carbon emissions in the transportation industry. (3) From the prediction results at the national level, technological breakthroughs have a limited effect on carbon emission reduction in China's transportation industry, while structural equipment optimization has the most significant effect on its emission reduction. When technological breakthroughs and equipment structure optimization are carried out simultaneously, the carbon emission reduction effect is the best. The carbon peak of China's transportation industry would achieve as early as 2030, with a peak range of 70,355.54-84,136.17 million tons. (4) From the perspective of prediction results at the regional level, the provinces with rapid population growth and per capita GDP growth, the provinces with rapid population growth and per capita GDP growth, and the provinces with low population growth and per capita GDP growth should control their average annual growth rate of carbon emissions of the transportation industry to 1.13%, 0.72% and 0.58% respectively in 2019-2030, in order to ensure the achievements of the carbon peak target.

Emission reduction of China׳s steel industry: Progress and challenges

Carbon Emissions and Economic Development in Transport Industry - An Empirical Research Based on Decoupling Theory and Structure Decomposition Model

Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model

Cities play a major role in decoupling economic growth from carbon emission for their significant role in climate change mitigation from national level. This paper selects Beijing (economic center and leader of emission reduction in China) as a case to examine the decoupling process during the period 2000–2015 through a sectoral decomposition analysis. This paper proposes the decoupling of carbon emission from economic growth or sectoral output by defining the Tapio decoupling elasticity, and combined the decoupling elasticity with decomposition technique such as Logarithmic Mean Divisia Index approach. The results indicate that agriculture and industrial sectors presented strong decoupling state, and weak decoupling is detected in construction and other industrial sectors. Meanwhile, transport sector is in expansive negative decoupling while trade industry shows expansive coupling during the study period. Per-capita gross domestic product, industrial structure, and energy intensity are the most significant effects influencing the decoupling process. Agriculture and industry are conducive to decoupling of carbon emissions from economic output, while transport and trade are detrimental to the realization of strong decoupling target between 2000 and 2015. However, construction and other industrial sectors exerted relatively little minor impact on the whole decoupling process. Improving and promoting energy-saving technologies in transport sector and trade sector should be the key strategy adjustments for Beijing to reduce carbon emissions in the future. The study aims to provide effective policy adjustments for policy makers to accelerate the decoupling process in Beijing, which, furthermore, can lay a theoretical foundation for other cities to develop carbon emission mitigation polices more efficiently.

This paper discusses energy conservation and emissions reduction (ECER) in China’s power sector. To better understand China’s successes and failures on energy conservation in the electricity industry, first it is important to know the status of China’s power sector, and the key energy conservation actions, as well as the achievements in the past years. Second, two ECER scenarios are constructed to probe the 2020 energy conservation potential. Results show that the potential is estimated to be more than 240 million tons of coal equivalent (Mtce). Third, the improvement of coal power operations, structures and technologies, and ambitious deployment of energy conservation measures are proposed to fully explore the potential of China’s power industry. Fourth, great challenges for China’s ECER and some suggested policies are summed up. The lessons learnt from China will provide a valuable reference and useful inputs for other emerging economies.

Integration of tradable green certificates trading and carbon emissions trading: How will Chinese power industry do?

PurposeThis study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.Design/methodology/approachThis study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.FindingsPower technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.Research limitations/implicationsThis study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.Practical implicationsThis study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.Social implicationsRelevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.Originality/valueThis study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

