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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]

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. • Present study constructs the life cycle framework of Chinese paper and paperboard by the combination of MFA and LCA. • Quantitative analysis of the economic benefits and GHG emissions generated by China's waste paper recycling system. • Sensitivity analysis on the main parameters of the economic and environmental benefits of the waste paper recycling system. • Benefits of China's waste paper recycling from 2018 to 2030 are evaluated by integrating nostandard and standard recycling. [ABSTRACT FROM AUTHOR]