Energy use, greenhouse gases emission and cost effectiveness of an integrated high– and low–temperature Fisher–Tropsch synthesis plant from a lifecycle viewpoint

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.

Estimating the Macroeconomic Costs of CO2 Emission Reduction in China Based on Multi-objective Programming

Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets

The power industry is a major contributor to CO2 emissions in China and thus plays a critical role in achieving the targets of CO2 emission reduction. This study analyzes the historical trajectory and feature of CO2 emissions in China’s power industry, explores the driving factors of CO2 emission change using LMDI method, and develops two emission reduction scenarios to evaluate the reduction potential of CO2 emissions. Results show the following: (1) China’s power industry has experienced a significant but unstable increase in CO2 emissions from 343.18 Mt in 1985 to 3447.57 Mt in 2013, a growth rate of 904.60%. (2) Industrial-scale effect plays a dominant role in promoting CO2 emission growth in China’s power industry, and the corresponding contribution degree reaches 111.73%. Energy intensity effect contributes most to the decrease in CO2 emissions, with a contribution degree of −16.82%. Capital productivity effect is another important factor leading to the increase in CO2 emissions. (3) The aggregate CO2 emission reduction in China’s power industry would reach 18,031.62 Mt in the ideal scenario and 15,466.03 Mt in the current policy scenario during 2014–2030. Finally, this study provides policy implications for energy-saving and CO2 emission reduction in China’s power industry.

The logistics industry is one of the major fossil energy consumers and CO2 emitters in China, which plays an important role in achieving sustainable development as well as China’s emission reduction targets. To identify the key influencing factors regarding the logistics of CO2 reductions and ensure that the development of China’s logistics industry becomes less dependent on CO2 emissions, this paper built an extended log-mean Divisia index model (LMDI) to decompose the logistics of CO2 changes between 1985 and 2015. Then, we introduced a decoupling model that combined the decomposition results to analyze the decoupling state and identify the main factors that influenced the decoupling relationship. The results show the following. (1) The urbanization effect was the decisive factor in CO2 emissions increases, followed by structural adjustment effects, while technological progress effects played a major role in inhibiting CO2 emissions. Particularly, the energy structure showed great potential for CO2 emissions reduction in China. (2) Highways appeared to have dominant promoting roles in increasing CO2 emissions regarding transportation structure effects; highways and aviation proved to have the largest impact on CO2 emission reduction. (3) There has been an increase in the number of expansive negative decoupling states between 2005 and 2015, which implies that the development of the logistics industry has become more dependent on CO2 emissions. Finally, this paper puts forward some policy implications for CO2 emission reductions in China’s logistics industry.

The current paper combines multi-regional input-output model and linear programming model to identify industrial shift strategies for CO2 emissions reduction in China. As a supplement to the previous studies, the optimal sequence of demand regulation for various products is explored. The results show that demand side regulation would pose negative effect on both GDP and CO2 emissions. However, certain strategies can be adopted to decrease CO2 emissions at the minimum decrease in GDP. According to the optimal sequence analysis, a group of key final products, such as the metallurgy products, the nonmetal products, the metal products, and the chemical products should be firstly regulated. Most of these key products concentrate in the eastern and coastal regions in China. Our model can be used to aid policy makers in design of effective industrial restructuring policy to achieve the national emissions targets.

Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector

Cost of energy saving and CO2 emissions reduction in China’s iron and steel sector

An overview is given of the Fischer–Tropsch based conversion of carbon containing feed materials (coal, biomass, natural gas and waste) into useful products (fuels and chemicals). A high-level process flow diagram is provided showing the different conversion steps, namely feed preparation, feed-to-syngas conversion, syngas conditioning, Fischer–Tropsch synthesis, syncrude cooling/separation and refining. The composition of Fischer–Tropsch derived syncrude is discussed, while listing syncrude compositions representative of the three major technologies, iron-based low and high temperature Fischer–Tropsch synthesis, as well as cobalt-based low temperature Fischer–Tropsch synthesis. This serves as introduction to the refining of syncrude and the catalysis relevant to Fischer–Tropsch syncrude refining. The need for refining, the difference between syncrude and conventional crude oil and the special requirements for catalysis when dealing with syncrude are highlighted.