As a major province of energy consumption and carbon emission, Jiangsu Province is also a major province of the construction industry, which is a key region and potential area for carbon emission reduction in China. The research and prediction of carbon emission in the construction industry is of great significance for the development of low-carbon policies in the construction industry of other cities. The purpose of this paper is to study the influencing factors of the whole life cycle carbon emissions of buildings in Jiangsu Province, and to predict the carbon emissions of buildings in Jiangsu Province based on the main influencing factors. This paper uses the energy balance sheet splitting method, STIRPAT model, gray correlation method and GA-BP neural network model to study and predict the carbon emissions of construction industry in Jiangsu Province. The research results show that the resident population, urbanization rate, steel production, average distance of road transportation, and labor productivity of construction enterprises have a catalytic effect on construction carbon emissions; GDP per capita and added value of tertiary industry have a suppressive effect; construction carbon emissions reached the historical peak in 2012; the prediction results show that the future construction carbon emissions in Jiangsu province generally show a decreasing trend. The research results of this paper provide a possibility to refine the study of construction carbon emission, and also provide a basis and guidance for subsequent research on construction carbon emission.

The decoupling of carbon emissions has also become the dependence of countries’ development. Finance plays an important role in decoupling economic development from carbon emissions. This paper explores the impact of financial development in different regions on the decoupling of carbon emissions from economic growth, using the Tapio decoupling elastic model and the method of fully modified least squares (FMOLS) to study the impact of financial development on carbon emissions in six regional panels from 1995 to 2020: and Foreign direct investment (FDI), urbanization, population, and infrastructure as control variables. The results turn out that financial development will promote the decoupling of carbon emissions from economic growth in the ECA region. For EAP, SSA, AC, SA, and MENA regions, financial development will promote the growth of carbon emissions, and due to the different economic development dynamics of different countries, the positive effects of financial development on carbon emissions are heterogeneous. The impact of FDI, urbanization, and infrastructure on carbon emissions varies from region to region. The population will promote the growth of carbon emissions, regardless of the region. In addition, the ECA region is the most countries that has achieved the strong decoupling and is the first to realize the transition from weak decoupling to strong decoupling. Therefore,the ECA, EAP and AC region should accelerate the construction of a green financial system to promote the decoupling of economic growth and carbon emissions. The SSA, SA and MENA region should speed up the transformation of economic development mode and move towards weak decoupling or even strong decoupling.

Can renewable energy portfolio standards and carbon tax policies promote carbon emission reduction in China's power industry?

As a new type of economy, the digital economy has become an important driver of economic changes and the direction of future economic development, as well as an important way to reduce carbon emissions in the logistics industry. Promoting carbon emissions reduction in the logistics industry with the digital economy has great practical significance. This paper analyzes the mechanism through which the digital economy impacts carbon emissions of the logistics industry, and then, based on provincial panel data from 2005 to 2019 in China, a nonlinear regression model and a quantile regression model are used to empirically test the digital economy’s impact on the carbon emissions of the logistics industry. The results show that there is a U-shaped correlation between the digital economy and carbon emissions of China’s logistics industry, and it is in the first half of the U-shaped correlation. The development of the digital economy has both a significant inhibitory and evolutionary effect on the carbon emissions of the logistics industry. With the increase in quantiles, the marginal impact of digital economy development on carbon emission reduction in China’s logistics industry decreases.

Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach

Distorted energy prices cause resource mismatch and hinder the coordinated development of economic growth and carbon emission reduction (CDEC) in China. Therefore, it is essential to determine the optimal levels of energy price distortions. This paper first measures the price distortions of fossil and renewable energy sources and applies a panel smooth transition regression model to assess the optimal threshold values for the degree of energy price distortions. The results show that 1) Fossil energy price distortions are negative, and the price distortion for renewable energy is positive. 2) Energy price distortions inhibit CDEC, and this effect is regionally heterogeneous. 3) The panel smooth transformation model results indicate that distorted energy prices have a nonlinear impact on CDEC. CDEC is significantly hampered in the low regime by distorted fossil energy prices and facilitated in the high regime. In contrast, the distorted renewable energy price shows positive in the low regime and negative in the high regime. We also obtain the optimal intervals for the degree of energy price distortions that promote CDEC. With the target of “growth” and “carbon reduction,” this study provides a reference for improving the energy pricing mechanism and exploring the effective ways of CDEC.