# Thermochemical conversion modelling of multilayer packaging waste using Aspen Plus®

Abdul Rehman Khurram, Marion Carrier, Francisco Javier Escudero Sanz, Juma Haydary

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Abdul Rehman Khurram, Marion Carrier, Francisco Javier Escudero Sanz, Juma Haydary. Thermo-chemical conversion modelling of multilayer packaging waste using Aspen Plus®. 51st International Conference of the Slovak Society of Chemical Engineering SSCHE 2025, May 2025, Jasná, Demänovská Dolina, Slovakia., 2025. [https://hal-05169271](https://hal-05169271)

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Submitted on 26 Nov 2025

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<figure><img src="image_1.png" /></figure>
## 1 Introduction

* Paper and cardboard is the main packaging waste material, contributing 32.7 million tonnes to the total packaging waste generated in 2020 (Figure 1).

* The multilayer character of those wastes, typically Tetra Pak® packaging mainly composed of paper (Figure 2), make recycling difficult; as a result, they are mainly disposed of in landfills or incinerated causing environment issues.

* In this study, we propose to combine current hydropulping recycling to separate cellulosic fibers from Aluminium-LDPE laminate, while this latter is processed through thermochemical processes.

* Indeed, Pyrolysis is one waste conversion method that has received considerable attention due to its potential to reduce waste and recover valuable liquids and materials.

<figure><img src="image_2.png" /><figcaption>Figure 1: Packaging waste generated, European Union (27 countries)¹</figcaption></figure>

## 2 Objectives

The goals of this study are:

1) to develop process models for co-combustion and slow co-pyrolysis of high-fidelity waste simulant;

2) to quantify and manage mass streams balances.

<figure><img src="image_3.png" /><figcaption>Figure 2: Tetra Pak® composition</figcaption></figure>

## 3 Materials and methods

* Aluminium was not included in the feed for the current process model.

<figure><img src="image_4.png" /></figure>

* Experimental kinetics (Table 1) based degradation, followed by py-oil and py-gas yields distributions based on literature data⁴,⁵ with several assumptions.

<table><caption>Table 1: Compositional and kinetic data for the feed of thermochemical valorization process</caption><thead><tr><th></th><th>RCF</th><th>LLDPE</th><th>Char<sub>RCF</sub><sup>2,3</sup></th></tr></thead><tbody><tr><td><strong>Moisture</strong></td><td>3.3 ± 0.4</td><td>-</td><td>-</td></tr><tr><td><strong>Proximate analysis (wt%)<sup>a</sup></strong></td><td></td><td></td><td></td></tr><tr><td><strong>Ash</strong></td><td>5.8 ± 1</td><td>-</td><td>41.7<sup>d</sup></td></tr><tr><td><strong>Volatile matter</strong></td><td>79.9 ± 0.5</td><td>100 ± 0.4</td><td>13.5</td></tr><tr><td><strong>Fixed carbon</strong></td><td>14.3 ± 0.1</td><td>-</td><td>44.8</td></tr><tr><td><strong>Ultimate analysis (wt%)<sup>b</sup></strong></td><td></td><td></td><td></td></tr><tr><td><strong>C</strong></td><td>44.5 ± 0.9</td><td>84.5 ± 0.5</td><td>50.1</td></tr><tr><td><strong>H</strong></td><td>6.1 ± 0.3</td><td>15.5 ± 0.5</td><td>2.0</td></tr><tr><td><strong>O<sup>c</sup></strong></td><td>43.6 ± 1.4</td><td>-</td><td>6.2</td></tr><tr><td><strong>HHV (MJ/kg)</strong></td><td>16.9 ± 0.0</td><td>46.7 ± 0.2</td><td>-</td></tr><tr><td><strong>Pyrolysis global kinetic analysis</strong></td><td></td><td></td><td></td></tr><tr><td><strong>α (-)</strong></td><td>0.01 - 0.84</td><td>0.01 - 0.99</td><td>-</td></tr><tr><td><strong>E<sub>α</sub> (kJ/mol)</strong></td><td>206 ± 16</td><td>308 ± 19</td><td>-</td></tr><tr><td><strong>Log[A<sub>α</sub> (1/s)]</strong></td><td>14.5 ± 1.3</td><td>19.1 ± 1.3</td><td>-</td></tr></tbody></table>

a) Dry basis, b) Ash rich basis, c) By difference d) based on ash of RCF

<figure><img src="image_5.png" /><figcaption>Figure 3: Process flow diagram of thermo-chemical conversion processes</figcaption></figure>

## 4 Preliminary results and discussions

### Combustion

<figure><img src="image_6.png" /><figcaption>Figure 4: State of the flue gases</figcaption></figure>

### Pyrolysis

<table><caption>Table 2: Pyrolysis product flow rates (t/h) at $\tau$ = 30s and T = 500 °C</caption><thead><tr><th></th><th>RCF</th><th>LLDPE</th><th>Total flow</th></tr></thead><tbody><tr><td>Char</td><td>0.2</td><td>0.0</td><td>0.2</td></tr><tr><td>Py-oil</td><td>0.9</td><td>2.9</td><td>3.8</td></tr><tr><td>Py-gas</td><td>0.3</td><td>0.0</td><td>0.3</td></tr></tbody></table>

<table><caption>Table 3: Pyrolysis conversions at $\tau$ = 30s and T = 500 °C</caption><thead><tr><th></th><th>RCF</th><th>LLDPE</th></tr></thead><tbody><tr><td>Conversion</td><td>0.99</td><td>0.37</td></tr></tbody></table>

Combustion of 9.4 t/h of solid residues can produce ~17 MW of indicated horsepower.

LLDPE degradation kinetics is the limiting factor for the pyrolytic degradation of the solid residues (Table 3).

## 5 Conclusion and future work

Current modeling work shows that different modeling strategies must be adequately chosen and applied when it comes to simulate thermochemical conversion of solid residues from hydro-pulped multilayer packaging waste.

Thermodynamics based model was a good fit for the combustion process, whereas the approach of kinetic modeling calibrated with experimental yields aligns well with the pyrolysis of this waste.

Next, experimental yields for the real materials and process conditions in the same reactor design will be implemented to ease comparison and improve both models. Additionally, the water flow for hydro-pulping and the energy generation, or the valuables recovery will be optimized.

## 6 Acknowledgements

* The authors acknowledge the financial support by the French state managed by the National Research Agency in the name of France 2030 to conduct the French scientific program PAC-3R (ANR-22-PERE-0004).

* This work has benefited from State aid managed by the Agence Nationale de la Recherche under the Programme d'Investissements d'Avenir with the reference ANR-18-EURE-0021.

## 7 References

1. Eurostat, European Commission, 2020. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Packaging_waste_statistics.

2. Ultimate analysis adapted from Zhang et al. *Renewable and Sustainable Energy Reviews* 135 (2021): 110416.

3. Proximate analysis adapted from Smith et al. *Biomass and Bioenergy* 104 (2017): 17-35.

4. Volatile and gas yields for RCF adapted from Zhao et al. *Journal of the Energy Institute* 90.6 (2017): 902-913.

5. Volatile yield for LLDPE (as LDPE) adapted from Yousef et al. *Industrial Crops and Products* 218 (2024): 118970.