Tunnel composting Optimisation using polynomial models with moisture and density control for electrical conductivity stabilisation
Controlling electrical conductivity (EC), a key indicator of compost salinity, is essential to ensure the agronomic quality of compost produced from organic waste. This study assessed the effect of moisture content and bulk density on EC evolution across 72 composting batches using a mixture of biow...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Sustainable Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19397038.2025.2538867 |
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| Summary: | Controlling electrical conductivity (EC), a key indicator of compost salinity, is essential to ensure the agronomic quality of compost produced from organic waste. This study assessed the effect of moisture content and bulk density on EC evolution across 72 composting batches using a mixture of biowaste and green waste (Bio:Green ratio). The Bio:Green ratio (the mass proportion of biosolids to lignocellulosic green waste) served as a calibration tool for optimising initial process conditions. A polynomial regression model (R2 = 0.656) demonstrated that maintaining moisture between 34.7% and 37.5%, bulk density between 363.3 and 461.3 g/L, and a Bio:Green ratio between 1.2 and 1.4 ensures EC remains within the optimal range (3.75–4.0 mS/cm). These conditions minimise the need for corrective aeration or irrigation, enhancing process efficiency. Future studies may incorporate variables such as the carbon-to-nitrogen (C/N) ratio, microbial activity, and germination index to expand the model’s robustness and applicability. These findings offer a practical data-driven approach to compost EC control in industrial composting operations. |
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| ISSN: | 1939-7038 1939-7046 |