(385m) Optimal Strategies of Upcycling Plastic Waste through Superstructure-Based Framework

The increasing environmental issue of disposing of plastic waste is a significant problem all over the world. This study focuses on analysis and evaluation of main solid-to-chemical strategies for upcycling the plastic wastes. First, we propose a technological superstructure that produces value-added chemicals from plastic waste. The rigorous simulation models of main process included in the superstructure were developed to estimate the technical, economic, and environmental parameters within the technological superstructure. Then, the superstructure along with associated parameter is used to develop an optimization model which allow us to identify and assess the optimal strategy of upcycling plastic waste under different objective functions: 1. Maximization of profit, 2. Minimization of cost, 3. Reduction of CO₂ emission, 4. Minimization of CO₂ emission, 5. Energy generation, 6. Energy consumption. The capability of the developed framework was illustrated with the production of chemicals from plastic waste and case studies from different scenarios. Based on the developed framework, we also discussed the trade-off between sorting strategy and non-sorting strategy to identify sorting performance under different scenarios. The results of this study provide applicable decision-making strategies for stakeholders and government policymakers to make decisions related to plastic waste utilization and treatment issues within the circular economy.

One of the most critical global issues is the disposal of increased plastic waste as production of plastic is faster and faster. The existing methods of disposing of plastic waste, such as landfill and incineration, have a negative effect on environment in terms of air pollution and soil contamination. Mechanical recycling is alternative technology for disposing of plastic waste, but this technology has high product yield only in high-density polyethylene (HDPE) and polyethylene terephthalate (PET). This limitation has facilitated the development of new recycling technologies and one of them is chemical upcycling. Various upcycling technologies such as pyrolysis and gasification that use plastic waste as feedstock are promising to dispose of plastic waste. However, most research focuses on the specific unit process or unit technology such as gasification of polypropylene (PP) and pyrolysis of HDPE. To overcome this limitation and to accelerate the application of upcycling technologies in industries, there are needs for evaluation of a number of practical strategies. Accordingly, the objective of this study is to develop a systematic framework for the evaluation of upcycling strategies, which can be used to answer a wide range of questions such as what plastic types would make the upcycling strategy economically viable and what types of conversion routes should be integrated and how. To develop this framework, we first generate a technological superstructure to represent and analyze a system of upcycling plastic waste consisting of various feedstocks and products along with the integration of technologies. In particular, we develop a network optimization model to identify and evaluate the optimal strategy under various objective functions. Then, we estimate the economic, environmental and energy parameters of optimization model with a rigorous process model. Finally, we identify a variety of upcycling and sorting strategies under different objective functions.

Various products such as fuel, olefin, and lubricant are produced through plastic waste depending on what type of process is used. In the technological superstructure of this study, intermediate products are generated starting with plastic waste as a raw material, and finally, a number of products are produced. To develop this superstructure, a unit process of upcycling plastic waste must be connected. We define several feedstocks, compounds, and technologies within this technology superstructure and connect the flow of materials and unit processes to complete the upcycling technology superstructure.

Based on the information on compounds and technologies in the upcycling superstructure, we developed a rigorous simulation model for each process using Aspen Plus. By utilizing the process model, we obtained the main parameters of each process. The main parameters can be classified into three categories: one is a technical parameter such as yield or energy consumption for mass and energy balance, and another one is an economic parameter related to the revenue and cost of the process. The last parameter is environmental data such as CO₂ emission or reduction. The parameters were estimated through streams of each process from the simulation model, and energy consumption was obtained through utilities used in each process. In terms of economic parameters, major parameters such as capital cost and operating cost were calculated by considering the cost and sizing of each equipment.

To present an optimal upcycling strategy using plastic waste, we develop a mixed-integer linear programming (MILP)-based optimization model. In the optimization model, there are various logical and practical constraints to meet the different objective function.

Mass and energy balance: This constraint is used to balance mass and energy flow between involved technologies from the feedstock to the final products.

Technology capacity: This constraint means that the involved technologies is limited by its capacity.

Feedstock availability: The available amount of feed that can enter a particular technology balances the amount of feed that can be accessed.

Logical constraint: In the case an input stream can be processed by various technologies, the number of technologies that can satisfy the objective function is controlled by using binary variables.

We consider various objective functions and one of them is to maximize the net profit by economic aspect. This objective function includes the terms of revenue and cost. Thus, it means that it is important to consider not only the product price but also production cost. Other objective functions that consider the environmental and energy aspect are shown in supplementary figures.

In this study, the optimal strategies for upcycling plastic waste are assessed through six different objective functions. In addition to this, we presented the optimal strategies depending on the type of plastic waste (PET, PP, poly vinyl chloride (PVC), polystyrene (PS), polyethylene (PE), mixed plastic). The composition of mixed plastic is shown in the supplementary figure. The final products of the superstructure include recycled plastics, chemicals (BTX, olefin, and aromatics), and fuels (gasoline, diesel, and lubricant), and each product is defined by carbon range and molecular structure. The availability of the feedstock is 6,250 kg/h, which is adopted from the literature. The price of feedstocks (plastic wastes) is adopted from the market price of plastic flakes which are made from pre-treatment process before feeding the upcycling system. Then, we considered the market price as the price of final products such as H₂, gasoline, diesel, and recycled PET. While the price of feedstock and product fluctuated constantly, acceptable deterministic prices were selected in this study. The utility price of each process is estimated from the utility package of Aspen Plus V12.0 simulator. The optimal strategies and specific result values under different objective functions and different types of plastic waste using the framework are depicted in the supplementary image file. In the case of maximizing net profit, PET and PVC show low economic viability due to its chemical characteristics which means that PET and PVC have oxygen and chloride, respectively. The other case of objective functions, we identified that the strategies and values from different types of plastic waste are various account of its chemical characteristics. Based on the result of each plastic waste type, we evaluate the sorting strategy when the feedstock is mixed plastic. In general, when the capacity of plastic waste increases, the sorting strategy is selected for maximizing the net profit, but when the capacity of waste increases, sorting strategy is not adopted for minimizing CO₂ emissions. The reason for this result is complexity of strategy, which means the number of processes that plastic waste goes through in the strategy. The entire results of sorting strategies are depicted in the supplementary figure.

In conclusion, this study evaluated the strategy of dealing with increment of plastic waste. In particular, to present an optimal strategy, the upcycling superstructure including several compounds such as feeds, intermediate products, and final products was developed. Based on the information of the superstructure, we estimated the technical, economic, and environmental parameters. Using these parameters and superstructure, we developed an optimization model with practical and logical constraints to meet various objective functions. Through case studies with six objectives under six different types of plastic waste, we analyzed each pathway and presented an optimal strategy for chemical production. While the developed framework is helpful in decision-making for the strategy of upcycling plastic waste, further research is needed for different scenarios. For example, the carbon tax, which is the cost of CO₂ emissions, greatly effects selecting the optimal upcycling strategy and sorting strategy.