Power sector is significantly important for China to achieve the CO2 emission reduction targets. In this study, we analyze the features of CO2 emissions and environment effect in China’s power sector, investigate the driving factors of CO2 emission change based on the logarithmic mean Divisia index (LMDI) method, and evaluate the mitigation potential of CO2 emissions in China’s power sector. Results show that CO2 emissions in China’s power sector increased rapidly from 492.00 Mt in 1990 to 3049.88 Mt in 2014 while CO2 emission intensity experienced an unsteady downward trend during the study period. Industrial scale effect is the key contributor to CO2 emission growth in China’s power sector, and its contribution degree reaches 123.97%. Energy intensity effect contributes most to the decrease in CO2 emissions, with a contribution degree of −20.01%. Capital productivity effect is another important factor leading to CO2 emissions increase. The aggregate CO2 emission reduction would reach 17973.86 million tons (Mt) during 2015–2030 in the ideal emission reduction scenario. Finally, policy recommendations are made for future energy-saving and CO2 emission reduction in China’s power sector.

Guangdong, a developed province of China, attaches great importance to CO2 emissions in transport these years, especially in road transport. To explore the way to achieve CO2 emission peak of road transport in such a typical province, multiple scenarios were designed, including a baseline scenario, four single mitigation scenarios, and three combined mitigation scenarios. The peaking regularity and scale of provincial CO2 emissions and mitigation potential until 2035 were quantitatively evaluated. The assessment results showed that CO2 emissions kept rapid growth without control and reached 315.4 Mt in 2035. The peak of CO2 emission by 2030 could not be addressed by single mitigation measures. But combination of four single mitigation scenarios could drive CO2 emissions to peak in 2030 at the level of 171.3 Mt. The peak appeared later at higher level of CO2 emissions compared with UK (30.5%) and Australian (45.6%). Therefore, the CO2 emissions from road transport in such a developed province should be constrained in the future. A strong policy combination to constrain provincial CO2 emissions is necessary for sharing the target of CO2 emission reduction in China.

Factors affecting CO2 emissions in China's agriculture sector: A quantile regression

Exploring hydrogen metallurgy to CO2 emissions reduction in China’s iron and steel production: An analysis based on the life cycle CO2 emissions – LEAP model

An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector

China is facing increasing pressure to reduce CO2 emissions from energy consumption. Given this issue, understanding the characteristics, influencing factors, and trends can provide adequate information for decision-makers to solve the CO2 emission problem. This study analyzes the characteristics of CO2 emissions from energy consumption in 30 regions of China from 2005 to 2018 and applies the STIRPAT model to identify the impact of the influencing factors. Combined with the CO2 emission trend in 2030 as predicted by the ARIMA model, the key mitigation regions and strategies reduction have been determined. Results indicate that CO2 emissions have been increasing from 2005 to 2018 in China, thus showing the characteristic of the east being larger than the west spatially. Under the baseline scenario, these emissions will continue to rise in 2030. Carbon emissions intensity is declining, and the gap between provinces with the highest and lowest per capita CO2 emissions is widening. Although per capita GDP is significantly positively correlated with provinces, population is the key factor influencing more provinces, followed by the proportion of the secondary industry and urbanization rate. To achieve low-carbon sustainable development, Shandong, Shanxi, Inner Mongolia, Guangdong, Shaanxi, Xinjiang, and Ningxia are considered the key regions of concern for emission reduction. The heterogeneity of CO2 emission characteristics and influencing factors among regions provides a direction for the development of targeted and differentiated regional emission reduction strategies.