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• Dynamic material flow and life cycle assessment for recovery system is constructed. • Economic benefit and CO 2 emission of recovery system are analyzed quantitatively. • The sensitivity analysis of three main factors affecting the system is carried out. • The peak volume will reach to 16 million by using dynamic material flow analysis. • The recovery benefits are predicted under scenarios of low, mid and high speed. 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. [ABSTRACT FROM AUTHOR]

To study the key drivers of China's carbon dioxide emissions, this study combines the structural decomposition analysis method and the input-output subsystem analysis method to construct a decomposition model of the factors influencing the amount of change of the carbon dioxide emissions in China. From the perspective of final demand, this decomposition model (own internal component, feed-back component, spillover component, scale component) is used to analyze the amount of change of China's carbon dioxide emissions in the two periods of 2012–2017 and 2017–2018. Four scenarios are set up to predict the carbon dioxide emissions of China before 2035. The results show that in 2012, 2017 and 2018, the carbon dioxide emissions generated by final demand were respectively 9,018,810, 8,715,226, and 8,803,201 kt, of which the spillover component accounted for the largest share, namely 85.5%, 85.6% and 84.7% respectively. This indicates that the increase of carbon dioxide emissions in China is due to intersectoral pulling effects, and the activities of the Construction sector have had pulling effects on the carbon dioxide emissions of other sectors to a greater extent. The energy intensity effect is the significant influencing factor that inhibits carbon dioxide emissions and economic development is the main driver of the increase in carbon dioxide emissions; this implies that changing the current energy structure is necessary to reduce carbon dioxide emissions. The technical progress scenario (QN) and the energy structure optimization scenario (GN) are predicted to achieve the carbon peak in 2025 and 2030, respectively. [Display omitted] • Total carbon emissions generated by final demand are decomposed into four subsystems, with a structural decomposition. • The spillover components account for the largest proportion of carbon emissions. • Construction industry has pulled the carbon emissions of other sectors to a greater extent. • Under GN and QG scenarios, it is expected to achieve carbon peak in 2025 and 2030 respectively. • Technical improvements are effective in most sectors. [ABSTRACT FROM AUTHOR]

Recycling medical plastic waste has the potential to significantly reduce environmental pollution while also providing significant economic benefits. This study develops a benchmark model for the benefit evaluation of China's medical plastic waste recycling decision system in 2019, focusing on the recovery system's benefits and costs. Following model construction, a sensitivity analysis is conducted on the relevant parameters affecting the recycling system's efficiency. Finally, the system's primary recovery indexes are predicted for three development scenarios based on the results of sensitivity analysis: low-speed, medium-speed, and high-speed development. The results indicate that each ton of medical plastic waste generates an economic benefit of 2708.6 yuan in 2019, 187.8 μg TEQ of dioxin during incineration, and 1.48 tons of carbon dioxide during the recovery process. The total emission reduction is approximately 0.76 tons when compared to the initial production. If the illegal recovery rate is reduced by 0.5% and the mixed disposal rate is reduced by 5%, the comprehensive benefits increase by approximately 15.3% and 2.2%, respectively. The results of the scenario simulations indicate that the recovery benefit and potential for emission reduction associated with each ton of medical plastic waste increase year after year, while carbon dioxide emissions exhibit an inverted "U" shape evolution. [Display omitted] • Material flow analysis and LCA for medical plastic recycling system is constructed. • Benefits and losses of the recycling system are analyzed quantitatively. • The sensitivity analysis of three main factors affecting the system is carried out. • The recovery benefits are predicted under scenarios of low, mid and high speed. • Recycling makes the safe disposal of medical waste and brings considerable benefits. [ABSTRACT FROM AUTHOR]

Tackling coal-burning industrial boiler is becoming one of the key programs to solve the environmental problem in China. Assessing the economics of various options to address coal-fired boiler is essential to identify cost-effective solutions. This paper discusses our work in conducting a cost-effectiveness analysis on various types of improvement measures ranging from energy efficiency retrofits to switch from coal to other fuels in China. Sensitivity analysis was also performed in order to understand the impacts of some economic factors such as discount rate and energy price on the economics of boiler improvement options. The results show that nine out of 14 solutions are cost-effective, and a lower discount rate and higher energy price will result in more energy efficiency measures being cost-effective. Both monetary and non-monetary barriers to energy-efficiency improvement are discussed and policies to tackle these barriers are recommended. Our research aims at providing a methodology to assess cost-effective solutions to boiler problems. [ABSTRACT FROM AUTHOR]

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]

