Moisture content influence on composting parameters and degradation kinetic models in an aerated closed system
A variety of parameters including physical, chemical, and biological properties affect the degradation of organic matter during composting. Different input materials contribute to different composting performance, causing the characterisation of compost materials become crucial for benchmarking purp...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/79192/1/SitiNazrahZailaniPFChE2018.pdf |
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| Summary: | A variety of parameters including physical, chemical, and biological properties affect the degradation of organic matter during composting. Different input materials contribute to different composting performance, causing the characterisation of compost materials become crucial for benchmarking purpose. The challenges in characterisation become greater due to unavailability of standard method for identifying the compost stability in the open system. This study aimed to investigate the effect of initial moisture content on the properties of compost bed for composting process. It also aimed to predict the rate of composting in terms of the degradation of total organic carbon (TOC) for the compost inoculated with Bacillus coagulans (BC) and effective microorganism (EM). EM compost was used as positive control. An aerated closed composting system was used to characterise the composting parameters for the composts inoculated with the single culture of BC and the commercial mixed culture of EM. The composting materials consisted of 50% sawdust, 12% chicken dung and 38% rice husk with a fixed initial carbon to nitrogen ratio of 30. A closed and aerated compost batch reactor was fabricated with an optimum air flow rate of 0.3 L/min.kg compost to avoid oxygen limitation. The maximum compost temperature was recorded because it is important to predict the degradation of TOC by developing kinetic models for the degradation rate. The experimental data were fitted to four kinetic models with all models followed the first-order kinetic model equation, where the degradation rate constant, k, was corrected based on the model’s expression. Model 1 was corrected by the maximum compost temperature, model 2 was corrected by the initial moisture content, and model 3 and model 4 were corrected by the maximum compost temperature and initial moisture content. Model 1 was found to be the best-fitted model as it describes the degradation rate constant for composting well. Model 1 achieved a high sensitivity of the correlation for the degradation of TOC with regards to the water mass balance and energy balance. In summary, model 1, model 3, and model 4 can predict the degradation rate of TOC for the compost inoculated with BC or EM since their predictive power were R2 > 0.8. Model 2 showed the lowest predictive power (R2 = 0.484) for the degradation of TOC. The kinetic models developed for the composting using BC or EM could facilitate the prediction of TOC degradation in correlation to the initial moisture content, which is the most significant parameter that affects all other parameters (physical, chemical and biological) during composting. |
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