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China's automobile industry is developing rapidly, but the recycling rate of end-of-life vehicles has been low. In 2018, the recovery rate of end-of-life passenger vehicles was less than 18% of the scrapped amount. Dynamic material flow analysis can predict the amount of end-of-life passenger cars in China in the future, and analyze the flow of materials in recycling system. Life cycle assessment can be used to quantify greenhouse gas emissions. Therefore, this paper integrates these two methods into the model construction of recycling decision system. Meanwhile, sensitivity analysis of the important factors affecting the efficiency of the recovery system is carried out. Finally, the main recovery indexes of the system are predicted under three scenarios: low-speed, medium speed and high-speed development, which are set based on scrap volume, standard recovery rate, proportion of assembly into remanufacturing and carbon tax price. The research results show that in 2018, 656.9 kg/vehicle of iron, 150.2 kg/vehicle of aluminum and 7.9 kg/vehicle of copper are recovered from end-of-life passenger car in China, and the carbon emission during the recovery process is 651.1 kg of CO 2 eq/vehicle, with a total emission reduction of 3816.1 kgCO 2 eq/vehicle compared with the original production, and the economic benefit is about 5055.5 yuan/vehicle. The scenario prediction results show that by 2050, from the low-speed development scenario to the high-speed development scenario, the total amount of iron, aluminum and copper recovered rise from 3.96 million tons, 915 thousand tons and 46 thousand tons to 697 thousand tons, 1.61 million tons and 80 thousand tons respectively throughout the year. The carbon emission in the recovery process rise from 4.98 thousand tons to 9.32 million tons. Compared with the original production, the carbon emission reduction increases from 2.21 million tons to 38.3 million tons, the economic benefit increases from 58.9 billion yuan to 118.8 billion yuan, and the comprehensive benefit increases from 57 billion yuan to 111.6 billion yuan., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

China's paper industry development is rapid, but the recycling rate of China's waste paper has been low all the time. Meanwhile, material flow analysis can help determine the flow of waste paper, and life cycle assessment (LCA) is the methodological framework for quantifying greenhouse gas emissions. Therefore, present study integrates these two methods into the model construction of China's waste paper recycling decision system. Present study constructs a benchmark model of China's waste paper recycling decision system in 2017, focusing on the impact of nonstandard waste paper recycling on the economic and environmental benefits of China's domestic waste paper recycling system. This model construction is followed by sensitivity analysis of the relevant parameters affecting the efficiency of the waste paper recycling system. Finally, present study forecasts the system's economic benefits and greenhouse gas (GHG) emissions in the context of integrating and regulating nonstandard recycling vendors. The results show that the economic benefit of China's waste paper recycling in 2017 is approximately 458.3 yuan/t and that the GHG emissions are 901.1 kgCO 2 eq. The standard recovery rate and nonstandard recovery acceptance rate will both have a significant impact on the system's economic benefits and improve the GHG emissions structure. In the context of integrating nonstandard recycling enterprises and individual recycling vendors, the economic benefits will rise to 3312.5 yuan/t in 2030, while GHG emissions will rise to 942.9 kgCO 2 eq. Present study can play a certain guiding role for policy makers in formulating waste paper recycling industry specifications and formulating relevant policies., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Globally, the transportation industry is one of the leading fields that generate the largest share of greenhouse gas emissions. While undergoing rapid development, countries worldwide aim to solve the problems involved in high energy consumption. Taking China as an example, this paper studies the main factors of carbon emissions in the transport sector and analyses the decoupling states between carbon emission and economic growth, making energy efficiency policies accordingly. In order to better demonstrate the dependence of the economy on the carbon emissions in China's transportation industry comprehensively, combined with the C D production function, this paper develops the decomposition and decoupling technology based on the LMDI approach. Additionally, it quantifies seven effects: energy emission intensity effect, energy structure effect, energy intensity effect, transportation intensity effect, technology state effect, labor input effect and capital input effect. The results show three major points: (1) From 2001 to 2018, the cumulative carbon emissions of China's transportation industry increased by 633.46 million tons, in which the capital input effect is the key factor driving carbon emissions, accounting for 157.70% of the total cumulative increased emissions, followed by energy structure effect at 10.39%. The labor input effect accounted for the smallest proportion at 2.26%. In this case, the technology state effect is the primary factor in restraining carbon emissions. During the study period, it reduced carbon emissions by 292.27 million tons, accounting for 46.14%. To a certain extent, energy intensity effect, transportation intensity effect and energy emission intensity inhibited carbon emissions, representing 16.67%, 5.32% and 2.22%, respectively. (2) During the research period, two decoupling states existed between carbon emissions and economic growth in China's transportation industry, specifically weak decoupling and expansive coupling. (3) The analysis of decomposition and decoupling state of influencing factors of carbon emissions shows that, on the one hand, factors promoting carbon emissions (capital input effect, energy structure effect and labor input effect) hinder the decoupling process. On the other hand, factors restraining carbon emissions (technology state effect, transportation intensity effect, energy intensity effect and energy emission intensity effect) accelerate the decoupling process. The research findings provide a new perspective for achieving carbon emission reduction in the transportation industry and curbing energy consumption growth. [Display omitted] • Develop the carbon emissions decomposition framework in transportation industry. • The framework is composed of LMDI decomposition model and C-D production function. • Fixed asset investment is the main factor influencing carbon emissions in China. • Optimizing capital use and labor efficiency are the keys to reduce carbon emissions [ABSTRACT FROM AUTHOR]