Waste paper recycling decision system based on material flow analysis and life cycle assessment: A case study of waste paper recycling from China.

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 kgCO2eq. 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 kgCO2eq. Present study can play a certain guiding role for policy makers in formulating waste paper recycling industry specifications and formulating relevant policies.

A decision-support system for recycling of residents' waste plastics in China based on material flow analysis and life cycle assessment.

Recycling waste plastics is one of the important ways to save petroleum resources and reduce carbon emissions. However, the current recycling rate of waste plastics is still low. Material flow analysis can help determine the flow of waste plastics, and life cycle assessment (LCA) can be used to quantify environmental impacts. The present study integrates these two methods into the model construction of the residents' waste plastics recycling decision-support system. This model construction is followed by sensitivity analysis of the relevant parameters affecting the performance of the waste plastics recycling system. Finally, the present study forecasts the recycling system's performance and environmental impacts by setting four optimization scenarios based on sensitivity analysis. The results show that in 2019, a total of 8.39 million tons of high-end applications were recovered, carbon emissions during the recycling process were 34.9 million tons, and dioxin emissions were 316.11 g TEQ, with a total emission reduction of 24.47 million tons of CO2 compared to the original production. Sensitivity analysis shows that the selection rate of waste plastic recycling, the re-sorting rate of waste plastic recycling plant, and the classification recovery rate of mixed waste had relatively high effects on the recovery performance and environmental benefits of the recycling system. In the scenario of comprehensive improvement, in 2035, the recycling volume of high-end applications will rise to 33.96 million tons, the carbon emissions will rise to 64.73 million tons, the dioxin emissions will drop to 165.98 g TEQ, and the carbon emission reduction will rise to 99.06 million tons. This study has a certain guiding role for policy-makers to formulate industry norms and related policies for waste plastic recycling.

Carbon emission structure decomposition analysis of manufacturing industry from the perspective of input-output subsystem: a case study of China.

In China, manufacturing is the industry that consumes the most energy and emits the most carbon, and the effect of emission reduction on the process of reaching carbon peaking and carbon neutrality is decisive. The existing research on the driving factors of manufacturing carbon emissions has not analyzed the specific structural characteristics of manufacturing carbon emissions from the perspective of industrial relevance, and little attention has been paid to the discussion of carbon emission reduction paths of different manufacturing sectors from the perspective of final demand. This study examines the direct carbon emissions and carbon emissions from final demand in China's manufacturing sector, and decomposes the carbon emissions from final demand into six distinct components using input-output analysis. In addition, this study examines the carbon emission path in manufacturing production activities, as well as the carbon emission reduction potential and scenario prediction of the factors influencing manufacturing carbon emissions. In 2018, the direct carbon emissions and carbon emissions from final demand were approximately 4.61 billion tons and 3.50 billion tons, respectively. Meanwhile, direct and indirect spillovers accounted for 62.1% and 23.1% of carbon emissions from final demand, respectively. Using the carbon emission transfer route map of the manufacturing industry, the direction and amount of carbon emission transfer from various energy sources can be accurately determined. The CR scenario predicts that the manufacturing industry will reach its carbon peak between 2025 and 2030, with a corresponding peak between 4.02 and 4.06 billion tons, and that carbon emissions in 2060 will be 40% lower than in 2018.

Enabling a Rapid and Just Transition away from Coal in China.

As the world's largest coal producer and consumer, China's transition from coal to cleaner energy sources is critical for achieving global decarbonization. Increasing regulations on air pollution and carbon emissions and decreasing costs of renewables drive China's transition away from coal; however, this transition also has implications for employment and social justice. Here, we assess China's current coal-transition policies, their barriers, and the potential for an accelerated transition, as well as the associated environmental, human health, and employment and social justice issues that may arise from the transition. We estimate that the most aggressive coal-transition pathway could reduce annual premature death related to coal combustion by 224,000 and reduce annual water consumption by 4.3 billion m3 in 2050 compared with business-as-usual. We highlight knowledge gaps and conclude with policy recommendations for an integrated approach to facilitate a rapid and just transition away from coal in China.

End-of-life passenger vehicles recycling decision system in China based on dynamic material flow analysis and life cycle assessment.

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 CO2eq/vehicle, with a total emission reduction of 3816.1 kgCO2eq/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.