Cleaner energy for cleaner production: Modeling and optimization of biogas generation from Carica papayas (Pawpaw) fruit peels
| Autor: | Samuel Olatunde Dahunsi, Vincent Enontiemonria Efeovbokhan, Solomon U. Oranusi |
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| Rok vydání: | 2017 |
| Předmět: |
Waste management
Central composite design Renewable Energy Sustainability and the Environment Chemistry 020209 energy Strategy and Management Microorganism 02 engineering and technology 010501 environmental sciences 01 natural sciences Industrial and Manufacturing Engineering Anaerobic digestion Rumen Biogas Biofuel Yield (chemistry) 0202 electrical engineering electronic engineering information engineering Response surface methodology Food science 0105 earth and related environmental sciences General Environmental Science |
| Zdroj: | Journal of Cleaner Production. 156:19-29 |
| ISSN: | 0959-6526 |
| DOI: | 10.1016/j.jclepro.2017.04.042 |
| Popis: | In this study, the potentials of pretreated and untreated Carica papayas fruit peels for biogas generation was evaluated alongside its process optimization after employing the combination of mechanical and thermo-alkaline pretreatment methods. The peel was anaerobically digested using a consortium of microorganisms from cattle rumen content as inoculum. A batch system designed by the Central Composite Design (CCD) was employed. The physicochemical and microbial characteristics of the substrates and inoculum as well as the constituent of the generated biogas were evaluated using standard methods and results showed elevated levels of most elements after anaerobic digestion. The most feasible experimental biogas yields were 0.1839 m3/kg VS and 0.1361 m3/kg VS for the pretreated and untreated experiments respectively. Microbiologically, members of the genus Clostridium dominated the microbial flora and their succession patterns were affected by temperature and pH. The methane and carbon dioxide content of biogas from both experiments were 61.5± 2.5%; 24± 1% and 52 ± 2%; 25± 1.5% respectively. The Response Surface Methodology (RSM) and the Artificial Neural Networks (ANNs) were employed in data optimization. Based on the optimized values, the predicted biogas yield for RSM was 0.1895 m3/kg VS and 0.1839 m3/kg VS for ANNs in the pretreated experiment. For the experiment without pretreatment, the RSM predicted yield was 0.1361 m3/kg VS while that of ANNs was 0.1392 m3/kg VS. In all, there was a 26.5% increase in predicted biogas yield in the pretreated experiment over the untreated. Further usage of pawpaw peels for biofuels generation is advocated. |
| Databáze: | OpenAIRE |
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