Oil yield optimization from co-pyrolysis of low-density polyethylene (LDPE), polystyrene (PS) and polyethylene terephthalate (PET) using simplex lattice mixture design

Odejobi, Oludare Johnson; Oladunni, Atilade A.; Sonibare, Jacob Ademola; Abegunrin, I.O.

doi:10.1016/j.jfueco.2020.100006

Cited by 9 publications

(4 citation statements)

References 37 publications

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“…In addition to PVC, oil yields obtained from pyrolysis of PET are generally less than those obtained from HDPE, LDPE, PS, and PP. 56,57 Consistent with this expectation, the XGBoost model predicts that pyrolysis of pure PET at 500 °C results in 28% oil yield much less than that predicted for PP, PS, or HDPE at the same conditions (74, 70, and 63%, respectively, as seen in Supplementary Information Figure SI.3). Similarly, whereas HDPE, LDPE, PS, and PP are all hydrocarbon plastics that yield oils with properties similar to hydrocarbon fuels, PET is an oxygenate that yields small oxygenated compounds, especially ethylene groups and benzoic acid, 58 that are more suitable for use as monomers than as fuels.…”

Section: Resultsmentioning

confidence: 54%

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis

et al. 2022

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Chemical recycling via thermal processes such as pyrolysis is a potentially viable way to convert mixed streams of waste plastics into usable fuels and chemicals. Unfortunately, experimentally measuring product yields for real waste streams can be time- and cost-prohibitive, and the yields are very sensitive to feed composition, especially for certain types of plastics like poly(ethylene terephthalate) (PET) and polyvinyl chloride (PVC). Models capable of predicting yields and conversion from feed composition and reaction conditions have potential as tools to prioritize resources to the most promising plastic streams and to evaluate potential preseparation strategies to improve yields. In this study, a data set consisting of 325 data points for pyrolysis of plastic feeds was collected from the open literature. The data set was divided into training and test sub data sets; the training data were used to optimize the seven different machine learning regression methods, and the testing data were used to evaluate the accuracy of the resulting models. Of the seven types of models, eXtreme Gradient Boosting (XGBoost) predicted the oil yield of the test set with the highest accuracy, corresponding to a mean absolute error (MAE) value of 9.1%. The optimized XGBoost model was then used to predict the oil yields from real waste compositions found in Municipal Recycling Facilities (MRFs) and the Rhine River. The dependence of oil yields on composition was evaluated, and strategies for removing PET and PVC were assessed as examples of how to use the model. Thermodynamic analysis of a pyrolysis system capable of achieving oil yields predicted using the machine-learned model showed that pyrolysis of Rhine River plastics should be net exergy producing under most reasonable conditions.

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Section: Resultsmentioning

confidence: 54%

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis

et al. 2022

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“…Pyrolysis is the most efficient way to recycle plastic since the energy may be used directly. Pyrolysis reduces waste volume by 90%, produces solid, liquid, and gaseous fuels, and has the least environmental impact of any thermal waste degradation process 20 .…”

Section: Methodsmentioning

confidence: 99%

An analysis of environment effect on ethanol blends with plastic fuel and blend optimization using a full factorial design

Padmanabhan

Kumar

Giridharan³

et al. 2022

Sci Rep

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There is a growing amount of plastic waste that needs to be properly disposed of in order to protect the environment from the negative effects of increasing reliance on plastic products. Recent interest has focused on chemical recycling as a means of reducing plastic's negative environmental effects. Converting waste plastics into basic petrochemicals allows them to serve as hydrocarbon feedstock or fuel oil through pyrolysis operations. Scientists have taken a keen interest in the production of bioethanol from renewable feedstocks due to its potential as a source of energy and alternative fuel. Due to its beneficial effects on the environment, ethanol has emerged as a promising biofuel. In this paper, energy recovered from low-density polyethylene and high-density polyethylene waste was converted into an alternative plastic fuel and evaluated for its environmental impact with the blending of ethanol in a diesel engine. Ternary fuel blends with 20%, 30%, and 40% waste plastic fuel and 10%, 15%, and 20% ethanol with standard diesel were tested. The study found that blending 10% ethanol with 20% plastic fuel decreased fuel consumption by around 7.9% compared to base diesel. Carbon monoxide emissions are reduced by about 10.2%, and hydrocarbon emissions are reduced by about 13.43% when using the same ternary blend. The optimum values of fuel consumption and emissions were obtained by full factorial design for a ternary fuel blend of 10% ethanol and 20% plastic fuel at the full load condition.

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“…Generally, PS pyrolysis oil yields vary between 90 wt.% and 99 wt.%. In a batch reactor, an oil yield of 89.5 wt.% was observed at 580 • C [34], while at a lower temperature (450 • C), the yield of liquid products was 56 wt.% [39].…”

Section: Polystyrene (Ps) Pyrolysis Oil Yieldsmentioning

confidence: 98%

Economic Assessment of Polypropylene Waste (PP) Pyrolysis in Circular Economy and Industrial Symbiosis

Zabaniotou

Vaskalis

2023

Energies

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Plastic waste has a high energy content and can be utilized as an energy source. This study aims to assess the economic feasibility of polypropylene plastic waste (PP) pyrolysis. A literature review was carried out to determine the optimal pyrolysis conditions for oil production. The preferred pyrolysis temperature ranges from 450 °C to 550 °C, where the oil yields vary from 82 wt.% to 92.3 wt.%. Two scenarios were studied. In the first scenario, pyrolysis gas is used for the pyrolysis heating needs, whereas in the second scenario, natural gas is used. An overview of the economic performance of a pyrolysis plant with a capacity of 200,000 t/year is presented. Based on the results, the plant is economically viable, as it presents high profits and a short payback time for both scenarios considered. Although the annual revenues are smaller in scenario 1, the significant reduction in operating costs makes this scenario preferable. The annual profits amount to 37.3 M€, while the return on investment is 81% and the payback time is 1.16 years. In scenario 2, although the plant is still feasible and shows high profitability, the annual profits are lower by about 1.5 M€, while the payback time is 1.2 years.

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Oil yield optimization from co-pyrolysis of low-density polyethylene (LDPE), polystyrene (PS) and polyethylene terephthalate (PET) using simplex lattice mixture design

Cited by 9 publications

References 37 publications

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis

An analysis of environment effect on ethanol blends with plastic fuel and blend optimization using a full factorial design

Economic Assessment of Polypropylene Waste (PP) Pyrolysis in Circular Economy and Industrial Symbiosis

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