Energy Potential of Plastic Waste Valorization: A Short Comparative Assessment of Pyrolysis versus Gasification
Bibliographic record
Abstract
Plastics are abundant and have a high energy content making their use in energy applications attractive. This article presents a review on plastic waste (PW) management by pyrolysis and gasification, which are two types of thermochemical conversion (TCC) techniques. The conversion of PW and the application of its converted products are important steps toward reducing reliance on fossil fuels, enhancing closed-loop recycling of materials and the circular economy. The review presented herein also focuses on product distribution and yields with emphasis on the energy content and potential integration to energy systems and grids. It is found that pyro-oils have properties similar to conventional fuels such as diesel and can partially substitute for fossil fuels. In fact, the energy content of PW pyro-oils obtained by various researchers range from 41.10–46.16 MJ kg –1, which is close to the heating values of conventional fuels and thus are potential candidates for fuel applications. Typical treatment post-conversion is also conducted to maintain the quality of the oil produced and the removal of sulfur content to conform with market standards. On the other hand, syngas produced during gasification possesses a lower potential for fuel applications as its energy content may reach values as low as 20 MJ kg –1 in comparison to pyro-oil. However, depending on the process conditions, it is possible to increase the energy content to values of over 40 MJ kg –1 . Additionally, syngas is the building block for many valuable chemicals. With appropriate treatment, the syngas obtained from the gasification of PW can be used in gas engines and can be converted to commercial products such as liquid fuels via the Fischer–Tropsch synthesis. This review also highlights some available commercial-scale plants for the TCC of PW and real-life application of their obtained products. It is noted that the integration of the processes to energy systems is technically and economically feasible. Real-life applications of products obtained from the pyrolysis and gasification of PW in different parts of the world are also discussed. The produced fuels have been used in cooking stoves and burned in a gas turbine, internal combustion engine, and direct injection diesel engine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".