• Household indirect energy consumption is decomposed by input-output subsystem method. • Indirect consumption is 1.3 and 1.65 times of direct in 2012 and 2017 respectively. • Coal indirect consumption accounts for 50.2%, 54.6% in 2012 and 2017 respectively. • Spillover effect is the most one among the four components. • Ferrous metal smelting and rolling sector is most affected by household activities. In recent years, China's rapid economic development and steady growth of household consumption have contributed to the continuous growth of energy consumption. In addition to considering direct household energy consumption, the indirect effects of people's consumption activities on energy consumption in other productive sectors can't be ignored. According to the input-output analysis framework and consumer lifestyle analysis, this paper mainly studies the direct and indirect consumption of energy by Chinese household consumption ways and the relationship between energy structure and lifestyle. From the perspective of structural analysis, the input-output subsystem model (scale component, own internal component, feed-back component and spillover component) is used to analyze the energy supply and demand relations among 36 sectors of the national economy related to the lives of household in 2012 and 2017, revealing the change trend and transmission mechanism. This paper also focuses on the impact of household consumption ways on energy consumption of industrial sector and changing consumer lifestyles on energy saving, meanwhile it also forecasts China's future household energy consumption under four scenarios. The results show that in 2012 and 2017, total consumption of energy which is influenced by household consumption ways in China is 28461.82 PJ and 44759.96 PJ, respectively, accounting for 26.9% and 34.1% of total consumption of final energy. The indirect energy consumption is 1.3 times and 1.65 times of direct, respectively. The coal consumption accounts for the majority of indirect energy consumption. The smelting and pressing of ferrous metals is the industrial sector which is most affected by the household consumption ways. The scale component, own internal component, feed-back component and spillover component has accounted for 18.5%, 1.3%, 0.1% and 80.0%, from 17.5%, 2.0%, 0.2% and 80.3% of energy consumption in total, respectively. Under the four scenario development modes (NN, NA, LN and LA), it is predicted that the indirect energy consumption in household life in 2025 is 43740.56PJ, 34922.93PJ, 39149.37PJ and 31257.28PJ, respectively. The implementation of low-carbon consumption mode and the accelerated decline of energy intensity will help to reduce energy consumption. [ABSTRACT FROM AUTHOR]

Tackling coal-burning industrial boilers is one of the key solutions to meeting the climate change and solving the environmental problem in China. Assessing the economics of various options to address coal-fired boilers is essential to identify cost-effective solutions. This paper discusses our work in conducting a comprehensive techno-economic analysis to evaluate various strategies for improving efficiency and maximize fuel-switching of industrial boilers. The analysis focused on three options: (1) fuel switching to replace coal with alternative fuels for small size of boilers; (2) retrofitting boilers through a series of efficiency improvement measures; (3) developing community-scale, distributed systems to replace otherwise scattered boilers operated by individual industrial facilities. Key barriers that prevent these solutions from being fully captured are discussed and policy recommendations to tackle these barriers are provided. [ABSTRACT FROM AUTHOR]

The global warming problem caused by carbon emissions from transportation has caused widespread concern, and the choice of private vehicle type directly affects the carbon emissions of individuals' travel. Therefore, replacing internal combustion vehicles with battery electric vehicles turns out to be an important measure to solve traffic-related pollution. Battery electric vehicles are high-intervention environmentally friendly products. In addition to considering their functional benefits, consumers will also value the symbolic meaning of electric vehicles, which could be an effective expression of their identities. This study explored the factors of the electric vehicle adoption intention from the perspective of the symbolic meaning, and explored the boundary conditions of symbolic meaning's effects on adoption intention from the perspective of consumer self-identity and traditional cultural value (face consciousness). The conclusions of this paper are as follows: (1) The status symbol, environmentalism symbol, and innovation symbol of electric vehicles have significant positive impacts on the adoption intention of consumers. Compared to status symbol, environmentalism symbol and innovation symbol have stronger influences; (2) The influence of the environmentalism symbol on adoption intention is positively moderated by environmentalist self-identity; (3) The influence of the innovation symbol on adoption intention is positively moderated by innovator self-identity; (4) The influence of the innovation symbol on the adoption intention is positively moderated by face consciousness. This research provides a theoretical support for electric vehicle companies to develop promotion strategies and target customers, and can effectively promote the popularity of electric vehicles. Image 1 • Chinese consumers' perception of different symbolic meanings of electric vehicles and their adoption intention were comprehensively investigated. • The status, environmentalism, and innovation symbol of electric vehicles have positive impacts on consumers' adoption intention. • Consumer self-identity plays a moderating role in the influence of symbolic meanings on adoption intention. • The influence of the innovation symbol on the adoption intention is moderated by face consciousness. [ABSTRACT FROM AUTHOR]